数字信号处理英文文献及翻译
南邮专业英语报告 信号处理导论完整版(包含翻译,原文和单词)
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SWEEP
样值处理算法来计算飘动的滤波器系数，再分别计算每次输入抽样的滤波。
Flanging、合唱、调相三种效果都是把一个简单滤波器的系数设计尾随输入
抽样变化而使滤波器成为时变滤波器。自适应信号处理也是随时间改变滤波器的
系数。系数与时间之间的关系是受某些设计条件的限制，即滤波器系数相对于输
入抽样调节并且优化。自适应算法的实施也就是要求滤波器的样值处理算法当中
英文原文
8.2 Digital Audio Effects Audio effects, such as delay, echo, reverberation, comb filtering, flanging, chorusing, pitch shifting, stereo imaging, distortion, compression, expansion, noise gating, and equalization, are indispensable in music production and performance [115 –151]. Some are also available for home and car audio systems.
程序chorus.m演示的是正弦信号经合唱处理后的情形。 调相(Phase Shifting)对吉他手、键盘演奏人员、歌唱家来说是经常采用的一种 效果。调相是把声音信号用一个窄带陷状滤波器过滤，再把过滤信号的一部分与 源信号相加而得到的。
陷点的频率以可控的方式调节，比如说可以用一个低频振荡器，也可以用脚踏板 控制。陷点附近的频率有较强的漂移，与原来的直接声音结合，使得相位在频率 轴上发生抵消或加强，整个相位在频率轴上出现波动。
dsp外文翻译
外文参考文献翻译英文题目 The Breadth and Depth of DSP 中文题目 DSP的广度和深度学院自动化与电气工程学院专业自动化姓名白学文学号 201108536指导教师王思明2015 年 04月 20日DSP的广度和深度数字信号处理是最强大的技术，将塑造二十一世纪的科学与工程之一。
革命性的变化已经在广泛的领域：通信，医疗成像，雷达和声纳，高保真音乐再现，石油勘探，仅举几例。
上述各领域已建立了深厚的DSP技术，用自己的算法，数学，和专门技术。
这种呼吸和深度的结合，使得它不可能为任何一个人掌握所有已开发的DSP技术。
DSP教育包含两个任务：学习一般适用于作为一个整体领域的概念，并学习您感兴趣的特定领域的专门技术。
本章开始描述DSP已在几个不同领域的戏剧性效果的数字信号处理的世界，我们的旅程。
革命已经开始。
1 DSP的根源独特的数据类型，它使用的信号，数字信号处理是区别于其他计算机科学领域。
在大多数情况下，这些信号源于感觉来自现实世界的数据：地震的震动，视觉图像，声波等DSP是数学，算法，并用来操纵这些信号的技术后，他们已被转换成数字形式。
这包括了各种目标，如：加强视觉图像识别和语音生成，存储和传输的数据压缩，等假设我们重视计算机模拟 - 数字转换器，并用它来获得一个现实世界的数据块。
DSP回答了这个问题：下一步怎么办？DSP的根是在20世纪60年代和70年代数字计算机时首次面世。
电脑是昂贵的，在这个时代，DSP是有限的，只有少数关键应用。
努力开拓，在四个关键领域：雷达和声纳，国家安全风险是石油勘探，可以大量资金;太空探索，其中的数据是不可替代的;和医疗成像，可节省生活。
20世纪80年代和90年代的个人电脑革命，引起新的应用DSP的爆炸。
而不是由军方和政府的需求动机，DSP的突然被带动的商业市场。
任何人士如认为他们可以使资金在迅速扩大的领域突然一个DSP供应商。
DSP的市民等产品达到：移动电话机，光盘播放器，电子语音邮件。
(完整版)数字信号处理英文文献及翻译
数字信号处理一、导论数字信号处理（DSP）是由一系列的数字或符号来表示这些信号的处理的过程的。
数字信号处理与模拟信号处理属于信号处理领域。
DSP包括子域的音频和语音信号处理，雷达和声纳信号处理，传感器阵列处理，谱估计，统计信号处理，数字图像处理，通信信号处理，生物医学信号处理，地震数据处理等。
由于DSP的目标通常是对连续的真实世界的模拟信号进行测量或滤波，第一步通常是通过使用一个模拟到数字的转换器将信号从模拟信号转化到数字信号。
通常，所需的输出信号却是一个模拟输出信号，因此这就需要一个数字到模拟的转换器。
即使这个过程比模拟处理更复杂的和而且具有离散值，由于数字信号处理的错误检测和校正不易受噪声影响，它的稳定性使得它优于许多模拟信号处理的应用（虽然不是全部）。
DSP算法一直是运行在标准的计算机，被称为数字信号处理器（DSP）的专用处理器或在专用硬件如特殊应用集成电路（ASIC）。
目前有用于数字信号处理的附加技术包括更强大的通用微处理器，现场可编程门阵列（FPGA），数字信号控制器（大多为工业应用，如电机控制）和流处理器和其他相关技术。
在数字信号处理过程中，工程师通常研究数字信号的以下领域：时间域（一维信号），空间域（多维信号），频率域，域和小波域的自相关。
他们选择在哪个领域过程中的一个信号，做一个明智的猜测（或通过尝试不同的可能性）作为该域的最佳代表的信号的本质特征。
从测量装置对样品序列产生一个时间或空间域表示，而离散傅立叶变换产生的频谱的频率域信息。
自相关的定义是互相关的信号本身在不同时间间隔的时间或空间的相关情况。
二、信号采样随着计算机的应用越来越多地使用，数字信号处理的需要也增加了。
为了在计算机上使用一个模拟信号的计算机，它上面必须使用模拟到数字的转换器（ADC）使其数字化。
采样通常分两阶段进行，离散化和量化。
在离散化阶段，信号的空间被划分成等价类和量化是通过一组有限的具有代表性的信号值来代替信号近似值。
数字信号处理的翻译
- 一个网页浏览器软件
- 一个播放软件，支持wav声音格式
- 一个播放软件，支持AVI视频格式
2。要查看此CD的内容，请打开
INDEX.HTM在网页浏览器中的文件。
3。 “方案”的目录包含几个目录
在这本书的章节中使用的方案，编写和测试下
MATLAB 7.0版本。为方便起见，这些文件已被
此CD包含的补充材料
文字书“数字信号处理：
基于计算机的方法“，第三版。
SK米特拉，ISBN 0073043869。
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PDF格式的最常用的功能和一些基本概念
与MATLAB。
7。 “常见问题”目录中包含一些常见的答案
其中读者学习本书时可能遇到的的问题。
8。以下的音乐声演示教授柯蒂斯道路和大卫先生Thall提供，
媒体艺术和技术方案，美国加州大学圣巴巴拉分校。
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信号处理中英文对照外文翻译文献
信号处理中英文对照外文翻译文献(文档含英文原文和中文翻译)译文：一小波研究的意义与背景在实际应用中，针对不同性质的信号和干扰，寻找最佳的处理方法降低噪声，一直是信号处理领域广泛讨论的重要问题。
目前有很多方法可用于信号降噪，如中值滤波，低通滤波，傅立叶变换等，但它们都滤掉了信号细节中的有用部分。
传统的信号去噪方法以信号的平稳性为前提，仅从时域或频域分别给出统计平均结果。
根据有效信号的时域或频域特性去除噪声，而不能同时兼顾信号在时域和频域的局部和全貌。
更多的实践证明，经典的方法基于傅里叶变换的滤波，并不能对非平稳信号进行有效的分析和处理，去噪效果已不能很好地满足工程应用发展的要求。
常用的硬阈值法则和软阈值法则采用设置高频小波系数为零的方法从信号中滤除噪声。
实践证明，这些小波阈值去噪方法具有近似优化特性，在非平稳信号领域中具有良好表现。
小波理论是在傅立叶变换和短时傅立叶变换的基础上发展起来的，它具有多分辨分析的特点，在时域和频域上都具有表征信号局部特征的能力，是信号时频分析的优良工具。
小波变换具有多分辨性、时频局部化特性及计算的快速性等属性，这使得小波变换在地球物理领域有着广泛的应用。
随着技术的发展，小波包分析(Wavelet Packet Analysis)方法产生并发展起来，小波包分析是小波分析的拓展，具有十分广泛的应用价值。
它能够为信号提供一种更加精细的分析方法，它将频带进行多层次划分，对离散小波变换没有细分的高频部分进一步分析，并能够根据被分析信号的特征，自适应选择相应的频带，使之与信号匹配，从而提高了时频分辨率。
小波包分析(wavelet packet analysis)能够为信号提供一种更加精细的分析方法，它将频带进行多层次划分，对小波分析没有细分的高频部分进一步分解，并能够根据被分析信号的特征，自适应地选择相应频带,使之与信号频谱相匹配，因而小波包具有更广泛的应用价值。
利用小波包分析进行信号降噪，一种直观而有效的小波包去噪方法就是直接对小波包分解系数取阈值，选择相关的滤波因子，利用保留下来的系数进行信号的重构，最终达到降噪的目的。
数字信号处理(英文版)1-连续时间信号系统
Unit impulse function δ(t)
With a gate signal pτ(t), short the duration τ and keep the unit area
4/τ 2/τ 1/τ
1/τ
-τ/2
τ/2
-τ/4
τ/4
-τ/8 τ/8
When τ0, the amplitude tends to , which means it is impossible to define δ(t) by a regular function.
Typical signals and their representation
Gate signal
p (t ) 0
1
|t |
2
1 -τ/2 τ/2
|t |
2
The gate signal can be represented by unit step signals:
(t )dt (t )dt (t )dt u (t )
0
0
Properties of δ(t)
δ(t) is a even function, that is
δ(t) = δ(-t) We got δ(t) from a gate signal, and gate signal is an even function. It is also easy to give the math show of the even property.
Typical signals and their representation
Sinusoidal Asin(ωt+υ)
数字信号处理英文文献及翻译
英文原文The simulation and the realization of the digital filterWith the information age and the advent of the digital world, digital signal processing has become one of today's most important disciplines and door technology. Digital signal processing in communications, voice, images, automatic control, radar, military, aerospace, medical and household appliances, and many other fields widely applied. In the digital signal processing applications, the digital filter is important and has been widely applied.1、 figures Unit on :Analog and digital filtersIn signal processing, the function of a filter is to remove unwanted parts of the signal, such as random noise, or to extract useful parts of the signal, such as the components lying within a certain frequency range.The following block diagram illustrates the basic idea.There are two main kinds of filter, analog and digital. They are quitedifferent in their physical makeup and in how they work. An analog filter uses analog electronic circuits made up from components such as resistors, capacitors and op amps to produce the required filtering effect. Such filter circuits are widely used in such applications as noise reduction, video signal enhancement, graphic equalisers in hi-fi systems, and many other areas. There are well-established standard techniques for designing an analog filter circuit for a given requirement. At all stages, the signal being filtered is an electrical voltage or current which is the direct analogue of the physical quantity (e.g. a sound or video signal or transducer output) involved. Adigital filter uses a digital processor to perform numerical calculations on sampled values of the signal. The processor may be a general-purpose computersuch as a PC, or a specialised DSP (Digital Signal Processor) chip. The analog input signal must first be sampled and digitised using an ADC (analog todigital converter). The resulting binary numbers, representing successive sampled values of the input signal, are transferred to theprocessor, which carries out numerical calculations on them. These calculations typically involve multiplying the input values by constants and adding the products together. If necessary, the results of these calculations, which now represent sampled values of the filtered signal, are output through a DAC (digital to analog converter) to convert the signal back to analog form.Note that in a digital filter, the signal is represented by a sequence of numbers, rather than a voltage or current.The following diagram shows the basic setup of such a system.Unit refers to the input signals used to filter hardware or software. If the filter input, output signals are separated, they are bound to respond to the impact of the Unit is separated, such as digital filters filter definition. Digital filter function, which was to import sequences X transformation into export operations through a series Y.According to figures filter function 24-hour live response characteristics, digital filters can be divided into two, namely, unlimited long live long live the corresponding IIR filter and the limited response to FIR filters. IIRfilters have the advantage of the digital filter design can use simulation results, and simulation filter design of a large number of tables mayfacilitate simple. It is the shortcomings of the nonlinear phase; Linear phase if required, will use the entire network phase-correction. Image processing and transmission of data collection is required with linear phase filters identity. And FIR linear phase digital filter to achieve, but an arbitrary margincharacteristics. Impact from the digital filter response of the units can be divided into two broad categories : the impact of the limited response (FIR) filters, and unlimited number ofshocks to (IIR) digital filters.FIR filters can be strictly linear phase, but because the system FIR filter function extremity fixed at the original point, it can only use the higher number of bands to achieve their high selectivity for the same filter design indicators FIR filter called band than a few high-IIR 5-10 times, the cost is higher, Signal delay is also larger. But if the same linear phase, IIR filters must be network-wide calibration phase, the same section also increase the number of filters and network complexity. FIR filters can be used to achieve non-Digui way, not in a limited precision of a shock, and into the homes and quantitative factors of uncertainty arising from the impact of errors than IIR filter small number, and FIR filter can be used FFT algorithms, the computational speed. But unlike IIR filter can filter through the simulation results, there is no ready-made formula FIR filter must use computer-aided design software (such as MATLAB) to calculate. So, a broader application of FIR filters, and IIR filters are not very strict requirements on occasions.Unit from sub-functions can be divided into the following four categories :(1) Low-filter (LPF);(2) high-filter (HPF);(3) belt-filter (BPF);(4) to prevent filter (BSF).The following chart dotted line for the ideals of the filter frequency characteristics :A1(f) A2(f)10 c2f c2 f(a) (b)A3(f) A4(f)0 c1c2f c1c2 f(c) (d)(a)LPF (b)HPF (c)BPF (d)BSF2、 MATLAB introducedMATLAB is a matrix laboratory (Matrix Laboratory) is intended. In addition to an excellent value calculation capability, it also provides professional symbols terms, word processing, visualization modeling, simulation and real-time control functions. MATLAB as the world's top mathematical software applications, with a strong engineering computing, algorithms research, engineering drawings, applications development, data analysis and dynamic simulation, and other functions, in aerospace, mechanical manufacturing and construction fields playing an increasingly important role. And the C language function rich, the use of flexibility, high-efficiency goals procedures. High language both advantages as well as low level language features. Therefore, C language is the most widely used programming language. Although MATLAB is a complete, fully functional programming environment, but in some cases, data and procedures with the external environment of the world is very necessary and useful. Filter design using Matlab, could be adjusted with the design requirements and filter characteristics of the parameters, visual simple, greatly reducing the workload for the filter design optimization.In the electricity system protection and secondary computer control, many signal processing and analysis are based on are certain types Yeroskipou and the second harmonics of the system voltage and current signals (especially at D process), are mixed with a variety of complex components, the filter has been installed power system during the critical components. Current computer protection and the introduction of two digital signal processing software main filter. Digital filter design using traditional cumbersome formula, the need to change the parameters after recalculation, especially in high filters, filter design workload. Uses MATLAB signal processing boxes can achieve rapid and effective digital filter design and simulation.MATLAB is the basic unit of data matrix, with its directives Biaodashi mathematics, engineering, commonly used form is very similar, it is used to solve a problem than in MATLAB C, Fortran and other languages End precision much the same thing. The popular MATLAB 5.3/Simulink3.0 including hundreds of internal function with the main pack and 30 types of tool kits (Toolbox). kits can be divided into functional tool kits and disciplines toolkit. MATLAB tool kit used to expand the functional symbols terms, visualization simulation modelling, word processing and real-time control functions. professional disciplines toolkit is a stronger tool kits, tool kits control, signal processing tool kit, tool kits, etc. belonging to such communicationsMATLAB users to open widely welcomed. In addition to the internal function, all the packages MATLAB tool kits are readable document and the document could be amended, modified or users through Yuanchengxu the construction of new procedures to prepare themselves for kits.3、 Digital filter designDigital filter design of the basic requirementsDigital filter design must go through three steps :(1) Identification of indicators : In the design of a filter, there must be some indicators. These indicators should be determined on the basis of the application. In many practical applications, digital filters are often used to achieve the frequency operation. Therefore, indicators in the form of general jurisdiction given frequency range and phase response. Margins key indicators given in two ways. The first is absolute indicators. It provides a function to respond to the demands of the general application of FIR filter design. The second indicator is the relative indicators. Its value in the form of answers to decibels. In engineering practice, the most popular of such indicators. For phase response indicators forms, usually in the hope that the system with a linear phase frequency bands human. Using linear phase filter design with thefollowing response to the indicators strengths：①it only contains a few algorithms, no plural operations；②there is delay distortion, only a fixed amount of delay; ③the filter length N (number of bands for N-1), the volume calculation for N/2 magnitude.(2) Model approach : Once identified indicators can use a previous study of the basic principles and relationships, a filter model to be closer to the target system.(3) Achieved : the results of the above two filters, usually by differential equations, system function or pulse response to describe. According to this description of hardware or software used to achieve it.4、 Introduced FPGA Programmable logic device is a generic logic can use a variety of chips, which is to achieve ASIC ASIC (Application Specific Integrated Circuit) semi-customized device, Its emergence and development of electronic systems designers use CAD tools to design their own laboratory in the ASIC device. Especially FPGA (Field Programmable Gate Array) generated and development, as a microprocessor, memory, the figures for electronic system design and set a new industry standard (that is based on standard product sales catalogue in the market to buy). Is a digital system for microprocessors, memories, FPGA or three standard building blocks constitute their integration direction.Digital circuit design using FPGA devices, can not only simplify the design process and can reduce the size and cost of the entire system, increasing system reliability. They do not need to spend the traditional sense a lot of time and effort required to create integrated circuits, to avoid the investment risk and become the fastest-growing industries of electronic devices group. Digital circuit design system FPGA devices using the following main advantages (1) Design flexibleUse FPGA devices may not in the standard series device logic functional limitations. And changes in system design and the use of logic in any one stage of the process, and only through the use of re-programming the FPGA device can be completed, the system design provides for great flexibility.(2) Increased functional densityFunctional density in a given space refers to the number of functional integration logic. Programmable logic chip components doors several high, a FPGA can replace several films, film scores or even hundreds of small-scale digital IC chip illustrated in the film. FPGA devices using the chip to use digital systems in small numbers, thus reducing the number of chips used to reduce the number of printed size and printed, and will ultimately lead to a reduction in the overall size of the system.(3) Improve reliabilityPrinting plates and reduce the number of chips, not only can reduce system size, but it greatly enhanced system reliability. A higher degree ofintegration than systems in many low-standard integration components for the design of the same system, with much higher reliability. FPGA device used to reduce the number of chips required to achieve the system in the number printed on the cord and joints are reduced, the reliability of the system can be improved.(4) Shortening the design cycleAs FPGA devices and the programmable flexibility, use it to design a system for longer than traditional methods greatly shortened. FPGA device master degrees high, use printed circuit layout wiring simple. At the same time, success in the prototype design, the development of advanced tools, a high degree of automation, their logic is very simple changes quickly. Therefore, the use of FPGA devices can significantly shorten the design cycle system, and speed up the pace of product into the market, improving product competitiveness.(5) Work fastFPGA/CPLD devices work fast, generally can reach several original Hertz, far larger than the DSP device. At the same time, the use of FPGA devices, the system needed to achieve circuitclasses and small, and thus the pace of work of the entire system will be improved.(6) Increased system performance confidentialityMany FPGA devices have encryption functions in the system widely used FPGA devices can effectively prevent illegal copying products were others(7) To reduce costsFPGA device used to achieve digital system design, if only device itself into the price, sometimes you would not know it advantages, but there are many factors affecting the cost of the system, taken together, the cost advantages of using FPGA is obvious. First, the use of FPGA devices designed to facilitate change, shorten design cycles, reduce development costs for system development; Secondly, the size and FPGA devices allow automation needs plug-ins, reducing the manufacturing system to lower costs; Again, the use of FPGA devices can enhance system reliability, reduced maintenance workload, thereby lowering the cost of maintenance services for the system. In short, the use of FPGA devices for system design to save costs.FPGA design principles :FPGA design an important guiding principles : the balance and size and speed of exchange, the principles behind the design of the filter expression of a large number of certification.Here, "area" means a design exertion FPGA/CPLD logic resources of the FPGA can be used to the typical consumption (FF) and the search table (IUT) to measuremore general measure can be used to design logic equivalence occupied by the door is measured. "pace" means stability operations in the chip design can achieve the highest frequency, the frequency of the time series design situation, and design to meet the clock cycle -- PADto pad, Clock Setup Time, Clock Hold Beijing, Clock-to-Output Delay, and other characteristics of many time series closely related. Area (area) and speed (speed) runs through the two targets FPGA design always is the ultimate design quality evaluation criteria. On the size and speed of the two basic concepts : balance of size and speed and size and speed of swap.One pair of size and speed is the unity of opposites contradictions body. Requirements for the design of a design while the smallest, highest frequency of operation is unrealistic. More scientific goal should be to meet the design requirements of the design time series (includes requirements for the design frequency) premise, the smallest chip area occupied. Or in the specified area, the design time series cushion greater frequency run higher. This fully embodies the goals of both size and speed balanced thinking. On the size and speed requirements should not be simply interpreted as raising the level and design engineers perfect sexual pursuit, and should recognize that they are products and the quality and cost of direct relevance. If time series cushion larger design, running relatively high frequency, that the design Jianzhuangxing stronger, more quality assurance system as a whole; On the other hand, the smaller size of consumption design is meant to achieve in chip unit more functional modules, the chip needs fewer, the entire system has been significantly reduced cost. As a contradiction of the two components, the size and speed is not the same status. In contrast, meet the timetables and work is more important for some frequency when both conflicts, the use of priority guidelines.Area and the exchange rate is an important FPGA design ideas. Theoretically, if a design time series cushion larger, can run much higher than the frequency design requirements, then we can through the use of functional modules toreduce the consumption of the entire chip design area, which is used for space savings advantages of speed; Conversely, if the design of a time series demanding, less than ordinary methods of design frequency then generally flow through the string and data conversion, parallel reproduction of operational module, designed to take on the whole "string and conversion" and operate in the export module to chip in the data "and string conversion" from the macro point of view the whole chip meets the requirements of processing speed, which is equivalent to the area of reproduction - rate increase.For example. Assuming that the digital signal processing system is 350Mb/s input data flow rate, and in FPGA design, data processing modules for maximum processing speed of 150Mb/s, because the data throughput processing module failed to meet requirements, it is impossible to achieve directly in the FPGA. Such circumstances, they should use "area-velocity" thinking, at least three processing modules from the first data sets will be imported and converted, and then use these three modules parallel processing of data distribution, then the results "and string conversion," we have complete data rate requirements. We look at both ends of the processing modules, data rate is 350Mb/s, and in view of the internal FPGA, each sub-module handles the data rate is 150Mb/s, in fact, all the data throughput is dependent on three security modules parallel processing subsidiary completed, that is used by more chip area achieve high-speed processing through "the area of reproduction for processing speed enhancement" and achieved design.FPGA is the English abbreviation Field of Programmable Gate Array for the site programmable gate array, which is in Pal, Gal, Epld, programmable device basis to further develop the product. It is as ASIC (ASIC) in the field of a semi-customized circuit and the emergence of both a customized solution to the shortage circuit, but overcome the original programmable devices doors circuit few limited shortcomings.FPGA logic module array adopted home (Logic Cell Array), a new concept of internal logic modules may include CLB (Configurable Logic Block), export import module IOB (Input Output Block) and internal links (Interconnect) 3. FPGA basic features are :(1) Using FPGA ASIC design ASIC using FPGA circuits, the chip can be used,while users do not need to vote films production.(2) FPGA do other customized or semi-customized ASIC circuits throughout the Chinese specimen films.3) FPGA internal capability and rich I/O Yinjue.4) FPGA is the ASIC design cycle, the shortest circuit, the lowest development costs, risks among the smallest device5) FPGA using high-speed Chmos crafts, low consumption, with CMOS, TTL low-power compatibleIt can be said that the FPGA chip is for small-scale systems to improve system integration, reliability one of the bestCurrently FPGA many varieties, the Revenue software series, TI companies TPC series, the fiex ALTERA company series FPGA is stored in films from theinternal RAM procedures for the establishment of the state of its work, therefore, need to programmed the internal Ram. Depending on the different configuration, users can use a different programming methodsPlus electricity, FPGA, EPROM chips will be read into the film, programming RAM 中 data, configuration is completed, FPGA into working order. Diaodian, FPGA resume into white films, the internal logic of relations disappear, FPGA to repeated use. FPGA's programming is dedicated FPGA programming tool, using generic EPROM, prom programming device can. When the need to modify functional FPGA, EPROM can only change is. Thus, with a FPGA, different programming datato produce different circuit functions. Therefore, the use of FPGA very flexible.There are a variety of FPGA model : the main model for a parallel FPGA plus a EPROM manner; From the model can support a number of films FPGA; serial prom programming model could be used serial prom FPGA programming FPGA; The external model can be engineered as microprocessors from its programming microprocessors.Verilog HDL is a hardware description language for the algorithm level, doors at the level of abstract level to switch-level digital system design modelling. Modelling of the target figure by the complexity of the system can be something simple doors and integrity of electronic digital systems. Digital system to the levels described, and in the same manner described in Hin-time series modelling.Verilog HDL language with the following description of capacity : design behaviour characteristics, design data flow characteristics, composition and structure designed to control and contain the transmission and waveform design a certification mechanism. All this with the use of a modelling language. In addition, Verilog HDL language programming language interface provided by the interface in simulation, design certification from the external design of the visit, including specific simulation control and operation.Verilog HDL language grammar is not only a definition, but the definition of each grammar structure are clear simulation, simulation exercises. Therefore, the use of such language to use Verilog simulation models prepared by a certification. From the C programming language, the language inherited multiple operating sites and structures. Verilog HDL provides modelling capacity expansion, many of the initial expansion would be difficult to understand. However, the core subsets of Verilog HDL language very easy to learn and use, which is sufficient for most modelling applications. Of course, the integrityof the hardware description language is the most complex chips from theintegrity of the electronic systems described.historyVerilog HDL language initially in 1983 by Gateway Design Automation companies for product development simulator hardware modelling language. Then it is only a dedicated language. Since their simulation, simulation devices widely used products, Verilog HDL as a user-friendly and practical language for many designers gradually accepted. In an effort to increase the popularity of the language activities, Verilog HDL language in 1990 was a public area. Open Verilog International (OVI) is to promote the development of Verilog international organizations. 1992, decided to promote OVI OVI standards as IEEE Verilog standards. The effort will ultimately succeed, a IEEE1995 Verilog language standard, known as IEEE Std 1364-1995. Integrity standards in Verilog hardware description language reference manual contains a detailed description.Main capacity：Listed below are the main Verilog hardware description language ability*Basic logic gate, and, for example, or have embedded in the language and nand * Users of the original definition of the term (UDP), the flexibility. Users can be defined in the original language combinations logic original language, the original language of logic could also be time series* Switches class infrastructure models, such as the nmos and pmos also be embedded in the language* Hin-language structure designated for the cost of printing the design and trails Shi Shi and design time series checks.* Available three different ways to design or mixed mode modelling. These methods include : acts described ways - use process of structural modelling; Data flow approach - use of a modelling approach Fuzhi expression; Structured way - using examples of words to describe modular doors and modelling.* Verilog HDL has two types of data : data types and sequence data line network types. Line network types that the physical links between components and sequence types that abstract data storage components.* To describe the level design, the structure can be used to describe any level module example * Design size can be arbitrary; Language is design size (size) impose any restrictions* Verilog HDL is no longer the exclusive language of certain companies but IEEE standards. * And the machine can read Verilog language, it may as EDA tools and languages of the world between the designers* Verilog HDL language to describe capacity through the use of programming language interface (PLI) mechanism further expansion. PLI is to allow external functions of the visit Verilog module information, allowing designers and simulator world Licheng assembly* Design to be described at a number of levels, from the switch level, doors level, register transfer level (RTL) to the algorithm level, including thelevel of process and content* To use embedded switching level of the original language in class switch design integrity modelling* Same language can be used to generate simulated incentive and certification by the designated testing conditions, such as the value of imports of the designated*Verilog HDL simulation to monitor the implementation of certification, the certification process of implementing the simulation can be designed to monitorand demonstrate value. These values can be used to compare with the expectations that are not matched in the case of print news reports.* Acts described in the class, not only in the RTL level Verilog HDL design description, and to describe their level architecture design algorithm level behavioural description* Examples can use doors and modular structure of language in a class structure described* Verilog HDL mixed mode modelling capabilities in the design of a different design in each module can level modelling* Verilog HDL has built-in logic function, such as*Structure of high-level programming languages, such as conditions of expression, and the cycle of expression language, language can be used* To it and can display regular modelling* Provide a powerful document literacy* Language in the specific circumstances of non-certainty that in the simulator, different models can produce different results; For example, describing events in the standard sequence of events is not defined.5、In troduction of DSPToday, DSP is w idely used in the modern techno logy and it has been the key part of many p roducts and p layed more and mo re impo rtant ro le in our daily life.Recent ly, Northw estern Po lytechnica lUniversity Aviation Microelect ronic Center has comp leted the design of digital signal signal p rocesso r co re NDSP25, w h ich is aim ing at TM S320C25 digital signal p rocesso r of Texas Inst rument TM S320 series. By using top 2dow n design flow , NDSP25 is compat ible w ith inst ruct ion and interface t im ing of TM S320C25.Digital signal processors (DSP) is a fit for real-time digital signal processing for high-speed dedicated processors, the main variety used for real-time digital signal processing to achieve rapid algorithms. In today's digital age background, the DSP has become the communications, computer, and consumer electronics products, and other fields based device.Digital signal processors and digital signal processing is inseparably, we usually say "DSP" can also mean the digital signal processing (Digital Signal Processing), is that in this digital signal processors Lane. Digital signal processing is a cover many disciplines applied to many areas and disciplines, refers to the use of computers or specialized processing equipment, the signals in digital form for the collection, conversion, recovery, valuation, enhancement, compression, identification, processing, the signals are compliant form. Digital signal processors for digital signal processing devices, it is accompanied by a digital signal processing to produce. DSP development process is broadly divided into three phases : the 20th century to the 1970s theorythat the 1980s and 1990s for the development of products. Before the emergence of the digital signal processing in the DSP can only rely on microprocessors (MPU) to complete. However, the advantage of lower high-speed real-time processing can not meet the requirements. Therefore, until the 1970s, a talent made based DSP theory and algorithms. With LSI technology development in 1982 was the first recipient of the world gave birth to the DSP chip. Years later, the second generation based on CMOS工艺 DSP chips have emerged. The late1980s, the advent of the third generation of DSP chips. DSP is the fastest-growing 1990s, there have been four successive five-generation and the generation DSP devices. After 20 years of development, the application of DSP products has been extended to people's learning, work and all aspects of life and gradually become electronics products determinants.中文翻译。
数字信号处理(第二版)(英文版) (7)
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Understanding DSP, Second Edition
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• Notice that the sudden changes in our input sequence of cars/minute are flattened out by our averager, just like passing an low-pass filter
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• In the case of averaging, y(n)th output is given by
• Write in a more general way
• For a general N-tap FIR filter, the nth output is
Understanding DSP, Second Edition
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Convolution of filter coefficients and the filter’s output impulse response
Understanding DSP, Second Edition
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• If we take a DFT transform of h(k) and x(n), we can get the following expression
• Relationships of convolution as applied to FIR digital filters
Understanding DSP, Second Edition
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Conclusion through the example of averaging
• FIR filters perform time-domain convolution by summing the products of the shifted input samples and a sequence of filter coefficients
电气类外文翻译---数字信号处理控制器
文献翻译TMS320LF2407, TMS320LF2406, TMS320LF2402TMS320LC2406, TMS320LC2404, MS320LC2402DSP CONTROLLERSThe TMS320LF240x and TMS320LC240x devices, new members of the ‘24x family of digital signal processor (DSP) controllers, are part of the C2000 platform of fixed-point DSPs. The ‘240x devices offer the enhanced TMS320 architectural design of the ‘C2xx core CPU for low-cost, low-power, high-performance processing capabilities. Several advanced peripherals, optimized for digital motor and motion control applications, have been integrated to provide a true single chip DSP controller. While code-compatible with the existing ‘24x DSP controller devices, the ‘240x offers increased processing performance (30 MIPS) and a higher level of peripheral integration. See the TMS320x240x device summary section for device-specific features.The ‘240x family offers an array of memory sizes and different peripherals tailored to meet the specific price/performance points required by various applications. Flash-based devices of up to 32K words offer a reprogrammable solution useful for: Applications requiring field programmability upgrades.Development and initial prototyping of applications that migrate to ROM-based devices.Flash devices and corresponding ROM devices are fully pin-to-pin compatible. Note that flash-based devices contain a 256-word boot ROM to facilitate in-circuit programming.All ‘240x devices offer at least one event manager module which has been optimized for digital motor control and power conversion applications. Capabilities of this module include centered- and/or edge-aligned PWM generation, programmabledeadband to prevent shoot-through faults, and synchronized analog-to-digital conversion. Devices with dual event managers enable multiple motor and/or converter control with a single ‗240x DSP controller.The high performance, 10-bit analog-to-digital converter (ADC) has a minimum conversion time of 500 ns and offers up to 16 channels of analog input. The auto sequencing capability of the ADC allows a maximum of 16 conversions to take place in a single conversion session without any CPU overhead.A serial communications interface (SCI) is integrated on all devices to provide asynchronous communication to other devices in the system. For systems requiring ad ditional communication interfaces; the ‘2407, ‘2406, and ‘2404 offer a 16-bit synchronous serial peripheral interface (SPI). The ‘2407 and ‘2406 offer a controller area network (CAN) communications module that meets 2.0B specifications. To maximize device flexibility, functional pins are also configurable as general purpose inputs/outputs (GPIO).To streamline development time, JTAG-compliant scan-based emulation has been integrated into all devices. This provides non-intrusive real-time capabilities required to debug digital control systems. A complete suite of code generation tools from C compilers to the industry-standard Code Composerdebugger supports this family. Numerous third party developers not only offer device-level development tools, but also system-level design and development support.PERIPHERALSThe integrated peripherals of the TMS320x240x are described in the following subsections:1Two event-manager modules (EV A, EVB)2Enhanced analog-to-digital converter (ADC) module3Controller area network (CAN) module3Serial communications interface (SCI) module4Serial peripheral interface (SPI) module5PLL-based clock module6Digital I/O and shared pin functions7External memory interfaces (‘LF2407 only)8Watchdog (WD) timer moduleEvent manager modules (EV A, EVB)The event-manager modules include general-purpose (GP) timers, full-compare/PWM units, capture units, and quadrature-encoder pulse (QEP) circuits. EV A‘s and EVB‘s timers, compare units, and capture units function identically. However, timer/unit names differ for EV A and EVB. Table 1 shows the module and signal names used. Table 1 shows the features and functionality available for the event-manager modules and highlights EV A nomenclature.Event managers A and B have identical peripheral register sets with EV A starting at 7400h and EVB starting at 7500h. The paragraphs in this section describe the function of GP timers, compare units, capture units, and QEPs using EV A nomenclature. These paragraphs are applicable to EVB with regard to function—however, module/signal names would differ.Table 1. Module and Signal Names for EV A and EVBEVENT MANAGER MODULESEV AMODULESIGNALEVBMODULESIGNALGP Timers Timer 1Timer 2T1PWM/T1CMPT2PWM/T2CMPTimer 3Timer 4T3PWM/T3CMPT4PWM/T4CMPCompare Units Compare 1Compare 2Compare 3PWM1/2PWM3/4PWM5/6Compare 4Compare 5Compare 6PWM7/8PWM9/10PWM11/12Capture Units Capture 1Capture 2Capture 3CAP1CAP2CAP3Capture 4Capture 5Capture 6CAP4CAP5CAP6QEP QEP1QEP2QEP1QEP2QEP3QEP4QEP3QEP4External Inputs DirectionExternalClockTDIRATCLKINADirectionExternal ClockTDIRBTCLKINBGeneral-purpose (GP) timersThere are two GP timers: The GP timer x (x = 1 or 2 for EV A; x = 3 or 4 for EVB) includes:1.A 16-bit timer, up-/down-counter, TxCNT, for reads or writes2.A 16-bit timer-compare register, TxCMPR (double-buffered with shadowregister), for reads or writes3.A 16-bit timer-period register, TxPR (double-buffered with shadow register),for reads or writes4.A 16-bit timer-control register,TxCON, for reads or writes5.Selectable internal or external input clocks6.A programmable prescaler for internal or external clock inputs7.Control and interrupt logic, for four maskable interrupts: underflow, overflow,timer compare, and period interrupts8.A selectable direction input pin (TDIR) (to count up or down when directionalup-/down-count mode is selected)The GP timers can be operated independently or synchronized with each other. The compare register associated with each GP timer can be used for compare function and PWM-waveform generation. There are three continuous modes of operations for each GP timer in up- or up/down-counting operations. Internal or external input clocks with programmable prescaler are used for each GP timer. GP timers also provide the time base for the other event-manager submodules: GP timer 1 for all the compares and PWM circuits, GP timer 2/1 for the capture units and the quadrature-pulse counting operations. Double-buffering of the period and compare registers allows programmable change of the timer (PWM) period and the compare/PWM pulse width as needed.Full-compare unitsThere are three full-compare units on each event manager. These compare units use GP timer1 as the time base and generate six outputs for compare and PWM-waveform generation using programmable deadband circuit. The state of each of the six outputs is configured independently. The compare registers of the compare units are double-buffered, allowing programmable change of the compare/PWM pulse widths as needed.Programmable deadband generatorThe deadband generator circuit includes three 8-bit counters and an 8-bit compare register. Desired deadband values (from 0 to 24 µs) can be programmed into the compare register for the outputs of the three compare units. The deadband generation can be enabled/disabled for each compare unit output individually. The deadband-generator circuit produces two outputs (with or without deadband zone) for each compare unit output signal. The output states of the deadband generator are configurable and changeable as needed by way of the double-buffered ACTR register.PWM waveform generationUp to eight PWM waveforms (outputs) can be generated simultaneously by each event manager: three independent pairs (six outputs) by the three full-compare units with programmable deadbands, and two independent PWMs by the GP-timer compares.PWM characteristicsCharacteristics of the PWMs are as follows:●16-bit registers●Programmable deadband for the PWM output pairs, from 0 to 24 µs●Minimum deadband width of 50 ns●Change of the PWM carrier frequency for PWM frequency wobbling asneeded●Change of the PWM pulse widths within and after each PWM period asneeded●External-maskable power and drive-protection interrupts●Pulse-pattern-generator circuit, for programmable generation of asymmetric,symmetric, and four-space vector PWM waveforms●Minimized CPU overhead using auto-reload of the compare and periodregistersCapture unitThe capture unit provides a logging function for different events or transitions. The values of the GP timer 2 counter are captured and stored in the two-level-deep FIFO stacks when selected transitions are detected on capture input pins, CAPx (x = 1, 2, or 3 for EV A; and x = 4, 5, or 6 for EVB). The capture unit consists of three capture circuits.Capture units include the following features:●One 16-bit capture control register, CAPCON (R/W)●One 16-bit capture FIFO status register, CAPFIFO (eight MSBs areread-only, eight LSBs are write-only)●Selection of GP timer 2 as the time base●Three 16-bit 2-level-deep FIFO stacks, one for each capture unit●Three Schmitt-triggered capture input pins (CAP1, CAP2, and CAP3)—oneinput pin per capture unit. [All inputs are synchronized with the device (CPU)clock. In order for a transition to be captured, the input must hold at itscurrent level to meet two rising edges of the device clock. The input pinsCAP1 and CAP2 can also be used as QEP inputs to the QEP circuit.]●User-specified transition (rising edge, falling edge, or both edges) detection●Three maskable interrupt flags, one for each capture unitEnhanced analog-to-digital converter (ADC) moduleA simplified functional block diagram of the ADC module is shown in Figure 1. The ADC module consists of a 10-bit ADC with a built-in sample-and-hold (S/H) circuit. Functions of the ADC module include:●10-bit ADC core with built-in S/H●Fast conversion time (S/H + Conversion) of 500 ns●16-channel, muxed inputs●Autosequencing capability provides up to 16 ―autoconversions‖ in a sing lesession. Each conversion can be programmed to select any 1 of 16 inputchannels●Sequencer can be operated as two independent 8-state sequencers or as onelarge 16-state sequencer (i.e., two cascaded 8-state sequencers)●Sixteen result registers (individually addressable) to store conversion values●Multiple triggers as sources for the start-of-conversion (SOC) sequence✧S/W – software immediate start✧EV A – Event manager A (multiple event sources within EV A)✧EVB – Event manager B (multiple event sources within EVB)✧Ext – External pin (ADCSOC)●Flexible interrupt control allows interrupt request on every end of sequence(EOS) or every other EOS●Sequencer can operate in ―start/stop‖ mode, allowing multiple―time-sequenced triggers‖ to synchronize conversions●EV A and EVB triggers can operate independently in dual-sequencer mode●Sample-and-hold (S/H) acquisition time window has separate prescalecontrol●Built-in calibration mode●Built-in self-test modeThe ADC module in the ‘240x has been enhanced to provide flexib le interface to event managers A and B. The ADC interface is built around a fast, 10-bit ADC module with total conversion time of 500 ns (S/H + conversion). The ADC module has 16 channels, configurable as two independent 8-channel modules to service event managers A and B. The two independent 8-channel modules can be cascaded to form a 16-channel module. Figure 2 shows the block diagram of the ‘240x ADC module.The two 8-channel modules have the capability to autosequence a series of conversions, each module has the choice of selecting any one of the respective eight channels available through an analog mux. In the cascaded mode, the autosequencer functions as a single 16-channel sequencer. On each sequencer, once the conversion is complete, the selected channel value is stored in its respective RESULT register. Autosequencing allows the system to convert the same channel multiple times, allowing the user to perform oversampling algorithms. This gives increased resolution over traditional single-sampled conversion results.Figure 2. Block Diagram of the ‘240x ADC ModuleTMS320LF2407, TMS320LF2406, TMS320LF2402TMS320LC2406, TMS320LC2404, MS320LC2402数字信号处理控制器TMS320LF240x和TMS320LC240x系列芯片作为’24x系列DSP控制器的新成员，是C2000平台下的一种定点DSP芯片。
数字信号处理英语词汇
AAbsolutely integrable绝对可积Absolutely integrable impulse response绝对可积冲激响应Absolutely summable绝对可和Absolutely summable impulse response绝对可和冲激响应Accumulator累加器Acoustic 声学Adder加法器Additivity property可加性Aliasing混叠现象All-pass systems全通系统AM (Amplitude modulation )幅度调制Amplifier放大器Amplitude modulation (AM)幅度调制Amplitude-scaling factor幅度放大因子Analog-to-digital (A-to-D) converter模数转换器Analysis equation分析公式（方程）Angel (phase) of complex number复数的角度（相位）Angle criterion角判据Angle modulation角度调制Anticausality反因果Aperiodic非周期Aperiodic convolution非周期卷积Aperiodic signal非周期信号Asynchronous异步的Audio systems音频（声音）系统Autocorrelation functions自相关函数Automobile suspension system汽车减震系统Averaging system平滑系统BBand-limited带（宽）限的Band-limited input signals带限输入信号Band-limited interpolation带限内插Bandpass filters带通滤波器Bandpass signal带通信号Bandpass-sampling techniques带通采样技术Bandwidth带宽Bartlett (triangular) window巴特利特（三角形）窗Bilateral Laplace transform双边拉普拉斯变换Bilinear双线性的Bilinear transformation双线性变换Bit（二进制）位，比特Block diagrams方框图Bode plots波特图Bounded有界限的Break frequency折转频率Butterworth filters巴特沃斯滤波器C“Chirp” transform algorithm“鸟声”变换算法Capacitor电容器Carrier载波Carrier frequency载波频率Carrier signal载波信号Cartesian (rectangular) form 直角坐标形式Cascade (series) interconnection串联，级联Cascade-form串联形式Causal LTI system因果的线性时不变系统Channel信道，频道Channel equalization信道均衡Chopper amplifier斩波器放大器Closed-loop闭环Closed-loop poles闭环极点Closed-loop system闭环系统Closed-loop system function闭环系统函数Coefficient multiplier系数乘法器Coefficients系数Communications systems通信系统Commutative property交换性（交换律）Compensation for nonideal elements非理想元件的补偿Complex conjugate复数共轭Complex exponential carrier复指数载波Complex exponential signals复指数信号Complex exponential(s)复指数Complex numbers 复数Conditionally stable systems条件稳定系统Conjugate symmetry共轭对称Conjugation property共轭性质Continuous-time delay连续时间延迟Continuous-time filter连续时间滤波器Continuous-time Fourier series连续时间傅立叶级数Continuous-time Fourier transform连续时间傅立叶变换Continuous-time signals连续时间信号Continuous-time systems连续时间系统Continuous-to-discrete-time conversion连续时间到离散时间转换Convergence 收敛Convolution卷积Convolution integral卷积积分Convolution property卷积性质Convolution sum卷积和Correlation function相关函数Critically damped systems临界阻尼系统Crosss-correlation functions互相关函数Cutoff frequencies截至频率DDamped sinusoids阻尼正弦振荡Damping ratio阻尼系数Dc offset直流偏移Dc sequence直流序列Deadbeat feedback systems临界阻尼反馈系统Decibels (dB) 分贝Decimation抽取Decimation and interpolation抽取和内插Degenerative (negative) feedback负反馈Delay延迟Delay time延迟时间Demodulation解调Difference equations差分方程Differencing property差分性质Differential equations微分方程Differentiating filters微分滤波器Differentiation property微分性质Differentiator微分器Digital-to-analog (D-to-A) converter数模转换器Direct Form I realization直接I型实现Direct form II realization直接II型实现Direct-form直接型Dirichlet conditions狄里赫利条件Dirichlet, P.L.狄里赫利Discontinuities间断点，不连续Discrete-time filters 离散时间滤波器Discrete-time Fourier series离散时间傅立叶级数Discrete-time Fourier series pair离散时间傅立叶级数对Discrete-time Fourier transform （DFT）离散时间傅立叶变换Discrete-time LTI filters离散时间线性时不变滤波器Discrete-time modulation离散时间调制Discrete-time nonrecursive filters离散时间非递归滤波器Discrete-time signals离散时间信号Discrete-time systems离散时间系统Discrete-time to continuous-time conversion离散时间到连续时间转换Dispersion弥撒（现象）Distortion扭曲，失真Distribution theory（property）分配律Dominant time constant主时间常数Double-sideband modulation (DSB)双边带调制Downsampling减采样Duality对偶性EEcho回波Eigenfunctions特征函数Eigenvalue特征值Elliptic filters椭圆滤波器Encirclement property围线性质End points终点Energy of signals信号的能量Energy-density spectrum能量密度谱Envelope detector包络检波器Envelope function包络函数Equalization均衡化Equalizer circuits均衡器电路Equation for closed-loop poles闭环极点方程Euler, L.欧拉Euler’s relation欧拉关系（公式）Even signals偶信号Exponential signals指数信号Exponentials指数FFast Fourier transform (FFT)快速傅立叶变换Feedback反馈Feedback interconnection反馈联结Feedback path反馈路径Filter(s)滤波器Final-value theorem终值定理Finite impulse response (FIR)有限长脉冲响应Finite impulse response (FIR) filters有限长脉冲响应滤波器Finite sum formula有限项和公式Finite-duration signals有限长信号First difference一阶差分First harmonic components基波分量（一次谐波分量）First-order continuous-time systems一阶连续时间系统First-order discrete-time systems一阶离散时间系统First-order recursive discrete-time filters一阶递归离散时间滤波器First-order systems一阶系统Forced response受迫响应Forward path正向通路Fourier series傅立叶级数Fourier transform傅立叶变换Fourier transform pairs傅立叶变换对Fourier, Jean Baptiste Joseph傅立叶（法国数学家，物理学家）Frequency response频率响应Frequency response of LTI systems线性时不变系统的频率响应Frequency scaling of continuous-time Fourier transform 连续时间傅立叶变化的频率尺度（变换性质）Frequency shift keying (FSK)频移键控Frequency shifting property频移性质Frequency-division multiplexing (FDM)频分多路复用Frequency-domain characterization频域特征Frequency-selective filter频率选择滤波器Frequency-shaping filters频率成型滤波器Fundamental components基波分量Fundamental frequency基波频率Fundamental period基波周期GGain增益Gain and phase margin增益和相位裕度General complex exponentials一般复指数信号Generalized functions广义函数Gibbs phenomenon吉伯斯现象Group delay群延迟HHalf-sample delay半采样间隔时延Hanning window汉宁窗Harmonic analyzer谐波分析议Harmonic components谐波分量Harmonically related谐波关系Heat propagation and diffusion热传播和扩散现象Higher order holds高阶保持Highpass filter高通滤波器Highpass-to-lowpass transformations高通到低通变换Hilbert transform希尔波特滤波器Homogeneity (scaling) property齐次性（比例性）IIdeal理想的Ideal bandstop characteristic理想带阻特征Ideal frequency-selective filter理想频率选择滤波器Idealization理想化Identity system恒等系统Imaginary part虚部Impulse response 冲激响应Impulse train冲激串Incrementally linear systems增量线性系统Independent variable独立变量Infinite impulse response (IIR)无限长脉冲响应Infinite impulse response (IIR) filters无限长脉冲响应滤波器Infinite sum formula无限项和公式Infinite taylor series无限项泰勒级数Initial-value theorem初值定理Inpulse-train sampling冲激串采样Instantaneous瞬时的Instantaneous frequency瞬时频率Integration in time-domain时域积分Integration property积分性质Integrator积分器Interconnection互联Intermediate-frequency (IF) stage中频级Intersymbol interference (ISI)码间干扰Inverse Fourier transform傅立叶反变换Inverse Laplace transform拉普拉斯反变换Inverse LTI system逆线性时不变系统Inverse system design逆系统设计Inverse z-transform z反变换Inverted pendulum倒立摆Invertibility of LTI systems线性时不变系统的可逆性Invertible systems逆系统LLag network滞后网络Lagrange, J.L.拉格朗日（法国数学家，力学家）Laplace transform拉普拉斯变换Laplace, P.S. de拉普拉斯（法国天文学家，数学家）lead network超前网络left-half plane左半平面left-sided signal左边信号Linear线性Linear constant-coefficient difference线性常系数差分方程equationsLinear constant-coefficient differential线性常系数微分方程equationsLinear feedback systems线性反馈系统Linear interpolation线性插值Linearity线性性Log magnitude-phase diagram对数幅－相图Log-magnitude plots对数模图Lossless coding无损失码Lowpass filters低通滤波器Lowpass-to-highpass transformation低通到高通的转换LTI system response线性时不变系统响应LTI systems analysis线性时不变系统分析MMagnitude and phase幅度和相位Matched filter匹配滤波器Measuring devices测量仪器Memory记忆Memoryless systems无记忆系统Modulating signal调制信号Modulation调制Modulation index调制指数Modulation property调制性质Moving-average filters移动平均滤波器Multiplexing多路技术Multiplication property相乘性质Multiplicities多样性NNarrowband窄带Narrowband frequency modulation窄带频率调制Natural frequency自然响应频率Natural response自然响应Negative (degenerative) feedback负反馈Nonanticipatibe system不超前系统Noncausal averaging system非因果平滑系统Nonideal非理想的Nonideal filters非理想滤波器Nonmalized functions归一化函数Nonrecursive非递归Nonrecursive filters非递归滤波器Nonrecursive linear constant-coefficient非递归线性常系数差分方程difference equationsNyquist frequency奈奎斯特频率Nyquist rate奈奎斯特率Nyquist stability criterion奈奎斯特稳定性判据OOdd harmonic 奇次谐波Odd signal奇信号Open-loop开环Open-loop frequency response开环频率响应Open-loop system开环系统Operational amplifier运算放大器Orthogonal functions正交函数Orthogonal signals正交信号Oscilloscope示波器Overdamped system过阻尼系统Oversampling过采样Overshoot超量PParallel interconnection并联Parallel-form block diagrams并联型框图Parity check奇偶校验检查Parseval’s relation帕斯伐尔关系（定理）Partial-fraction expansion部分分式展开Particular and homogeneous solution特解和齐次解Passband通频带Passband edge通带边缘Passband frequency通带频率Passband ripple通带起伏（或波纹）Pendulum钟摆Percent modulation调制百分数Periodic周期的Periodic complex exponentials周期复指数Periodic convolution周期卷积Periodic signals周期信号Periodic square wave周期方波Periodic square-wave modulating signal周期方波调制信号Periodic train of impulses周期冲激串Phase (angle) of complex number复数相位（角度）Phase lag相位滞后Phase lead相位超前Phase margin相位裕度Phase shift相移Phase-reversal相位倒置Phase modulation相位调制Plant工厂Polar form极坐标形式Poles极点Pole-zero plot(s)零极点图Polynomials 多项式Positive (regenerative) feedback正（再生）反馈Power of signals信号功率Power-series expansion method幂级数展开的方法Principal-phase function主值相位函数Proportional (P) control比例控制Proportional feedback system比例反馈系统Proportional-plus-derivative比例加积分Proportional-plus-derivative feedback比例加积分反馈Proportional-plus-integral-plus-different比例－积分－微分控制ial (PID) controlPulse-amplitude modulation脉冲幅度调制Pulse-code modulation脉冲编码调制Pulse-train carrier冲激串载波QQuadrature distortion正交失真Quadrature multiplexing正交多路复用Quality of circuit电路品质（因数）RRaised consine frequency response升余弦频率响应Rational frequency responses有理型频率响应Rational transform有理变换RC highpass filter RC 高阶滤波器RC lowpass filter RC 低阶滤波器Real实数Real exponential signals实指数信号Real part实部Rectangular (Cartesian) form 直角（卡笛儿）坐标形式Rectangular pulse矩形脉冲Rectangular pulse signal矩形脉冲信号Rectangular window矩形窗口Recursive (infinite impulse response)递归（无时限脉冲响应）滤波器filtersRecursive linear constant-coefficient 递归的线性常系数差分方程difference equationsRegenerative (positive) feedback再生（正）反馈Region of comvergence收敛域right-sided signal右边信号Rise time上升时间Root-locus analysis根轨迹分析（方法）Running sum动求和SS domain S域Sampled-data feedback systems采样数据反馈系统Sampled-data systems采样数据系统Sampling采样Sampling frequency采样频率Sampling function采样函数Sampling oscilloscope采样示波器Sampling period采样周期Sampling theorem采样定理Scaling (homogeneity) property比例性（齐次性）性质Scaling in z domain z域尺度变换Scrambler扰频器Second harmonic components二次谐波分量Second-order二阶Second-order continuous-time system二阶连续时间系统Second-order discrete-time system二阶离散时间系统Second-order systems二阶系统sequence序列Series (cascade) interconnection级联（串联）Sifting property筛选性质Sinc functions sinc函数Single-sideband单边带Single-sideband sinusoidal amplitude单边带正弦幅度调制modulationSingularity functions奇异函数Sinusoidal正弦（信号）Sinusoidal amplitude modulation正弦幅度调制Sinusoidal carrier正弦载波Sinusoidal frequency modulation正弦频率调制Sliding滑动Spectral coefficient频谱系数Spectrum频谱Speech scrambler语音加密器S-plane S平面Square wave方波Stability稳定性Stabilization of unstable systems不稳定系统的稳定性（度）Step response阶跃响应Step-invariant transformation阶跃响应不定的变换Stopband阻带Stopband edge阻带边缘Stopband frequency阻带频率Stopband ripple 阻带起伏（或波纹）Stroboscopic effect频闪响应Summer加法器Superposition integral叠加积分Superposition property叠加性质Superposition sum叠加和Suspension system减震系统Symmetric periodic 周期对称Symmetry对称性Synchronous同步的Synthesis equation综合方程System function(s)系统方程TTable of properties 性质列表Taylor series泰勒级数Time时间，时域Time advance property of unilateral单边z变换的时间超前性质z-transformTime constants时间常数Time delay property of unilateral单边z变换的时间延迟性质z-transformTime expansion property时间扩展性质Time invariance时间变量Time reversal property时间反转（反褶）性Time scaling property时间尺度变换性Time shifting property时移性质Time window时间窗口Time-division multiplexing (TDM)时分复用Time-domain时域Time-domain properties时域性质Tracking system (s)跟踪系统Transfer function转移函数transform pairs变换对Transformation变换（变形）Transition band过渡带Transmodulation (transmultiplexing) 交叉调制Triangular (Barlett) window三角型（巴特利特）窗口Trigonometric series三角级数Two-sided signal双边信号Type l feedback system l 型反馈系统UUint impulse response单位冲激响应Uint ramp function单位斜坡函数Undamped natural frequency无阻尼自然相应Undamped system无阻尼系统Underdamped systems欠阻尼系统Undersampling欠采样Unilateral单边的Unilateral Laplace transform单边拉普拉斯变换Unilateral z-transform单边z变换Unit circle单位圆Unit delay单位延迟Unit doublets单位冲激偶Unit impulse单位冲激Unit step functions单位阶跃函数Unit step response 单位阶跃响应Unstable systems不稳定系统Unwrapped phase展开的相位特性Upsampling增采样VVariable变量WWalsh functions沃尔什函数Wave波形Wavelengths波长Weighted average加权平均Wideband宽带Wideband frequency modulation宽带频率调制Windowing加窗zZ domain z域Zero force equalizer置零均衡器Zero-Input response零输入响应Zero-Order hold零阶保持Zeros of Laplace transform拉普拉斯变换的零点Zero-state response零状态响应z-transform z变换z-transform pairs z变换对。
数字信号处理词汇英文翻译
DFT (discrete Fourier transform)离散傅立叶变换
196
N-point DFT of a length L signal对L长信号做N点DFT
197
zero padding补零
198
biasing error偏移误差
199
rounding error舍入误差
200
matrix form矩阵形式
integrator积分器
88
DCgain直流增益
89
overlap-add-block convolution method重叠相加器
90
temporary临时的
91
adder加法器
92
multiplier相乘器
93
delay延迟器
94
tapped delay line抽头延迟器
95
differentiator微分器
78
difference equation差分卷积
79
recursive递归
80
even偶数
81
odd奇数
82
filter coefficient滤波器系数
83
diverge发散
84
antidiagonal反对角线
85
flip-and-slide翻转平移
86
input-off-state输出暂态
87
218
window method窗口法
219
linear phase线性相位
220
guaranteesability保证稳定性
221
lowpass低通
222
highpass高通
数字信号处理英语词汇
AAbsolutely integrable 绝对可积Absolutely integrable impulse response 绝对可积冲激响应Absolutely summable 绝对可和Absolutely summable impulse response 绝对可和冲激响应Accumulator 累加器Acoustic 声学Adder 加法器Additivity property 可加性Aliasing 混叠现象All-pass systems 全通系统AM (Amplitude modulation ) 幅度调制Amplifier 放大器Amplitude modulation (AM) 幅度调制Amplitude-scaling factor 幅度放大因子Analog-to-digital (A-to-D) converter 模数转换器Analysis equation 分析公式（方程）Angel (phase) of complex number 复数的角度（相位）Angle criterion 角判据Angle modulation 角度调制Anticausality 反因果Aperiodic 非周期Aperiodic convolution 非周期卷积Aperiodic signal 非周期信号Asynchronous 异步的Audio systems 音频（声音）系统Autocorrelation functions 自相关函数Automobile suspension system 汽车减震系统Averaging system 平滑系统BBand-limited 带（宽）限的Band-limited input signals 带限输入信号Band-limited interpolation 带限内插Bandpass filters 带通滤波器Bandpass signal 带通信号Bandpass-sampling techniques 带通采样技术Bandwidth 带宽Bartlett (triangular) window 巴特利特（三角形）窗Bilateral Laplace transform 双边拉普拉斯变换Bilinear 双线性的Bilinear transformation 双线性变换Bit （二进制）位，比特Block diagrams 方框图Bode plots 波特图Bounded 有界限的Break frequency 折转频率Butterworth filters 巴特沃斯滤波器C“Chirp” transform algorithm“鸟声”变换算法Capacitor 电容器Carrier 载波Carrier frequency 载波频率Carrier signal 载波信号Cartesian (rectangular) form 直角坐标形式Cascade (series) interconnection 串联，级联Cascade-form 串联形式Causal LTI system 因果的线性时不变系统Channel 信道，频道Channel equalization 信道均衡Chopper amplifier 斩波器放大器Closed-loop 闭环Closed-loop poles 闭环极点Closed-loop system 闭环系统Closed-loop system function 闭环系统函数Coefficient multiplier 系数乘法器Coefficients 系数Communications systems 通信系统Commutative property 交换性（交换律）Compensation for nonideal elements 非理想元件的补偿Complex conjugate 复数共轭Complex exponential carrier 复指数载波Complex exponential signals 复指数信号Complex exponential(s) 复指数Complex numbers 复数Conditionally stable systems 条件稳定系统Conjugate symmetry 共轭对称Conjugation property 共轭性质Continuous-time delay 连续时间延迟Continuous-time filter 连续时间滤波器Continuous-time Fourier series 连续时间傅立叶级数Continuous-time Fourier transform 连续时间傅立叶变换Continuous-time signals 连续时间信号Continuous-time systems 连续时间系统Continuous-to-discrete-time conversion 连续时间到离散时间转换Convergence 收敛Convolution 卷积Convolution integral 卷积积分Convolution property 卷积性质Convolution sum 卷积和Correlation function 相关函数Critically damped systems 临界阻尼系统Crosss-correlation functions 互相关函数Cutoff frequencies 截至频率DDamped sinusoids 阻尼正弦振荡Damping ratio 阻尼系数Dc offset 直流偏移Dc sequence 直流序列Deadbeat feedback systems 临界阻尼反馈系统Decibels (dB) 分贝Decimation 抽取Decimation and interpolation 抽取和内插Degenerative (negative) feedback 负反馈Delay 延迟Delay time 延迟时间Demodulation 解调Difference equations 差分方程Differencing property 差分性质Differential equations 微分方程Differentiating filters 微分滤波器Differentiation property 微分性质Differentiator 微分器Digital-to-analog (D-to-A) converter 数模转换器Direct Form I realization 直接I型实现Direct form II realization 直接II型实现Direct-form 直接型Dirichlet conditions 狄里赫利条件Dirichlet, P.L. 狄里赫利Discontinuities 间断点，不连续Discrete-time filters 离散时间滤波器Discrete-time Fourier series 离散时间傅立叶级数Discrete-time Fourier series pair 离散时间傅立叶级数对Discrete-time Fourier transform （DFT）离散时间傅立叶变换Discrete-time LTI filters 离散时间线性时不变滤波器Discrete-time modulation 离散时间调制Discrete-time nonrecursive filters 离散时间非递归滤波器Discrete-time signals 离散时间信号Discrete-time systems 离散时间系统Discrete-time to continuous-time离散时间到连续时间转换conversionDispersion 弥撒（现象）Distortion 扭曲，失真Distribution theory（property）分配律Dominant time constant 主时间常数Double-sideband modulation (DSB) 双边带调制Downsampling 减采样Duality 对偶性EEcho 回波Eigenfunctions 特征函数Eigenvalue 特征值Elliptic filters 椭圆滤波器Encirclement property 围线性质End points 终点Energy of signals 信号的能量Energy-density spectrum 能量密度谱Envelope detector 包络检波器Envelope function 包络函数Equalization 均衡化Equalizer circuits 均衡器电路Equation for closed-loop poles 闭环极点方程Euler, L. 欧拉Euler’s relation欧拉关系（公式）Even signals 偶信号Exponential signals 指数信号Exponentials 指数FFast Fourier transform (FFT) 快速傅立叶变换Feedback 反馈Feedback interconnection 反馈联结Feedback path 反馈路径Filter(s) 滤波器Final-value theorem 终值定理Finite impulse response (FIR) 有限长脉冲响应Finite impulse response (FIR) filters 有限长脉冲响应滤波器 Finite sum formula 有限项和公式 Finite-duration signals 有限长信号 First difference 一阶差分 First harmonic components 基波分量 （一次谐波分量） First-order continuous-time systems 一阶连续时间系统 First-order discrete-time systems 一阶离散时间系统 First-order recursive discrete-timefilters一阶递归离散时间滤波器First-order systems 一阶系统 Forced response 受迫响应 Forward path 正向通路 Fourier series 傅立叶级数 Fourier transform 傅立叶变换 Fourier transform pairs 傅立叶变换对 Fourier, Jean Baptiste Joseph 傅立叶（法国数学家，物理学家） Frequency response 频率响应 Frequency response of LTI systems 线性时不变系统的频率响应 Frequency scaling of continuous-time Fourier transform 连续时间傅立叶变化的频率尺度（变换性质） Frequency shift keying (FSK) 频移键控 Frequency shifting property 频移性质 Frequency-division multiplexing (FDM) 频分多路复用 Frequency-domain characterization 频域特征 Frequency-selective filter 频率选择滤波器 Frequency-shaping filters 频率成型滤波器 Fundamental components 基波分量 Fundamental frequency 基波频率 Fundamental period 基波周期GGain 增益 Gain and phase margin 增益和相位裕度 General complex exponentials 一般复指数信号 Generalized functions 广义函数 Gibbs phenomenon 吉伯斯现象 Group delay 群延迟HHalf-sample delay 半采样间隔时延 Hanning window 汉宁窗 Harmonic analyzer 谐波分析议 Harmonic components 谐波分量Harmonically related 谐波关系Heat propagation and diffusion 热传播和扩散现象Higher order holds 高阶保持Highpass filter 高通滤波器Highpass-to-lowpass transformations 高通到低通变换Hilbert transform 希尔波特滤波器Homogeneity (scaling) property 齐次性（比例性）IIdeal 理想的Ideal bandstop characteristic 理想带阻特征Ideal frequency-selective filter 理想频率选择滤波器Idealization 理想化Identity system 恒等系统Imaginary part 虚部Impulse response 冲激响应Impulse train 冲激串Incrementally linear systems 增量线性系统Independent variable 独立变量Infinite impulse response (IIR) 无限长脉冲响应Infinite impulse response (IIR) filters 无限长脉冲响应滤波器Infinite sum formula 无限项和公式Infinite taylor series 无限项泰勒级数Initial-value theorem 初值定理Inpulse-train sampling 冲激串采样Instantaneous 瞬时的Instantaneous frequency 瞬时频率Integration in time-domain 时域积分Integration property 积分性质Integrator 积分器Interconnection 互联Intermediate-frequency (IF) stage 中频级Intersymbol interference (ISI) 码间干扰Inverse Fourier transform 傅立叶反变换Inverse Laplace transform 拉普拉斯反变换Inverse LTI system 逆线性时不变系统Inverse system design 逆系统设计Inverse z-transform z反变换Inverted pendulum 倒立摆Invertibility of LTI systems 线性时不变系统的可逆性Invertible systems 逆系统LLag network 滞后网络Lagrange, J.L. 拉格朗日（法国数学家，力学家）Laplace transform 拉普拉斯变换Laplace, P.S. de 拉普拉斯（法国天文学家，数学家）lead network 超前网络left-half plane 左半平面left-sided signal 左边信号Linear 线性Linear constant-coefficient difference线性常系数差分方程equationsLinear constant-coefficient differential线性常系数微分方程equationsLinear feedback systems 线性反馈系统Linear interpolation 线性插值Linearity 线性性Log magnitude-phase diagram 对数幅－相图Log-magnitude plots 对数模图Lossless coding 无损失码Lowpass filters 低通滤波器Lowpass-to-highpass transformation 低通到高通的转换LTI system response 线性时不变系统响应LTI systems analysis 线性时不变系统分析MMagnitude and phase 幅度和相位Matched filter 匹配滤波器Measuring devices 测量仪器Memory 记忆Memoryless systems 无记忆系统Modulating signal 调制信号Modulation 调制Modulation index 调制指数Modulation property 调制性质Moving-average filters 移动平均滤波器Multiplexing 多路技术Multiplication property 相乘性质Multiplicities 多样性NNarrowband 窄带Narrowband frequency modulation 窄带频率调制Natural frequency 自然响应频率Natural response 自然响应Negative (degenerative) feedback 负反馈Nonanticipatibe system 不超前系统Noncausal averaging system 非因果平滑系统Nonideal 非理想的Nonideal filters 非理想滤波器Nonmalized functions 归一化函数Nonrecursive 非递归Nonrecursive filters 非递归滤波器Nonrecursive linear constant-coefficient非递归线性常系数差分方程difference equationsNyquist frequency 奈奎斯特频率Nyquist rate 奈奎斯特率Nyquist stability criterion 奈奎斯特稳定性判据OOdd harmonic 奇次谐波Odd signal 奇信号Open-loop 开环Open-loop frequency response 开环频率响应Open-loop system 开环系统Operational amplifier 运算放大器Orthogonal functions 正交函数Orthogonal signals 正交信号Oscilloscope 示波器Overdamped system 过阻尼系统Oversampling 过采样Overshoot 超量PParallel interconnection 并联Parallel-form block diagrams 并联型框图Parity check 奇偶校验检查Parseval’s relatio n 帕斯伐尔关系（定理）Partial-fraction expansion 部分分式展开Particular and homogeneous solution 特解和齐次解Passband 通频带Passband edge 通带边缘Passband frequency 通带频率Passband ripple 通带起伏（或波纹）Pendulum 钟摆Percent modulation 调制百分数Periodic 周期的Periodic complex exponentials 周期复指数Periodic convolution 周期卷积Periodic signals 周期信号Periodic square wave 周期方波Periodic square-wave modulating signal 周期方波调制信号Periodic train of impulses 周期冲激串Phase (angle) of complex number 复数相位（角度）Phase lag 相位滞后Phase lead 相位超前Phase margin 相位裕度Phase shift 相移Phase-reversal 相位倒置Phase modulation 相位调制Plant 工厂Polar form 极坐标形式Poles 极点Pole-zero plot(s) 零极点图Polynomials 多项式Positive (regenerative) feedback 正（再生）反馈Power of signals 信号功率Power-series expansion method 幂级数展开的方法Principal-phase function 主值相位函数Proportional (P) control 比例控制Proportional feedback system 比例反馈系统Proportional-plus-derivative 比例加积分Proportional-plus-derivative feedback 比例加积分反馈Proportional-plus-integral-plus-比例－积分－微分控制differential (PID) controlPulse-amplitude modulation 脉冲幅度调制Pulse-code modulation 脉冲编码调制Pulse-train carrier 冲激串载波QQuadrature distortion 正交失真Quadrature multiplexing 正交多路复用Quality of circuit 电路品质（因数）RRaised consine frequency response 升余弦频率响应Rational frequency responses 有理型频率响应Rational transform 有理变换RC highpass filter RC 高阶滤波器RC lowpass filter RC 低阶滤波器Real 实数Real exponential signals 实指数信号Real part 实部Rectangular (Cartesian) form 直角（卡笛儿）坐标形式Rectangular pulse 矩形脉冲Rectangular pulse signal 矩形脉冲信号Rectangular window 矩形窗口Recursive (infinite impulse response)递归（无时限脉冲响应）滤波器filtersRecursive linear constant-coefficient递归的线性常系数差分方程difference equationsRegenerative (positive) feedback 再生（正）反馈Region of comvergence 收敛域right-sided signal 右边信号Rise time 上升时间Root-locus analysis 根轨迹分析（方法）Running sum 动求和SS domain S域Sampled-data feedback systems 采样数据反馈系统Sampled-data systems 采样数据系统Sampling 采样Sampling frequency 采样频率Sampling function 采样函数Sampling oscilloscope 采样示波器Sampling period 采样周期Sampling theorem 采样定理Scaling (homogeneity) property 比例性（齐次性）性质Scaling in z domain z域尺度变换Scrambler 扰频器Second harmonic components 二次谐波分量Second-order 二阶Second-order continuous-time system 二阶连续时间系统Second-order discrete-time system 二阶离散时间系统Second-order systems 二阶系统sequence 序列Series (cascade) interconnection 级联（串联）Sifting property 筛选性质Sinc functions sinc函数Single-sideband 单边带Single-sideband sinusoidal amplitude单边带正弦幅度调制modulationSingularity functions 奇异函数Sinusoidal 正弦（信号）Sinusoidal amplitude modulation 正弦幅度调制Sinusoidal carrier 正弦载波Sinusoidal frequency modulation 正弦频率调制Sliding 滑动Spectral coefficient 频谱系数Spectrum 频谱Speech scrambler 语音加密器S-plane S平面Square wave 方波Stability 稳定性Stabilization of unstable systems 不稳定系统的稳定性（度）Step response 阶跃响应Step-invariant transformation 阶跃响应不定的变换Stopband 阻带Stopband edge 阻带边缘Stopband frequency 阻带频率Stopband ripple 阻带起伏（或波纹）Stroboscopic effect 频闪响应Summer 加法器Superposition integral 叠加积分Superposition property 叠加性质Superposition sum 叠加和Suspension system 减震系统Symmetric periodic 周期对称Symmetry 对称性Synchronous 同步的Synthesis equation 综合方程System function(s) 系统方程TTable of properties 性质列表Taylor series 泰勒级数Time 时间，时域Time advance property of unilateral z-单边z变换的时间超前性质transformTime constants 时间常数Time delay property of unilateral z-单边z变换的时间延迟性质transformTime expansion property 时间扩展性质Time invariance 时间变量Time reversal property 时间反转（反褶）性Time scaling property 时间尺度变换性Time shifting property 时移性质Time window 时间窗口Time-division multiplexing (TDM) 时分复用Time-domain 时域Time-domain properties 时域性质Tracking system (s) 跟踪系统Transfer function 转移函数transform pairs 变换对Transformation 变换（变形）Transition band 过渡带Transmodulation (transmultiplexing) 交叉调制Triangular (Barlett) window 三角型（巴特利特）窗口Trigonometric series 三角级数Two-sided signal 双边信号Type l feedback system l 型反馈系统UUint impulse response 单位冲激响应Uint ramp function 单位斜坡函数Undamped natural frequency 无阻尼自然相应Undamped system 无阻尼系统Underdamped systems 欠阻尼系统Undersampling 欠采样Unilateral 单边的Unilateral Laplace transform 单边拉普拉斯变换Unilateral z-transform 单边z变换Unit circle 单位圆Unit delay 单位延迟Unit doublets 单位冲激偶Unit impulse 单位冲激Unit step functions 单位阶跃函数Unit step response 单位阶跃响应Unstable systems 不稳定系统Unwrapped phase 展开的相位特性Upsampling 增采样VVariable 变量WWalsh functions 沃尔什函数Wave 波形Wavelengths 波长Weighted average 加权平均Wideband 宽带Wideband frequency modulation 宽带频率调制Windowing 加窗zZ domain z域Zero force equalizer 置零均衡器Zero-Input response 零输入响应Zero-Order hold 零阶保持Zeros of Laplace transform 拉普拉斯变换的零点Zero-state response 零状态响应z-transform z变换z-transform pairs z变换对。
《数字信号处理(英文)》Maria Elena Angoletta
Bandwidth: indicates rate of change of a signal. High bandwidth signal changes fast.
Warning: formal description makes use
of “negative” frequencies !
0.3
Digital
Discrete function Vk of discrete sampling variable tk, with k = integer: Vk = V(tk).
0.3
0.1 0 -0.1 -0.2 0 2 4 6 time [ms] 8 10
Voltage [V]
Voltage [V]
• General purpose processors (GPP), -controllers.
Hardware
• Digital Signal Processors (DSP). • Programmable logic ( PLD, FPGA ).
Fang
• Reproducibility.
M. E. Angoletta - DISP2003 -
From analog to digital domain
4 / 30
DSPing: aim & tools
Applications
• Predicting a system‟s output. • Implementing a certain processing task. • Studying a certain signal.
M. E. Angoletta - DISP2003 -
From analog to digital domain
科技英语 5数字信号处理器原文与翻译
Words and Expressionsfollow v.遵循memory n.存储器register n.寄存器access v.访问overlap v. 重叠pipelining n. 流水线操作multiplier n. 乘法器accumulator n. 累加器shifter n.移位器reference n. 寻址mantissa n.尾数exponent n. 指数cycle n. 机器周期customize v.定制，用户化package v.封装digital signal processor 数字信号处理器von Neumann architecture 冯·诺伊曼结构shared single memory 单一共享存储器program instruction 程序指令harvard architecture 哈佛结构fetch from 从…获取circular buffer 循环缓冲区，环形缓冲区address generator 地址产生器fixed point 定点floating point 浮点binary point 二进制小数点available precision 可用精度dynamic range 动态范围scale range 量程smallest Resolvable Difference 最小分辨率scientific notation 科学计数法assembly language 汇编语言multi-function instructions 多功能指令parallel architecture 并行结构looping scheme 循环机制sampling frequency 采样频率on-chip memory 片内存储器well-matched 非常匹配software tools 软件开发工具low level programming language 低级编程语言high level programming language 高级编程语言third party software 第三方软件board level product 板级产品data register 数据寄存器ALU=Arithmetic Logical Unit 运算逻辑单元program sequencer 程序定序器peripheral sections 外设single integrated circuit 单片集成电路cellular telephone 蜂窝电话printed circuit board 印刷电路板licensing agreement 专利使用权转让协定custom devices 定制器件extra memory 附加存储器stand alone 单机third party developer 第三方开发商multimedia operations 多媒体操作merged into 融合calculation-intensive algorithm运算密集型算法Unit 5 Digital Signal ProcessorsDigital signal processing tasks can be performed by all processors. Specialized digital signal processors(DSPs), however, perform these tasks most efficiently and most quickly. While traditional processors follow the Von Neumann architecture[]1model, which assumes a shared single memory to be used for both program instructions and data, DSPs use the Harvard or modified Harvard architecture []2, which includes multiple program and data memories, along with multiple buses to access them. This arrangement means that much less waiting is required when instructions or numbers are fetched from memory. In fact at least one of each can be fetched simultaneously. Such overlapping of tasks is called pipelining. In addition to multiple memories and buses, all DSPs have fast multipliers, accumulators, and shifters, and many have hardware support for circular buffers. Address generators can speed up accesses to memory locations referenced by registers.DSPs are available in two major classes: fixed point and floating point. The fixed point class represents real numbers in a fixed number of bits. The position of the binary point (similar to the decimal point) can be controlled by the programmer, and determines the range of numbers that can be represented. As the range increases, though, the available precision goes down, since fewer bits lie to the right of the binary point. In 16 bits, the formats 16.0, 15.1, 14.2, 13.3, 12.4, 11.5, 10.6, 9.7, 8.8, 7.9, 6.10, 5.11, 4.12, 3.13, 2.14, and 1.15 are possible. The dynamic range, calculated as 20log (Full Scale Range/Smallest2= 96.3 dB.Resolvable Difference), remains the same for all 16-bit formats, 20log16Figure 6.3 Van Neumann architectureFigure 6.4 Harvard architectureFloating point DSPs represent real numbers using a mantissa and an exponent , similar to scientific notation : Many combine mantissa and exponent into a 32-bit number. The dynamic range for floating point devices is calculated from the largest and smallest multipliers E 2, where E is the exponent. Thus, for a representation that uses 24 bits for the mantissa and 8 bits for the signed exponent, the dynamic range is 20 log (1281272/2-) = 1535.3 dB. A large dynamic range means the system has great power to represent a wide range of input signals, from very small to very large.Assembly language is the command language for DSPs. DSPs often have specialized instructions that make programming for common DSP tasks more convenient and more efficient. For example, most DSPs offer multi-function instructions that exploit their parallel architecture . Other constructs that are frequently offered are efficient looping schemes , since so many DSP operations involve a great deal of repetition.Choosing a DSP for a particular application is not always easy. The first decision is on whether tochoose a fixed point or a floating point device []3. Generally, fixed point devices are cheaper and quicker,but floating point devices are more convenient to program and more suited to calculation-intensive algorithms . Second, the data width of the DSP determines how accurately it can represent numbers. Speed is another issue, not only how many cycles occur in each second, but also how many instructions execute in each cycle and how much work each of these instructions accomplishes. One way to assess the minimum requirements for the DSP is to estimate how many instructions must be executed for each received sample. When this number is multiplied by the sampling frequency , the minimum required number of instructions per second is obtained.The specific hardware and software features offered by a particular DSP can make one choice betterthan another, as can the amount of on-chip memory available []4. Sometimes DSPs are chosen becausewell-matched supporting hardware, particularly A/D and D/A converters, is obtainable. Frequently, the quality and convenience of the software tools, for both low level and high level programming languages, are also major factors, as is the availability of third party software. As always, cost is a factor. In fact, quite often, the DSP that is fastest and offers the most features, but also fits the budget, is the one selected.DSPs can be purchased in three forms, as a core, as a processor, and as a board level product. In DSP, the term "core" refers to the section of the processor where the key tasks are carried out, including the data registers, multiplier, ALU, address generator, and program sequencer. A complete processor requires combining the core with memory and interfaces to the outside world. While the core and these peripheral sections are designed separately, they will be fabricated on the same piece of silicon, making the processor a single integrated circuit.Suppose you build cellular telephones and want to include a DSP in the design. You will probably want to purchase the DSP as a processor, that is, an integrated circuit that contains the core, memory and other internal features. To incorporate this IC in your product, you have to design a printed circuit board where it will be soldered in next to your other electronics. This is the most common way that DSPs are used.Now, suppose the company you work for manufactures its own integrated circuits. In this case, you might not want the entire processor, just the design of the core. After completing the appropriate licensing agreement, you can start making chips that are highly customized to your particular application. This gives you the flexibility of selecting how much memory is included, how the chip receives and transmits data, how it is packaged, and so on.Custom devices of this type are an increasingly important segment of the DSP marketplace.There are several dozen companies that will sell you DSPs already mounted on a printed circuit board. These have such features as extra memory, A/D and D/A converters, EPROM sockets, multiple processors on the same board, and so on. While some of these boards are intended to be used as stand alone computers, most are configured to be plugged into a host, such as a personal computer. Companies that make these types of boards are called Third Party Developers. The best way to find them is to ask the manufacturer of the DSP you want to use. Look at the DSP manufacturer's website; if you don't find a list there, send them an e-mail. They will be more than happy to tell you who are using their products and how to contact them.Keep in mind that the distinction between DSPs and other microprocessors is not always a clear line. For instance, look at how Intel describes the MMX technology addition to its Pentium processor: "Intel engineers have added 57 powerful new instructions specifically designed to manipulate and process video, audio and graphical data efficiently. These instructions are oriented to the highly parallel, repetitivesequences often found in multimedia operations . "In the future, we will undoubtedly see more DSP-like functions merged into traditional microprocessors and microcontrollers. The Internet and other multimedia applications are a strong driving force for these changes. These applications are expanding so rapidly, in twenty years it is very possible that the Digital Signal Processor may be the "traditional" microprocessor.Notes1. “冯·诺伊曼结构”取名字美国杰出的数学家—约翰·冯·诺伊曼（John Von Neumann,1903~1957）。
数字信号处理词汇英文翻译
complex conjugate pairs复共轭对
151
quantization effects in digital filters数字滤波器中的量化效应
152
roundofferror舍入误差
153
sample-by-sample processing algorithm逐个样本处理算法
96
unit step单位阶跃信号
97
alternating step正负交替的阶跃信号
98
Z-transform Z变换
99
positive正的
100
negative负的
101
region of convergence收敛域
102
marginally stable临界稳定
103
polynomial多项式
208
Decimation-in-time radix-2 FFT algorithm按时间抽取的基二FFT算法
209
butterfly merging equations蝶形组合公式
210
shuffling重排
211
bit reversal码位倒置
212
fast convolution快速卷积
213
104
denominator分母
105
numerator分子
106
peak峰
107
dip谷
108
partial fraction expansion method部分分式展开法
109
unit circle单位圆
110
double sided complex sinusoid双边复正弦
数字信号处理 英文 教材
数字信号处理英文教材
数字信号处理是一门涉及数学、工程学和计算机科学的学科，其英文教材有很多，以下是一些经典的数字信号处理英文教材：
1. "Digital Signal Processing" by John G. Proakis and Masoud Salehi
2. "Digital Signal Processing: Principles, Algorithms, and Applications" by Robert J. Schroeder and Ray P. Kailath
3. "Digital Signal Processing: A Practical Guide for Applications Engineers" by Robert A. Monzingo and John W. Cocke
4. "Digital Signal Processing: A Computer-Based Approach" by John
G. Proakis and Dimitris G. Manolakis
5. "Digital Signal Processing: Theory, Algorithms, and Practicalities" by John G. Proakis and Gilbert H. Walker
这些教材都是非常经典的数字信号处理教材，被广泛应用于数字信号处理领域。
它们涵盖了数字信号处理的基本概念、原理、算法和应用，适合初学者和有一定基础的读者。
数字信号处理(英文版)0-引言
The foundation of information
technology is digitalization. The kernel of digitalization is digital signal processing Most of digital signal processing, especially real-time processing are implemented by DSP processor or ASIC based on DSP core DSP technology becomes hot front edge and is growing up rapidly.
Digital system：By the Nyquist Rule，the
processing speed is limited by the S/H, A/D and processor speed.
We still need analog processing
(3)The most signals in real would are analog. If we want to process these analog signals with digital signal processing system, must change them into digital form first by mixed signal processing.
Digital system：Modify software.
Example：Analog filter, digital
filter, adaptive filter
Why digital?
（2）Precision
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数字信号处理一、导论数字信号处理（DSP）是由一系列的数字或符号来表示这些信号的处理的过程的。
数字信号处理与模拟信号处理属于信号处理领域。
DSP包括子域的音频和语音信号处理，雷达和声纳信号处理，传感器阵列处理，谱估计，统计信号处理，数字图像处理，通信信号处理，生物医学信号处理，地震数据处理等。
由于DSP的目标通常是对连续的真实世界的模拟信号进行测量或滤波，第一步通常是通过使用一个模拟到数字的转换器将信号从模拟信号转化到数字信号。
通常，所需的输出信号却是一个模拟输出信号，因此这就需要一个数字到模拟的转换器。
即使这个过程比模拟处理更复杂的和而且具有离散值，由于数字信号处理的错误检测和校正不易受噪声影响，它的稳定性使得它优于许多模拟信号处理的应用（虽然不是全部）。
DSP算法一直是运行在标准的计算机，被称为数字信号处理器（DSP）的专用处理器或在专用硬件如特殊应用集成电路（ASIC）。
目前有用于数字信号处理的附加技术包括更强大的通用微处理器，现场可编程门阵列（FPGA），数字信号控制器（大多为工业应用，如电机控制）和流处理器和其他相关技术。
在数字信号处理过程中，工程师通常研究数字信号的以下领域：时间域（一维信号），空间域（多维信号），频率域，域和小波域的自相关。
他们选择在哪个领域过程中的一个信号，做一个明智的猜测（或通过尝试不同的可能性）作为该域的最佳代表的信号的本质特征。
从测量装置对样品序列产生一个时间或空间域表示，而离散傅立叶变换产生的频谱的频率域信息。
自相关的定义是互相关的信号本身在不同时间间隔的时间或空间的相关情况。
二、信号采样随着计算机的应用越来越多地使用，数字信号处理的需要也增加了。
为了在计算机上使用一个模拟信号的计算机，它上面必须使用模拟到数字的转换器（ADC）使其数字化。
采样通常分两阶段进行，离散化和量化。
在离散化阶段，信号的空间被划分成等价类和量化是通过一组有限的具有代表性的信号值来代替信号近似值。
奈奎斯特-香农采样定理指出，如果样本的取样频率大于两倍的信号的最高频率，一个信号可以准确地重建它的样本。
在实践中，采样频率往往大大超过所需的带宽的两倍。
数字模拟转换器（DAC）用于将数字信号转化到模拟信号。
数字计算机的使用是数字控制系统中的一个关键因素。
三、时间域和空间域在时间或空间域中最常见的处理方法是对输入信号进行一种称为滤波的操作。
滤波通常包括对一些周边样本的输入或输出信号电流采样进行一些改造。
现在有各种不同的方法来表征的滤波器，例如：一个线性滤波器的输入样本的线性变换；其他的过滤器都是“非线性”。
线性滤波器满足叠加条件，即如果一个输入不同的信号的加权线性组合，输出的是一个同样加权线性组合所对应的输出信号。
“因果”滤波器只使用以前的样本的输入或输出信号；而“非因果”滤波器使用未来的输入样本。
一个非因果滤波器通常可以通过增加一个延迟将它变成了一个因果滤波器。
“时间不变”滤波器随着时间的推移性具有稳定特性；其他滤波器如随时间变化的自适应滤波器。
一些滤波器是“稳定”的，别的是“不稳定的”。
一个稳定的滤波器产生的输出信号随时间收敛于一个恒定值，或在一个有限的时间间隔内是有界的。
一种不稳定的滤波器可以产生一个没有增长界限的输出，甚至零输入有界。
“有限脉冲响应（FIR）”滤波器只使用于输入信号，而“无限脉冲响应滤波器（IIR）”使用于输入信号和输出信号之前的样品。
FIR滤波器总是稳定的，而IIR滤波器可能是不稳定的。
大多数滤波器可以被描述在z域（频域的一个超集）的传递函数。
如果它是一个FIR滤波器的脉冲响应和阶跃响应，滤波器也可以被描述为一个差分方程，或对零点和极点的收集。
一个FIR滤波器的输出是通过对任何给定的输入与脉冲响应的卷积计算得到的。
滤波器也可以被用来推导出一个样品的处理算法的方块图利用硬件指令实现滤波器所代表。
四、频域信号通常是通过傅立叶变换将其从时间或空间域转换到频率域。
傅里叶变换将信号转换信息和相位分量级的每个频率。
通常的傅里叶变换转换为功率谱，这是大小的每个频率分量的平方。
在频域对信号分析的最常见的用途是信号特性分析。
工程师可以研究频谱来确定哪一频率的存在于输入信号中。
滤波，特别是在非实时的工作也可以被转换到频域实现，应用滤波器，然后转换回时域。
这是一个快速，O（nlogn）操作，可以基本上给出任何滤波器的形状包括砖墙滤波器优良的逼近。
有一些常用的频域变换。
例如，倒谱转换信号的频域傅立叶变换，取对数，然后将另一个傅里叶变换。
这强调的频率成分的幅度较小而保留的频率分量的大小顺序。
频域分析又称谱或谱分析。
五、信号处理信号通常需要以不同的方式进行处理。
例如，从一个传感器的输出信号可能被污染的多余电“噪音”。
电极连接到一个病人的胸部时，心电图是测量由心脏和其他肌肉的活动引起的微小的电压变化。
由于电的干扰从电源的强烈影响，信号通常是采用“总管拾取”。
处理信号的滤波电路可以消除或至少降低信号的不需要的部分。
现在，越来越多的的情况下，是由DSP技术来进行信号的滤波以提高信号质量或提取重要信息，而不是模拟电子技术。
六、DSP的发展数字信号处理的发展从1960年代的大型数字计算机的数字运算应用程序的使用快速傅立叶变换（FFT），它允许一个信号的频谱可以快速计算。
这些技术在当时没有被广泛使用，因为合适的计算设备通常仅在大学及其他科研机构可以使用。
七、数字信号处理器（DSP）在20世纪70年代末和20世纪80年代初微处理机的介绍使DSP技术在更广泛的范围内得到了使用。
然而，通用微处理器如Intel x86的家庭并不适合于DSP的计算密集型的需求，随着20世纪80年代DSP重要性的增加导致几个主要的电子产品制造商（如德克萨斯仪器，模拟设备和摩托罗拉）去开发数字信号处理器芯片，专门的微处理器，专门设计用于在数字信号处理要求的操作的类型的架构。
（注意，缩写DSP数字信号处理的不同的意思，这个词用于处理数字信号，多种技术或数字信号处理器，一种特殊类型的微处理器芯片）。
像一个通用微处理器，DSP是一种具有其自己的本地指令代码的可编程器件。
DSP芯片是能够每秒进行数以百万计的浮点运算，像他们同类型的更著名的通用器件，更快和更强大的版本正在不断被引入。
DSP也可以嵌入在复杂的“系统芯片”装置，通常包括模拟和数字电路。
8、数字信号处理器的应用DSP技术是当今普遍在手机，多媒体计算机，录像机，CD播放器，硬盘驱动器和控制器的调制解调器等设备，并将很快在电视和电话业务中取代模拟电路。
DSP的一个重要的应用是信号的压缩和解压。
信号压缩用于数字蜂窝电话，在每一个地方的“单元”让更多的电话同时被处理。
DSP信号压缩技术不仅使人们可以相互交谈，而且可以通过使用安装在计算机上的小的摄像机使人们通过显示器看见对方，而这些只需要将传统的电话线连接在一起。
在音频CD系统，DSP技术来执行复杂的错误检测和校正原始数据，因为它是从光盘读取。
虽然一些潜在的DSP技术的数学理论，如傅立叶和希尔伯特变换，数字滤波器的设计和信号压缩，可以相当复杂，而数值运算所需的实际实现这些技术是非常简单的，主要包括操作可以在一个便宜的四功能的计算器上进行操作。
一种DSP芯片的结构设计进行这样的操作非常快，处理的样品每秒数以亿计，提供实时的性能：即，能够处理一个实时的信号，因为它是采样，然后输出信号的处理，例如扬声器或视频显示。
所有的DSP应用前面提到的实例，如硬盘驱动器和移动电话，要求实时操作。
主要电子产品制造商已投入巨资在DSP技术。
因为他们现在发现在大众市场的产品应用中，DSP芯片的电子装置占有世界市场的很大比例。
销售额每年数十亿美元，并可能继续快速增长。
DSP主要应用的音频信号处理，音频压缩，数字图像处理，视频压缩，语音处理，语音识别，数字通信，雷达，声纳，地震，和生物医学。
具体的例子是在数字移动电话的语音压缩与传输，空间匹配均衡的音响、扩声领域，良好的天气预测，经济预测，地震数据处理，和工业过程控制分析，计算机生成的动画电影中，医学影像如CAT扫描和MRI，MP3压缩，图像处理，高保真度扬声器分频器和均衡，并与电吉他放大器使用的音频效果。
九、数字信号处理的实验数字信号处理是经常使用专门的微处理器，如dsp56000，TMS320，或SHARC。
这些通常处理数据使用定点运算，虽然某些版本可以使用浮点算法和更强大。
更快的应用FPGA可能从慢启动流处理器应用Freescale公司的出现，传统的较慢的处理器如单片机可能是适当的。
【英文原文】Digital Signal Processing1、IntroductionDigital signal processing (DSP) is concerned with the representation of the signals by a sequence of numbers or symbols and the processing of these signals. Digital signal processing and analog signal processing are subfields of signal processing. DSP includes subfields like audio and speech signal processing, sonar and radar signal processing, sensor array processing, spectral estimation, statistical signal processing, digital image processing, signal processing for communications, biomedical signal processing, seismic data processing, etc.Since the goal of DSP is usually to measure or filter continuous real-world analog signals, the first step is usually to convert the signal from an analog to a digital form, by using an analog to digital converter. Often, the required output signal is another analog output signal, which requires a digital to analog converter. Even if this process is more complex than analog processing and has a discrete value range, the stability of digital signal processing thanks to error detection and correction and being less vulnerable to noise makes it advantageous over analog signal processing for many, though not all, applications.DSP algorithms have long been run on standard computers, on specialized processors called digital signal processors (DSP)s, or on purpose-built hardware such as application-specific integrated circuit (ASICs). Today there are additional technologies used for digital signal processing including more powerful general purpose microprocessors, field-programmable gate arrays (FPGAs), digital signal controllers (mostly for industrial applications such as motor control), and stream processors, among others.In DSP, engineers usually study digital signals in one of the following domains: time domain (one-dimensional signals), spatial domain (multidimensional signals), frequency domain, autocorrelation domain, and wavelet domains. They choose the domain in which to process a signal by making an informed guess (or by trying different possibilities) as to which domain best represents the essential characteristics of the signal. A sequence of samples from a measuring device produces a time or spatial domain representation, whereas a discrete Fourier transform produces the frequency domain information that is the frequency spectrum. Autocorrelation is defined as the cross-correlation of the signal with itself over varying intervals of time or space.2、Signal SamplingWith the increasing use of computers the usage of and need for digital signal processing has increased. In order to use an analog signal on a computer it must be digitized with an analog to digital converter (ADC). Sampling is usually carried out in two stages, discretization and quantization. In the discretization stage, the space of signals is partitioned into equivalence classes and quantization is carried out by replace the signal with representative signal values are approximated by values from a finite set.The Nyquist-Shannon sampling theorem states that a signal can be exactly reconstructed from its samples if the samples if the sampling frequency is greater than twice the highest frequency of the signal. In practice, the sampling frequency is often significantly more than twice the required bandwidth.A digital to analog converter (DAC) is used to convert the digital signal back to analog signal.The use of a digital computer is a key ingredient in digital control systems.3 、Time and Space DomainsThe most common processing approach in the time or space domain is enhancement of the input signal through a method called filtering. Filtering generally consists of some transformation of a number of surrounding samples around the current sample of the input or output signal. There are various ways to characterize filters, for example: A “linear” filter is a linear transformation of input samples; other filters are “non-linear.” Linear filters satisfy the superposition condition, i.e. if an input is a weighted linear combination of different signals, the output is an equally weighted linear combination of the corresponding output signals.A “causal”filter uses only previous samples of the input or output signals; while a “non-causal”filter uses future input samples. A non-causal filter can usually be changed into a causal filter by adding a delay to it.A “time-invariant”filter has constant properties over time; other filters such as adaptive filters change in time.Some filters are “stable”, others are “unstable”. A stable filter produces an output that converges to a constant value with time, or remains bounded within a finite interval. An converges to a constant value with time, or remains bounded within a finite interval. An unstable filter can produce an output that grows without bounds, with bounded or even zero input.A “Finite Impulse Response”(FIR) filter uses only the input signal, while an “Infinite Impulse Response” filter (IIR) uses both the input signal and previous samples of the output signal. FIR filters are always stable, while IIR filters may be unstable.Most filters can be described in Z-domain (a superset of the frequency domain) by their transfer functions. A filter may also be described as a difference equation, a collection of zeroes and poles or, if it is an FIR filter, an impulse response or step response. The output of an FIR filter to any given input may be calculated by convolving the input signal with the impulse response. Filters can also be represented by block diagrams which can then be used to derive a sample processing algorithm to implement the filter using hardware instructions.4、Frequency DomainSignals are converted from time or space domain to the frequency domain usually through the Fourier transform. The Fourier transform converts the signal information to a magnitude and phase component of each frequency. Often the Fourier transform is converted to the power spectrum, which is the magnitude of each frequency component squared.The most common purpose for analysis of signals in the frequency domain is analysis of signal properties. The engineer can study the spectrum to determine which frequencies are present in the input signal and which are missing.Filtering, particularly in non real-time work can also be achieved by converting to the frequency domain, applying the filter and then converting back to the time domain. This is a fast, O (n log n) operation, and can give essentially any filter shape including excellent approximations to brickwall filters.There are some commonly used frequency domain transformations. For example, the cepstrum converts a signal to the frequency domain Fourier transform, takes the logarithm, then applies another Fourier transform. This emphasizes the frequency components with smaller magnitude while retaining the order of magnitudes of frequency components. Frequency domain analysis is also called spectrum or spectral analysis.5、Signal ProcessingSignals commonly need to be processed in a variety of ways. For example, the output signal from a transducer may well be contaminated with unwanted electrical “noise”. The electrodes attached to a patient’s chest when an ECG is taken measure tiny electrical voltage changes due to the activity of the heart and other muscles. The signal is often strongly affected by “mains pickup”due to electrical interference from the mains supply. Processing the signal using a filter circuit can remove or at least reduce the unwanted part of the signal. Increasingly nowadays, the filtering of signals to improve signal quality or to extract important information is done by DSP techniques rather than by analog electronics.6、Development of DSPThe development of digital signal processing dates from the 1960’s with the use of mainframe digital computers number-crunching applications such an the Fast Fourier Transform (FFT), which allows the frequency spectrum of a signal to be computed rapidly. These techniques are not widely used at that time, because suitable computing equipment was generally available only in universities and other scientific research institutions.7、Digital Signal Processors (DSPs)The introduction of the microprocessor in the late 1970’s and early 1980’s made it possible for DSP techniques to be used in a much wider range of applications. However, general-purpose microprocessors such as the Inter x86 family are not ideally suited to the numerically-intensive requirements of DSP, and during the 1980’s the increasing importance of DSP led several major electronics manufacturers (such as Texas Instruments, Analog Devices and Motorola) to develop Digital Signal Processor chips-specialised microprocessors with architectures designed specifically for the types of operations required in digital signal processing.(Note that the acronym DSP can variously mean Digital Signal Processing, the term used for a wide range of techniques for processing signals digitally, or Digital Signal Processor, a specialized type of microprocessor chip). Like a general-purpose microprocessor, a DSP is a programmable device, with its own native instruction code. DSP chip are capable of carrying out millions of floating point operations per second, and like their better-known general-purpose cousins, faster and more powerful versions are continually being introduced. DSPs can also be embedded within complex “system-on-chip” devices, often containing both analog and digital circuitry.8、Applications of DSPDSP technology is nowadays commonplace in such devices as mobile phones, multimedia computers, video recorders, CD players, hard disc drive controllers and modems, and will soon replace analog circuitry in TV sets and telephones. An important application of DSP is in signal compression and decompression. Signal compression is used in digital cellular phones to allow a greater number of calls to be handled simultaneously within each local “cell”. DSP signal compression technology allows people not only to talk to one another but also to see one anther on their computer screens, using small video cameras mounted on the computer monitors, with only a conventional telephone line linking them together. In audio CD systems, DSP technology is used to perform complex error detection and correction on the raw data as it is read from the CD.Although some of the mathematical theory underlying DSP techniques, such as Fourier and Hilbert transforms, digital filter design and signal compression, can be fairly complex, the numerical operations required actually to implement these techniques are very simple, consisting mainly of operations that could be done on a cheap four-function calculator. The architecture of aDSP chip is designed to carry out such operations incredibly fast, processing hundreds of millions of samples every second, to provided real-time performance: that is , the ability to process a signal “live” as it is sampled and then output the processed signal, for example to a loudspeaker or video display. All of the practical examples of DSP applications mentioned earlier, such as hard disc drives and mobile phones, demand real-time operation.The major electronics manufacturers have invested heavily in DSP technology. Because they now find application in mass-market products, DSP chips account for a substantial proportion of the world market for electronic devices. Sales amount to billions of dollars annually, and seem likely to continue to increase rapidly.The main applications of DSP are audio signal processing, audio compression, digital image processing, video compression, speech processing, speech recognition, digital communications, RADAR, SONAR, seismology, and biomedicine. Specific examples are speech compression and transmission in digital mobile phones, room matching equalization of sound in hi-fi and sound reinforcement applications, weather forecasting, economic forecasting, seismic data processing, analysis and control of industrial processes, computer-generated animations in movies, medical imaging such as CAT scans and MRI, MP3 compression, image manipulation, high fidelity loudspeaker crossovers and equalization, and audio effects for use with electric guitar amplifiers.9、ImplementationDigital signal processing is often implemented using specialized microprocessors such as the DSP56000, the TMS320, or the SHARC. These often process data using fixed-point arithmetic, although some versions are available which use floating point arithmetic and are more powerful. For faster applications FPGAs might be emerge from companies including Freescale and startup Stream Processors Inc. For slow applications, a traditional slower processor such as a microcontroller may be adequate.。