专业名词--专业英语-信号处理导论
信号系统英语词汇专业排版
信号系统英语词汇专业排版消息（Message）信息（Information）信号（Signal）电子信息科学与技术Electronic Information Science and Technology 光学工程Optical Engineering物理电子学Physical Electronics 光电检测与信息处理Optoelectric Inspecting and Information Processing传感器技术Transducer Technique光电检测技术Optoelectric Inspection Technique信号与系统Signal and System光电信息处理Opto-electric Information Processing专业外语Professional English无线光通信Free Space Optical Communication确定信号(Certain Signal)随机信号(Random Signal)周期信号(Periodic Signal)非周期信号(Aperiodic Signal)连续时间信号(Continuous Temporal Signal)离散时间信号(Discrete Temporal Signal)基函数(Primary Function)正交函数(Orthogonal Function)误差函数(Error Function)正交矢量(Orthogonal Vector)正交函数集(Orthogonal Function Set)完备正交函数集(Complete Orthogonal Functional Set) 复变函数(Complex Function)线性组合(Linear Combination最佳近似(Optimum Approximation)均方误差(Mean Square Error)相关系数(Correlation Coefficient)三角函数集(Trigonometric Functions)复指数函数集(Complex Exponent Function Set)连续信号(Continuous Signals)正弦函数Sine Functions 指数函数Exponent Functions抽样函数Sample Functions钟形脉冲函数（高斯函数）Bell Pulse Functions (Gaussian)奇异信号(Singular Signals)单位斜坡函数Unit Ramp Signal单位阶跃函数Unit Step Signal单位冲激函数δ(t)Unit Impulse Signal单位冲激偶δ'(t)Unit Impulse Coupling单位冲激偶δ'(t) (Unit Impulse C oupling)信号的时域分解与变换Decomposition and Transformation in Time Domain离散时间信号---序列Discrete Time Signal—Sequence 卷积Convolution信号的时域分解与变换Decomposition and Transformation of Signals in Time Domain将信号分解为正交函数的线性组合Decomposed into the linear combination of orthogonal functions将信号表示为阶跃信号或冲激信号之和Described as the sum of step signals and impulse signals 任意信号分解为阶跃函数之和Random signals decomposed into the sum of step functions 任意信号表示为冲激函数之和Random signals decomposed into the sum of step functions 信号的时域变换Signals’ transform in time domain信号的迭加与相乘Superposition & Multiplication信号的翻转（反褶）Turnover (Folding)常用的离散时间信号Frequently-used Sequences离散时间信号的运算Operations of Sequences单位函数序列Unit Function Sequence单位阶跃序列Unit Step Sequence矩形序列Rectangle Sequence斜变序列Ramp Sequence指数序列Exponent Sequence6、正弦序列Sine Sequence复指数序列Complex Exponent Sequence序列与标量相乘Multiplication between Sequence and Scalar 卷积的图解计算Diagram Calculation卷积的解析计算Analysis Calculation积分限的确定Determination of Integral Limits积分结果有效存在时间的确定Determination of the Effective Existing Time of the Integral Results§2.1 周期信号的频谱分析（傅立叶级数）Spectral Analysis of Periodic Signals三角形式的傅立叶级数Triangular Form Fourier Series指数傅立叶级数Exponent Form Fourier Series函数波形的对称性与傅立叶级数的关系Relation between the Symmetry of the Function Waveand Fourier Series基波角频率Fundamental Wave Angular Frequencyn次谐波角频率nth Harmonic Angular Frequency非周期信号的频谱分析?傅立叶变换FourierTransform频谱密度函数的概念Spectrum density function傅立叶正变换Fourier Transform傅立叶反变换Inverse Fourier Transform典型非周期信号的频谱Spectrum of typical aperiodicSignals线性（齐次性和迭加性）Linearity(Homogeneity &Addivity)奇偶虚实性Parity & Virtual propertyf(t)是虚函数Imaginary Functionf(t)是实奇函数Real Odd Function时移特性Time-shifting Character频移特性Frequency-shifting尺度变换特性Scale Variation Character对称特性Symmetry Character微分特性Differential Character频域微分特性Differential Character in Frequency Domain积分特性Integral Character卷积定理Convolution Theorem时域卷积定理Convolution Theorem in Time Domain 频域卷积定理Convolution Theorem in Time Domain 奇异函数的傅立叶变换：FT of S ingular Function线性（齐次性和迭加性）Linearity(Homogeneity & Addivity奇偶虚实性Parity & Virtual property实偶函数Real Even Function实奇函数Real Odd Function正弦、余弦信号的傅立叶变换Fourier Transform of Sine and Cosine Signals周期信号的傅立叶变换Fourier Transform of Periodic Signals卷积定理Convolution Theorem抽样信号的频谱Spectral of Sample Signals矩形脉冲抽样Rectangular Pulse Sampling冲激序列抽样Impulse Sequence Sampling抽样定理Sampling Theorem频域抽样定理Sampling Theorem in Frequency Domain拉普拉斯变换Laplace Transform拉普拉斯变换的收敛域Convergence Region拉普拉斯反变换Inverse Laplace Transform拉普拉斯变换的基本性质Basic Characters狄里赫利条件(Dirichlet Condition)绝对可积条件时Absolutely integrable condition双边拉普拉斯变换Bilateral Laplace Transform复频率(Complex Frequency)复频谱(Complex Frequency Spectrum)单边拉普拉斯变换Unilateral Laplace Transform复平面(s平面) Complex Plane拉氏变换的收敛域（ROC: Region of Convergence单边拉氏变换的收敛条件Convergence Condition收敛坐标(Convergence Coordinate指数阶函数Exponent Order Function时限信号Time Limited Signal部分分式法Partial Fraction真分式(Proper Fraction)重实根（Repeated Root）共轭复根（Conjugated Complex Root初值定理Initial Value Theorem终值定理Final Value TheoremZ变换Z TransformZ变换及其收敛域Z Transform and It’s ROCZ反变换Inverse Z Transform由抽样信号的拉氏变换引出Z变换Introducing ZT from LT of Sample SignalsZ变换的收敛域ROC of ZT级数收敛的充分必要条件为 Substantial and Necessary Condition of Series Convergence有限长序列Finite Length Sequence右边序列Right-lateral Sequence双边序列Double-lateral Sequence典型序列的Z变换ZT of Typical Sequence幂级数展开法（长除法）Power Series Expansion Method (Long Division Method) 部分分式展开法Partial Fraction Expansion重极点Multiple Poles系统函数System Function无失真传输 Undistorted Transmission幅度失真(Amplitude Distortion)相位失真(Phase Distortion)幅频特性(Amplitude-Frequency Character)相频特性(Phase-Frequency Character)线性失真（Linear Distortion）非线性失真（Nonlinear Distortion）低于截止频率(Cut-off Frequency)频带有限系统(Band Limited System)佩利-维纳准则 Paley-Wiener Criterion正弦积分函数(Sine Integral Function)极零点分布 Distribution of pole and zero渐近稳定Asymptotic stability不稳定 Unstability临界稳定Neutrality全通函数All Pass Function最小相移函数 Minimum Phase Shift Function波特图（Bode Chart)绘制原理 Drawing Principle自然对数(Natural Logarithm)对数增益(Logarithm Gain)相位(Phase)单位为弧度(rad, Radian)度(Degree)增益(Gain)增益的单位(Unit of Gain)功率比(Power Ratio)常用对数(Common Logarithm)分贝（deci Bel）加法器(Adder)、数乘器(Multiplier)、积分器(Integrator)线性系统模拟(Simulation of Linear System)微分器(Differentiator)并联形式 Parallel Form级联形式 Cascade Form反馈系统Feedback System信号流图 Signal Flow Diagram节点(Node)、支路(Branch)源节点Source Node（激励节点Simulation Node）阱节点Sink Node（响应节点 Response Node）混合节点Mixed Node通路(Access Circuit) 开通路(Open Circuit)前向开通路(Forward Open Circuit)环路(Loop Circuit)自环路(Self Loop Circuit)互不接触的环路(Noncontacted Loop Circuit)梅森(Mason)公式离散系统(Discrete System)数学模型(Mathmatic Model)差分方程(Difference Equation)后向差分 Backward Difference一阶后向差分 One-order Backward Difference二阶后向差分 Two-order Backward Differencex(k)的前向差分 Forward Difference一阶前向差分 One-order Forward Difference二阶前向差分Two-order Forward Difference 离散系统的描述 Description of Discrete System 费班纳西数列(Fibonacci Sequence)阶数（Order）离散时间系统的模拟 Simulation of Discrete System基本运算单元 Basic Operation Unit单位延时器(Unit Delayer)系统的模拟 Simulation of System。
数字信号处理导论
狭义理解可为 Digital Signal Processor 数 字信号处理器。
广义理解可为Digital Signal Processing， 译为数字信号处理技术。
数字信号处理：把信号用数字或符号表示的序列， 利用计算机或通用（专用）数字信号处理设备，用数 值计算方法处理（例如：滤波、检测、参数提取、频 谱分析等），实现信号自身或有用特征的提取，达到 认识信号、利用信号的目的。
四、数字信号处理的特点
精度高 Precision
component specification
在模拟系统中，它的精度是由元件决定，模拟元 器件的精度很难达到10-3以上。而数字系统中，17位
字长就可达10-5精度，所以在高精度系统中，通常采
用数字系统。
ADC bits, CPU word width
（信号的频谱分析和数字滤波）
How to learn?
二、课程的特点 （数学工具要求高、应用性强）
三、课程的学习方法与要求 （课上、作业、实验）
课程教学大纲
四、课程的性质和目的 五、课程的研究对象 六、课程的安排与考核 七、主要教材和参考书
绪
论
一、信号、系统和信号处理 二、数字信号处理系统的基本组成 三、数字信号处理的学科概貌 四、数字信号处理的特点 五、数字信号处理的应用
1 2 3 n
多路器
DSP
分 路 器
1 2 3 n
同步
We still need analog processing
（1）Real-Time Processing
Analog system：Besides the delay introduced by the circuit, the processing is in real-time. Digital system：Decided by the processor speed.
专业英语翻译之数字信号处理
Signal processingSignal processing is an area of electrical engineering and applied mathematics that deals with operations on or analysis of signals, in either discrete or continuous time, to perform useful operations on those signals. Signals of interest can include sound, images, time-varying measurement values and sensor data, for example biological data such as electrocardiograms, control system signals, telecommunication transmission signals such as radio signals, and many others. Signals are analog or digital electrical representations of time-varying or spatial-varying physical quantities. In the context of signal processing, arbitrary binary data streams and on-off signalling are not considered as signals, but only analog and digital signals that are representations of analog physical quantities.HistoryAccording to Alan V. Oppenheim and Ronald W. Schafer, the principles of signal processing can be found in the classical numerical analysis techniques of the 17th century. They further state that the "digitalization" or digital refinement of these techniques can be found in the digital control systems of the 1940s and 1950s.[2]Categories of signal processingAnalog signal processingAnalog signal processing is for signals that have not been digitized, as in classical radio, telephone, radar, and television systems. This involves linear electronic circuits such as passive filters, active filters, additive mixers, integrators and delay lines. It also involves non-linear circuits such ascompandors, multiplicators (frequency mixers and voltage-controlled amplifiers), voltage-controlled filters, voltage-controlled oscillators andphase-locked loops.Discrete time signal processingDiscrete time signal processing is for sampled signals that are considered as defined only at discrete points in time, and as such are quantized in time, but not in magnitude.Analog discrete-time signal processing is a technology based on electronic devices such as sample and hold circuits, analog time-division multiplexers, analog delay lines and analog feedback shift registers. This technology was a predecessor of digital signal processing (see below), and is still used in advanced processing of gigahertz signals.The concept of discrete-time signal processing also refers to a theoretical discipline that establishes a mathematical basis for digital signal processing, without taking quantization error into consideration.Digital signal processingDigital signal processing is for signals that have been digitized. Processing is done by general-purpose computers or by digital circuits such as ASICs, field-programmable gate arrays or specialized digital signal processors (DSP chips). Typical arithmetical operations include fixed-point and floating-point, real-valued and complex-valued, multiplication and addition. Other typical operations supported by the hardware are circular buffers and look-up tables. Examples of algorithms are the Fast Fourier transform (FFT), finite impulseresponse (FIR) filter, Infinite impulse response (IIR) filter, and adaptive filters such as the Wiener and Kalman filters1.Digital signal processingDigital signal processing (DSP) is concerned with the representation of 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, control of systems, biomedical signal processing, seismic data processing, etc.The goal of DSP is usually to measure, filter and/or compress continuousreal-world analog signals. The first step is usually to convert the signal from an analog to a digital form, by sampling it using an analog-to-digital converter (ADC), which turns the analog signal into a stream of numbers. However, often, the required output signal is another analog output signal, which requires a digital-to-analog converter (DAC). Even if this process is more complex than analog processing and has a discrete value range, the application of computational power to digital signal processing allows for many advantages over analog processing in many applications, such as error detection and correction in transmission as well as data compression.[1]DSP algorithms have long been run on standard computers, on specialized processors called digital signal processors (DSPs), or on purpose-built hardware such as application-specific integrated circuit (ASICs). Today thereare additional technologies used for digital signal processing including more powerful general purpose microprocessors, field-programmable gate arrays (FPGAs), digital signal controllers (mostly for industrial apps such as motor control), and stream processors, among others.[2]2. DSP domainsIn 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.3. Signal samplingMain article: Sampling (signal processing)With 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. 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 replacing the signal with representative signal of the corresponding equivalence class. In the quantization stage the 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 sampling frequency is greater than twice the highest frequency of the signal; but requires an infinite number of samples . In practice, the sampling frequency is often significantly more than twice that required by the signal's limited bandwidth.A digital-to-analog converter is used to convert the digital signal back to analog. The use of a digital computer is a key ingredient in digital control systems. 4. Time and space domainsMain article: Time domainThe most common processing approach in the time or space domain is enhancement of the input signal through a method called filtering. Digital filtering generally consists of some linear 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 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 signals, while an "infinite impulse response" filter (IIR) uses both the input signal and previous samples ofthe output signal. FIR filters are always stable, while IIR filters may be unstable.Filters can be represented by block diagrams which can then be used to derive a sample processing algorithm to implement the filter using hardware instructions. 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 a digital filter to any given input may be calculated by convolving the input signal with the impulse response.5. Frequency domainMain article: 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 todetermine which frequencies are present in the input signal and which are missing.In addition to frequency information, phase information is often needed. This can be obtained from the Fourier transform. With some applications, how the phase varies with frequency can be a significant consideration.Filtering, particularly in non-realtime 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 through 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.6. Z-domain analysisWhereas analog filters are usually analysed on the s-plane; digital filters are analysed on the z-plane or z-domain in terms of z-transforms.Most filters can be described in Z-domain (a complex number superset of the frequency domain) by their transfer functions. A filter may be analysed in the z-domain by its characteristic collection of zeroes and poles.7. ApplicationsThe 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 Hifi 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 amplifiers8. ImplementationDigital signal processing is often implemented using specialised 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[3] might be used. Beginning in 2007, multicore implementations of DSPs have started to emerge from companies including Freescale and Stream Processors, Inc. For faster applications with vast usage, ASICs might be designed specifically. For slow applications, a traditional slower processor such as a microcontroller may be adequate. Also a growing number of DSP applications are now being implemented on Embedded Systems using powerful PCs with a Multi-core processor.（翻译）信号处理信号处理是电气工程与应用数学领域，在离散的或连续时间域处理和分析信号，以对这些信号进行所需的有用的处理。
【测控专业英语】Signal Process信号处理
•
他们是许多仪器系统的基础。在仪器中，他们使 用的起源可追溯到的早期的计算机使用，首先，机械 计算机器(19世纪后期到1930年)，然后到模拟电子设 备(20世纪初到20世纪60年代)，所有这些都从大约 1950年开始由于数字计算机的使用而被代替。
12
All of these algorithmic methods of processing can be simplistically regarded as embodiments of a mathematical equation inside a suitable technological machine. • 所有的这些处理方法可以简单地看成是一个包 含适当的技术设备的数学方程具体化。 • As the demands complexity and performance requirements grew over time, so the did the demands on the detail of the algorithm and the means to model it inside a computational machine. •
• 随着算法复杂度的增长，处理能力必须提高以保持 精确和处理速度。 • Despite great advances being made in algorithm development and in computer power, the algorithmic methodology eventually encountered mathematical and technological barriers in many fields.
数学模型主要的缺点是迅速变得复杂，以致在 测量系统中这些模型运行通常是不能实现的。
信号处理导论(英文影印版) 习题答案_9-11章
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专业英语词汇(信号与系统)
《信号与系统》专业术语中英文对照表第1 章绪论信号（signal）系统（system）电压（voltage）电流（current）信息（information）电路（circuit）网络（network）确定性信号（determinate signal）随机信号（random signal）一维信号（one–dimensional signal）多维信号（multi–dimensional signal）连续时间信号（continuous time signal）离散时间信号（discrete time signal）取样信号（sampling signal）数字信号（digital signal）周期信号（periodic signal）非周期信号（nonperiodic（aperiodic）signal）能量（energy）功率（power）能量信号（energy signal）功率信号（power signal）平均功率（average power）平均能量（average energy）指数信号（exponential signal）时间常数（time constant）正弦信号（sine signal）余弦信号（cosine signal）振幅（amplitude）角频率（angular frequency）初相位（initial phase）周期（period）频率（frequency）欧拉公式（Euler’s formula）复指数信号（complex exponential signal）复频率（complex frequency）实部（real part）虚部（imaginary part）抽样函数Sa(t)（sampling（Sa）function）偶函数（even function）奇异函数（singularity function）奇异信号（singularity signal）单位斜变信号（unit ramp signal）斜率（slope）单位阶跃信号（unit step signal）符号函数（signum function）单位冲激信号（unit impulse signal）广义函数（generalized function）取样特性（sampling property）冲激偶信号（impulse doublet signal）奇函数（odd function）偶分量（even component）奇分量（odd component）正交函数（orthogonal function）正交函数集（set of orthogonal function）数学模型（mathematics model）电压源（voltage source）基尔霍夫电压定律（Kirchhoff’s voltage law（KVL））电流源（current source）连续时间系统（continuous time system）离散时间系统（discrete time system）微分方程（differential function）差分方程（difference function）线性系统（linear system）非线性系统（nonlinear system）时变系统（time–varying system）时不变系统（time–invariant system）集总参数系统（lumped–parameter system）分布参数系统（distributed–parameter system）偏微分方程（partial differential function）因果系统（causal system）非因果系统（noncausal system）因果信号（causal signal）叠加性（superposition property）均匀性（homogeneity）积分（integral）输入–输出描述法（input–output analysis）状态变量描述法（state variable analysis）单输入单输出系统（single–input and single–output system）状态方程（state equation）输出方程（output equation）多输入多输出系统（multi–input and multi–output system）时域分析法（time domain method）变换域分析法（transform domain method）卷积（convolution）傅里叶变换（Fourier transform）拉普拉斯变换（Laplace transform）第2 章连续时间系统的时域分析齐次解（homogeneous solution）特解（particular solution）特征方程（characteristic function）特征根（characteristic root）固有（自由）解（natural solution）强迫解（forced solution）起始条件（original condition）初始条件（initial condition）自由响应（natural response）强迫响应（forced response）零输入响应（zero-input response）零状态响应（zero-state response）冲激响应（impulse response）阶跃响应（step response）卷积积分（convolution integral）交换律（exchange law）分配律（distribute law）结合律（combine law）第3 章傅里叶变换频谱（frequency spectrum）频域（frequency domain）三角形式的傅里叶级数（trigonomitric Fourier series）指数形式的傅里叶级数（exponential Fourier series）傅里叶系数（Fourier coefficient）直流分量（direct composition）基波分量（fundamental composition）n 次谐波分量（n th harmonic component）复振幅（complex amplitude）频谱图（spectrum plot（diagram））幅度谱（amplitude spectrum）相位谱（phase spectrum）包络（envelop）离散性（discrete property）谐波性（harmonic property）收敛性（convergence property）奇谐函数（odd harmonic function）吉伯斯现象（Gibbs phenomenon）周期矩形脉冲信号（periodic rectangular pulse signal）周期锯齿脉冲信号（periodic sawtooth pulse signal）周期三角脉冲信号（periodic triangular pulse signal）周期半波余弦信号（periodic half–cosine signal）周期全波余弦信号（periodic full–cosine signal）傅里叶逆变换（inverse Fourier transform）频谱密度函数（spectrum density function）单边指数信号（single–sided exponential signal）双边指数信号（two–sided exponential signal）对称矩形脉冲信号（symmetry rectangular pulse signal）线性（linearity）对称性（symmetry）对偶性（duality）位移特性（shifting）时移特性（time–shifting）频移特性（frequency–shifting）调制定理（modulation theorem）调制（modulation）解调（demodulation）变频（frequency conversion）尺度变换特性（scaling）微分与积分特性（differentiation and integration）时域微分特性（differentiation in the time domain）时域积分特性（integration in the time domain）频域微分特性（differentiation in the frequency domain）频域积分特性（integration in the frequency domain）卷积定理（convolution theorem）时域卷积定理（convolution theorem in the time domain）频域卷积定理（convolution theorem in the frequency domain）取样信号（sampling signal）矩形脉冲取样（rectangular pulse sampling）自然取样（nature sampling）冲激取样（impulse sampling）理想取样（ideal sampling）取样定理（sampling theorem）调制信号（modulation signal）载波信号（carrier signal）已调制信号（modulated signal）模拟调制（analog modulation）数字调制（digital modulation）连续波调制（continuous wave modulation）脉冲调制（pulse modulation）幅度调制（amplitude modulation）频率调制（frequency modulation）相位调制（phase modulation）角度调制（angle modulation）频分多路复用（frequency–division multiplex（FDM））时分多路复用（time–division multiplex（TDM））相干（同步）解调（synchronous detection）本地载波（local carrier）系统函数（system function）网络函数（network function）频响特性（frequency response）幅频特性（amplitude frequency response）相频特性（phase frequency response）无失真传输（distortionless transmission）理想低通滤波器（ideal low–pass filter）截止频率（cutoff frequency）正弦积分（sine integral）上升时间（rise time）窗函数（window function）理想带通滤波器（ideal band–pass filter）第4 章拉普拉斯变换代数方程（algebraic equation）双边拉普拉斯变换（two-sided Laplace transform）双边拉普拉斯逆变换（inverse two-sided Laplace transform）单边拉普拉斯变换（single-sided Laplace transform）拉普拉斯逆变换（inverse Laplace transform）收敛域（region of convergence（ROC））延时特性（time delay）s 域平移特性（shifting in the s-domain）s 域微分特性（differentiation in the s-domain）s 域积分特性（integration in the s-domain）初值定理（initial-value theorem）终值定理（expiration-value）复频域卷积定理（convolution theorem in the complex frequency domain）部分分式展开法（partial fraction expansion）留数法（residue method）第5 章策动点函数（driving function）转移函数（transfer function）极点（pole）零点（zero）零极点图（zero-pole plot）暂态响应（transient response）稳态响应（stable response）稳定系统（stable system）一阶系统（first order system）高通滤波网络（high-low filter）低通滤波网络（low-pass filter）二阶系统（second system）最小相移系统（minimum-phase system）维纳滤波器（Winner filter）卡尔曼滤波器（Kalman filter）低通（low-pass）高通（high-pass）带通（band-pass）带阻（band-stop）有源（active）无源（passive）模拟（analog）数字（digital）通带（pass-band）阻带（stop-band）佩利－维纳准则（Paley-Winner criterion）最佳逼近（optimum approximation）过渡带（transition-band）通带公差带（tolerance band）巴特沃兹滤波器（Butterworth filter）切比雪夫滤波器（Chebyshew filter）方框图（block diagram）信号流图（signal flow graph）节点（node）支路（branch）输入节点（source node）输出节点（sink node）混合节点（mix node）通路（path）开通路（open path）闭通路（close path）环路（loop）自环路（self-loop）环路增益（loop gain）不接触环路（disconnect loop）前向通路（forward path）前向通路增益（forward path gain）梅森公式（Mason formula）劳斯准则（Routh criterion）第6 章数字系统（digital system）数字信号处理（digital signal processing）差分方程（difference equation）单位样值响应（unit sample response）卷积和（convolution sum）Z 变换（Z transform）序列（sequence）样值（sample）单位样值信号（unit sample signal）单位阶跃序列（unit step sequence）矩形序列(rectangular sequence)单边实指数序列（single sided real exponential sequence）单边正弦序列（single sided exponential sequence）斜边序列（ramp sequence）复指数序列（complex exponential sequence）线性时不变离散系统（linear time-invariant discrete-time system）常系数线性差分方程（linear constant-coefficient difference equation）后向差分方程（backward difference equation）前向差分方程（forward difference equation）海诺塔（Tower of Hanoi）菲波纳西（Fibonacci）冲激函数串（impulse train）第7 章数字滤波器（digital filter）单边Z 变换（single-sided Z transform）双边Z 变换(two-sided (bilateral) Z transform)幂级数（power series）收敛（convergence）有界序列（limitary-amplitude sequence）正项级数（positive series）有限长序列（limitary-duration sequence）右边序列（right-sided sequence）左边序列（left-sided sequence）双边序列（two-sided sequence）Z 逆变换（inverse Z transform）围线积分法（contour integral method）幂级数展开法（power series expansion）z 域微分（differentiation in the z-domain）序列指数加权（multiplication by an exponential sequence）z 域卷积定理（z-domain convolution theorem）帕斯瓦尔定理（Parseval theorem）传输函数（transfer function）序列的傅里叶变换（discrete-time Fourier transform：DTFT）序列的傅里叶逆变换（inverse discrete-time Fourier transform：IDTFT）幅度响应（magnitude response）相位响应（phase response）量化（quantization）编码（coding）模数变换（A/D 变换：analog-to-digital conversion）数模变换（D/A 变换：digital-to- analog conversion）第8 章端口分析法（port analysis）状态变量（state variable）无记忆系统（memoryless system）有记忆系统（memory system）矢量矩阵（vector-matrix ）常量矩阵（constant matrix ）输入矢量（input vector）输出矢量（output vector）直接法（direct method）间接法（indirect method）状态转移矩阵（state transition matrix）系统函数矩阵（system function matrix）冲激响应矩阵（impulse response matrix）朱里准则（July criterion）。
信号处理导论专业名词术语
专业名词术语总结specialized words chapter 1~6sample采样quantization量化reconstruction重建ideal reconstruction理想重建analog signal模拟信号digital signal数字信号A/D conversion模数转换D/A conversion数模转换digital signal processor数字信号处理器frequency spectrum频谱sinusoid 正弦filter滤波器pole极点zero零点exponentially decaying指数衰减impulse response冲激响应convolution卷积frequency response频率响应steady state稳态attenuate衰减magnified放大amplitude振幅aliasing混叠antaliasing profilers 抗混叠预滤波器symmetric相对的distort误传intersect相交rotate旋转clockwise顺时针duration持续时间periodically replication周期重复nodulation调制normalize归一化lowpass band低通带pass band通带DTFT序列傅氏变换Capacitor电容Resolution分解Bipolar双极性unipolar单极性rounding舍入truncation截断quantization error量化误差mean均值variance变量mean square values均方值root mean square均方根signal to noise ratio(SNR)信噪比square wave方波unipolar natural binary code单极性自然二进制码bipolar offset binary code双极性偏移二进制码bipolar two’s complement code双极性二的补码successive approximation A\D convertor 逐次比较型模数转换器full scale range满量程uniform quantization均匀量化quantization level量化等级quantization width/resolution量化宽度/间隔random variable随机变量uniform distribution均匀分布probability density概率密度stationary zero-mean white noise sequence零均值平稳白噪声序列autocorrelation 自相关cross-correlation互相关dynamic range动态范围comparator 比较器register寄存器feedback loop反馈环路linear time-invariant system线形时不变系统discrete-time system离散时间系统finite impulse response有限长单位脉冲响应infinite impulse response无限长单位脉冲响应block processing 块处理sample by sample processing逐个样本处理internal state内部状态linearity线性stability 稳定性weighted average加权平均difference equation差分卷积recursive递归even偶数odd 奇数filter coefficient滤波器系数diverge发散antidiagonal反对角线flip-and-slide翻转平移input-off-state输出暂态integrator积分器DCgain直流增益overlap-add-block convolution method重叠相加器temporary临时的adder加法器multiplier相乘器delay延迟器tapped delay line 抽头延迟器differentiator 微分器unit step 单位阶跃信号alternating step 正负交替的阶跃信号Z-transform Z变换positive正的negative负的region of convergence 收敛域marginally stable临界稳定polynomial多项式denominator 分母numerator分子peak 峰dip 谷partial fraction expansion method 部分分式展开法unit circle 单位圆double sided complex sinusoid 双边复正弦truncated complex sinusoid 单边复正弦real valued coefficient实系数complex conjugate pares 复共轭对transfer function传递函数direct form直接型parallel form并联型canonical form正准型transposed form转置型effective time constant有效时间常数resonator谐振器notch filter陷波滤波器comb filter 梳状滤波器parametric equalizer 参量均衡器channel equalization信道均衡deconvolution解卷积direct form 直接型difference equation 差分方程IIR filter 无限长单位脉冲响应滤波器FIR filter有限长单位脉冲响应滤波器adder 加法器multiplier 乘法器feeding forward 前馈feeding back 反馈numerator 分子denominator 分母polynomial 多项式coefficient 系数recursive term 递归项non-recursive term 非递归项negative 负的order 滤波器的阶internal state 内部状态state updating 状态更新transfer function 传递函数initialize 初始化cascade form 级联型register 寄存器canonical form (direct formII) 正准型（直接二型）second-order-section (SOS) 二阶基本节complex conjugate pairs 复共轭对quantization effects in digital filters 数字滤波器中的量化效应roundoff error 舍入误差sample-by-sample processing algorithm 逐个样本处理算法Chapter 8 Signal Processing Applicationdigital waveform generator 数字波形产生器periodic square wave 周期方波sinusoidal generator 正弦波产生器computational overhead 额外的计算开销exponentially decaying sinusoid 包络按指数衰减的正弦波wavetable synthesis 波表合成periodic sequence 周期序列periodic waveform generator 周期波形产生器touch—tone 全数字按键式DTMF 双音多频echo 回声combfilter 梳状滤波器reverberator 混响器noise reduction 降噪additive noise 加性噪声compromise 折衷NRR (noise reduction ratio) 降噪抑制比SNR (signal-to-noise ratio) 信噪比zero-mean white Gaussian noise 零均值高斯白噪声minimizing 最小化maximizing 最大化piece-wise linear 分段线性ECG 心电图Q-factor 品质因子time-windowing 时域加窗finite-duration 有限长sampling rate 采样率sampling time interval 采样间隔rectangular window 矩形窗hamming window 汉明窗window function 窗函数frequency leakage 频率泄露mainlobe 主瓣sidelobe 旁瓣mainlobe width 主瓣宽度relative sidelobe level 相对旁瓣水平physical frequency resolution 物理频率分辨率computational frequency resolution 计算频率分辨率resolvability condition 可分辨条件sharp spectral line 尖锐的谱线DTFT (discrete time Fourier transform) 离散时间（序列）傅立叶变换DFT (discrete Fourier transform) 离散傅立叶变换N-point DFT of a length L signal 对L长信号做N点DFTzero padding 补零biasing error 偏移误差rounding error 舍入误差matrix form 矩阵形式twiddle factor 旋转因子modulo-N 模Nperiodic extention 周期延拓computational cost 计算代价unitary matrix 酉阵merging 组合FFT (fast Fourier transform ) 快速傅立叶变换Decimation-in-time radix-2 FFT algorithm 按时间抽取的基二FFT算法butterfly merging equations 蝶形组合公式shuffling 重排bit reversal 码位倒置fast convolution 快速卷积circular convolution 圆周卷积overlap-add methord 重叠相加法overlap-save methord 重叠保留法IDFT (inverse discrete Fourier transform ) 序列傅氏反变换IFFT (inverse fast Fourier transform) 快速傅立叶反变换window method 窗口法linear phase 线性相位guarantee sability 保证稳定性lowpass 低通highpass 高通bandpass 带通bandstop 带阻transition band 过渡带passband 通带stopband 阻带differentiator 微分器Hilbert transformer 希尔伯特变换器double-sided 双边real 实部imaginary 虚部even 偶odd 奇truncate 截断cutoff frequency 截止频率transition band width 过渡带宽ripples 纹波symmetric 对称antisymmetric 反对称Chapter 11 IIR Digital Filter DesignBilinear transformation 双线性变换prewarping 预畸mapping 映射nonlinear 非线性first-order lowpass/highpass filter 一阶低通/高通滤波器high-order filter 高阶滤波器second-order notching filter 二阶陷波滤波器N-order Butterworth lowpass AF N阶巴特沃斯模拟低通滤波器magnitude response 幅度响应prototype 原型。
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测试信号分析与处理专业英语词汇
第一章系统：system 信号：signal模拟信号：analog signal 数字信号：digital signal模/数转换：analog-to-digital conversion 频谱：spectrum数字滤波：digital filtering 滤波器：filter采样：sample 保持：hold数字代码：digital code 量化电平：quantization level 时域：time domain 频域：frequency domain低频：low frequency 高频：high frequency低通滤波器：low pass filter 高通滤波器：high pass filter带通滤波器：band pass filter 带阻滤波器：band stop filter零阶保持信号:zero order hold signal 平滑：smooth采样周期：sampling period 频率分量:frequency elements图像处理：image processing 传感器：sensor电压：voltage 电流：current第二章anti-imaging filter 抗镜像滤波器sampling interval 采样间隔=sampling period 采样周期sampling frequency 采样频率=sampling rate 采样速率sampling theorem 采样定理Nyquist sampling rate 奈奎斯特采样率Nyquist frequency 奈奎斯特频率Nyquist range 奈奎斯特范围oversampling 过采样undersampling 欠采样quantization step 量化步长quantization noise量化噪声bit rate 比特率anti-aliasing filter 抗混叠滤波器第三章数字函数：digital function 合成函数：composite function 二维数字信号：two-dimensional digital signal语音信号：speech signal 量化方案：quantization scheme 脉冲函数：impulse function 单位脉冲函数：unit impulse function 阶跃函数：step function 幂函数:power function指数函数: exponential function 正弦函数：sine function余弦函数：cosine function 复平面：complex plain欧拉恒等式：Euler’s identity 模拟频率：analog frequency数字频率:digital frequency 采样间隔：sampling interval相移：phase shift 像素：pixel灰度级：gray scale第四章roll-off 滚降gain 增益pass band 通带stop band 阻带bandwidth 带宽linear system 线性系统superposition 叠加原理time-invariant 时不变causal system因果系统difference equation差分方程filter coefficient滤波器系数recursive filter 递归滤波器nonrecursive filter 非递归滤波器finite word length effect有限字长效应impulse response 脉冲响应infinite impulse response （IIR)无限脉冲响应finite impulse response (FIR)有限脉冲响应moving average filter 滑动平均滤波器step response 阶跃响应第六章z transform z变换region of convergence 收敛域inverse z transform 逆z变换transfer function 传输函数partial fraction expansion 部分分式展开cover-up method 覆盖法zero 零点pole 极点marginally stable 临界稳定unstable 不稳定第七章傅立叶变换：Fourier Transform 滤波器形状：filter shape频率响应:frequency response 频率特性：frequency characteristics 离散时间傅立叶变换：Discrete Time Fourier Transform幅度响应：magnitude response 相位响应：phase response传输函数：transfer function 相位差：phase difference采样频率：sampling frequency第八章white noise 白噪声magnitude spectrum 幅度频谱phase spectrum 相位频谱discrete Fourier series（DFS)离散傅里叶级数第九章有限脉冲响应滤波器：finite impulse response filter无限脉冲响应滤波器：infinite impulse response filter相位失真：phase distortion 理想低通滤波器：idle low pass filter 窗函数：window function 稳定性：stability通带波纹：pass band ripple 阻带波纹：stop band ripple通带边缘频率:pass band edge frequency过渡带宽度：transition width 矩形窗：Rectangular Window汉宁窗：Hanning Window 哈明窗:Hamming Window布莱克曼窗:Blackman Window 凯塞窗:Kaiser Window项数:number of terms 衰减:attenuation增益:gain 采样频率:sampling frequency第十章infinite impulse response filter(IIR)无限脉冲响应滤波器bilinear transformation 双线性变换prewarping equation 预扭曲方程Butterworth filter 巴特沃斯滤波器Chebyshev Type I filter 切比雪夫I 型滤波器Chebyshev Type II filter 切比雪夫II 型滤波器elliptic filter 椭圆滤波器Impulse invariance method 脉冲响应不变法。
【测控专业英语】SignalProcess信号处理精品PPT课件
•
当模型推动数学描述方法和人类发展的界限，
数学描述最终到达定义极限。通常，适当的细节能
够被构造进模型之前产生。算法是由于模型不足而
产生的需要。
14
Overview of Algorithmic Methods
• As the algorithm increases in complexity, the
the lack of a suitable mathematical formulation or
powerful enough processor to run the algorithm.
•
经常当算法因为缺乏适合的数学表达式和足
够强大处理器去运行算法而不能展开时，他们是
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4
• Signal processing in the modern instrument,
implementation of these models in measurement
systems is often impractical.
•
数学模型主要的缺点是迅速变得复不能实现的。
• In this class, the single, or set of multiple, input signal(s) to the data processor is converted to the output form using tightly formulated mathematical description.
development and in computer power, the algorithmic methodology eventually encountered mathematical and
测试信号分析与处理专业英语词汇
第一章系统：system 信号：signal模拟信号：analog signal 数字信号：digital signal模/数转换：analog-to-digital conversion 频谱：spectrum数字滤波：digital filtering 滤波器：filter采样：sample 保持：hold数字代码：digital code 量化电平：quantization level 时域：time domain 频域：frequency domain低频：low frequency 高频：high frequency低通滤波器：low pass filter 高通滤波器：high pass filter带通滤波器：band pass filter 带阻滤波器：band stop filter零阶保持信号:zero order hold signal 平滑：smooth采样周期：sampling period 频率分量:frequency elements图像处理：image processing 传感器：sensor电压：voltage 电流：current第二章anti-imaging filter 抗镜像滤波器sampling interval 采样间隔=sampling period 采样周期sampling frequency 采样频率=sampling rate 采样速率sampling theorem 采样定理Nyquist sampling rate 奈奎斯特采样率Nyquist frequency 奈奎斯特频率Nyquist range 奈奎斯特范围oversampling 过采样undersampling 欠采样quantization step 量化步长quantization noise量化噪声bit rate 比特率anti-aliasing filter 抗混叠滤波器第三章数字函数：digital function 合成函数：composite function 二维数字信号：two-dimensional digital signal语音信号：speech signal 量化方案：quantization scheme 脉冲函数：impulse function 单位脉冲函数：unit impulse function 阶跃函数：step function 幂函数:power function指数函数: exponential function 正弦函数：sine function余弦函数：cosine function 复平面：complex plain欧拉恒等式：Euler’s identity 模拟频率：analog frequency数字频率:digital frequency 采样间隔：sampling interval相移：phase shift 像素：pixel灰度级：gray scale第四章roll-off 滚降gain 增益pass band 通带stop band 阻带bandwidth 带宽linear system 线性系统superposition 叠加原理time-invariant 时不变causal system因果系统difference equation差分方程filter coefficient滤波器系数recursive filter 递归滤波器nonrecursive filter 非递归滤波器finite word length effect有限字长效应impulse response 脉冲响应infinite impulse response （IIR)无限脉冲响应finite impulse response (FIR)有限脉冲响应moving average filter 滑动平均滤波器step response 阶跃响应第六章z transform z变换region of convergence 收敛域inverse z transform 逆z变换transfer function 传输函数partial fraction expansion 部分分式展开cover-up method 覆盖法zero 零点pole 极点marginally stable 临界稳定unstable 不稳定第七章傅立叶变换：Fourier Transform 滤波器形状：filter shape频率响应:frequency response 频率特性：frequency characteristics 离散时间傅立叶变换：Discrete Time Fourier Transform幅度响应：magnitude response 相位响应：phase response传输函数：transfer function 相位差：phase difference采样频率：sampling frequency第八章white noise 白噪声magnitude spectrum 幅度频谱phase spectrum 相位频谱discrete Fourier series（DFS)离散傅里叶级数第九章有限脉冲响应滤波器：finite impulse response filter无限脉冲响应滤波器：infinite impulse response filter相位失真：phase distortion 理想低通滤波器：idle low pass filter 窗函数：window function 稳定性：stability通带波纹：pass band ripple 阻带波纹：stop band ripple通带边缘频率:pass band edge frequency过渡带宽度：transition width 矩形窗：Rectangular Window汉宁窗：Hanning Window 哈明窗:Hamming Window布莱克曼窗:Blackman Window 凯塞窗:Kaiser Window项数:number of terms 衰减:attenuation增益:gain 采样频率:sampling frequency第十章infinite impulse response filter(IIR)无限脉冲响应滤波器bilinear transformation 双线性变换prewarping equation 预扭曲方程Butterworth filter 巴特沃斯滤波器Chebyshev Type I filter 切比雪夫I 型滤波器Chebyshev Type II filter 切比雪夫II 型滤波器elliptic filter 椭圆滤波器Impulse invariance method 脉冲响应不变法。
专业导论_网络和信号处理
1.3 计算机网络在我国的发展
1989.11 我国第一个公用分组交换网CNPAC 运行; 1993. 该网扩充成层次结构的全国网CHINAPAC; 目前有7 大互联网络与Internet 相连： 中国公用计算机互联网(CHINANET)、 中国科技网(CSNET)、 中国教育和科研计算机网(CERNET)、 中国国家公用经济信息网(CHINAGBNET)、 中国联通数据网、 网通公用互联网(CNCNET)、 军队资源数据网。
多数科学和工程中遇到的是模拟信号。 以前都是研究模拟信号处理的理论和实现。 模拟信号处理缺点：难以做到高精度，受环境 影响较大，可靠性差，且不灵活等。 随着大规模集成电路以及数字计算机的飞速发 展，加之从60年代末以来数字信号处理理论和 技术的成熟和完善，用数字方法来处理信号， 即数字信号处理，已逐渐取代模拟信号处理。 随着信息时代、数字世界的到来，数字信号处 理已成为一门极其重要的学科和技术领域。
2.用单片机
由于单片机发展已经很久，价格便宜，且 功能很强。 优点：可根据不同环境配不同单片机，其 能达实时控制，但数据运算量不能太大。
3.利用通用DSP芯片
DSP芯片较之单片机有着更为突出优点。 如内部带有乘法器，累加器，采用流水线 工作方式及并行结构，多总线速度快。配 有适于信号处理的指令(如FFT指令)等。 目前市场上的DSP芯片有： 美国德州仪器公司(TI):TMS320CX系列 占有90% 还有AT&T公司dsp16,dsp32系列 Motorola公司的dsp56x,dsp96x系列 AD公司的ADSP21X,ADSP210X系列
多维信号处理导论Introduction to Multidimensional Signal Processing
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南邮 专业英语 信号处理导论
专业英语（自学）学院：通信与信息工程学院专业：网络工程班级： B100115学号： B100115姓名：时间 2013 年 10 月 31 日译文部分S.J.Orfanidis,Introduction to Signal Processing,Prentice Ha ll International,Inc.,2003清华大学出版社有影印版，2003.7，中文书名：《信号处理导论》第七章数字滤波器的实现§7.4从级联到规范(Cascade to Canonical) 把方程（7.1.4）的直接形式或规范形式转换为级联形式(7.3.1)式，要求把分子和分母多项式分解为二次多项式的乘积。
做到这一点可以求多项式的根，然后把它们构成共扼复数对。
过程如下：给定分母多项式的M个零点，pi i=0, 1, 2, …,M。
我们可以将D(z)表示为：如果为实数根，任意两个可以组合称为一个SOS(二阶滤波器)。
例如，p1，p2为实数，我们有：若p1为复根，则必有一个共扼复根p*1，将这两项组合得到：也可以将其表示为摸和复角。
即：，因此有：一旦将分子多项式和分母多项式分解为多个二次多项式的乘积以后，我们就可以将分母和分子中的每一对二次多项式构成一个二阶分段滤波器。
分子的二次多项式和分母的二次多项式如何构成二阶分段滤波器以及它们之间的相互次序不是唯一的。
当总的传递函数是确定的，实际应用当中，不同的组合可能会有所差别。
具体的硬件实现时，内部的每一个SOS相乘可能会产生一定量的截断误差，而这些误差会逐级传递。
最终输出时的净截断误差可能取决于前面提到的各二次多项式的组合/排序。
最优的排序可以产生最小的净截断误差。
但是找到这样一种最优的排序非常困难，且超出本书的范围。
用一些例子来讲述上面的多项式分解问题。
最烦的事情是求分子多项式和分母多项式的根。
对高次多项式，我们可以用MATLAB或Mathamatic的求方程根的子程序来实现。
信号处理导论(英文影印版)_课后习题答案_1-11章
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信号处理导论中文版
第三章 离散系统本章的讨论重点是离散系统，尤其是离散线性时不变系统。
线性时不变系统的输入输出（I/O ）方 程可以用输入信号与系统冲激响应的离散卷积来表示。
根据系统的冲激响应是否是有限延时还是无限延时可以分为有限冲激响应（FIR ）和无限冲激响 应(IIR)两种。
本章的主要目的是为FIR 滤波器设计算法。
FIR 滤波算法可以分为按块（Block to Block ） 和样值处理（Sample to Sample ）算法两种。
分批处理算法中，输入信号视为一次抽样的块。
将这一块信号与滤波器冲激响应卷积得到一个输 出块。
如果输入序列时限非常长或者是无限延时，这种方法需要做些改进，比如说可以将输入信号分成 多个块，每一块的长度都可以分别处理，可以一次滤波一块，然后再把输出拼凑在一起。
样值处理算法中，一次只处理一个抽样。
滤波器可以看作是一台状态机器，也就是说，把输入抽 样与滤波器当前的状态结合起来计算当前的输出抽样，同时也更新滤波器的内部状态为下一次处理作准 备。
当输入信号特别长的时候，这种方法对于实时运算特别有效。
滤波器自身特性变化的自适应滤波 就适合于使用这种算法。
目前的DSP 芯片对这种算法也很有效。
§3.1 输入输出规则离散系统所实现的就是将输入的离散抽样序列 x(n)，根据一定的输入/输出（I/O ）规则转换成输 出序列的运算。
I/O 规定了怎样由已知的输入计算输出。
样值处理方法，我们可以认为其I/O 规则就是一次处理一个输入抽样。
按块处理的方法，输入序列划分成块，每次处理一块。
因此其I/O 规则也就是将输入向量根据某种函数映射成输出向量。
y =H [x ]对于线性系统，这种映射就是用矩阵H 作线性变换。
线性定常系统，其变换矩阵H 根据系统的冲激响应有特定的结构。
例3.1.1例3.1.2 y (n ) = 2x (n )+3x (n -1)+4x (n -2) 。
n 时刻的输出是此前连续三个输入抽样的加权和。
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专业名词--专业英语-信号处理导论专业名词总结部分1.A/D conversion [eɪ] [diː][kən'vɜːʃ(ə)n]模数转换指为把数字信号转换为信息基本相同的模拟信号而设计的处理过程。
2.adder ['ædə]加法器加法器是产生数的和的装置。
加数和被加数为输入，和数与进位为输出的装置为半加器。
若加数、被加数与低位的进位数为输入，而和数与进位为输出则为全加器。
3.additive gauss white noise ['ædɪtɪv][gaʊs] [waɪt] [nɒɪz]加性高斯白噪声加性高斯白噪声指的是一种各频谱分量服从均匀分布（即白噪声），且幅度服从高斯分布的噪声信号。
因其可加性、幅度服从高斯分布且为白噪声的一种而得名。
4.aliasing ['eliəsɪŋ]混叠频混现象又称为频谱混叠效应，它是指由于采样信号频谱发生变化，而出现高、低频成分发生混淆的一种现象。
5.all-pass function ['ɔl,pæs] ['fʌŋ(k)ʃ(ə)n] 全通函数全通函数是凡极点位于左半开平面，零点位于右半开平面，并且所有零点与极点对于虚轴为一一镜像对称的系统函数。
6.amplifier ['æmplɪfaɪə] 放大器是指能够使用较小的能量来控制较大能量的任何器件。
7.amplitude ['æmplɪtjuːd]振幅指振动物体离开平衡位置的最大距离。
8.analog signal ['ænəlɒɡ] ['sɪgn(ə)l]模拟信号指信息参数在给定范围内表现为连续的信号。
或在一段连续的时间间隔内，其代表信息的特征量可以在任意瞬间呈现为任意数值的信号。
9.antialiasing profiler [,ænti'eliəsɪŋ] ['prəufailə] 抗混叠预滤波器指一种用以在输出电平中把混叠频率分量降低到微不足道的程度的低通滤波器。
图中，其结构都是由形似蝴蝶的运算单元所组成，所以称为蝶形运算。
10.Butterworth AF ['bʌtəwɜːθ] [eɪ][ef] 巴特沃斯模拟滤波器巴特沃斯滤波器是电子滤波器的一种。
巴特沃斯模拟滤波器的特点是通频带内的频率响应曲线最大限度平坦，没有起伏，而在阻频带则逐渐下降为零。
在振幅的对数对角频率的波特图上,从某一边界角频率开始,振幅随着角频率的增加而逐步减少,趋向负无穷大。
11.capacitor [kə'pæsɪtə] 电容是指在给定电位差下的电荷储藏量。
12.cascade form [kæs'keɪd] [fɔːm]级联型指其中每一实体只与其邻接者相互作用的多实体串联形式。
13.causal sequence ['kɔːz(ə)l]['siːkw(ə)ns]因果序列是指当n<0时，使离散系统的冲激响应h(n)恒等于0的离散系统函数序列。
14.causal system ['kɔːz(ə)l] ['sɪstəm] 因果系统是指零状态响应不会出现在激励之前的系统。
15.causality[kɔː'zælɪtɪ] 因果性是指当且仅当输入信号激励系统时，才会出现输出（响应）的系统性质。
也就是说，因果系统的（响应）不会出现在输入信号激励系统的以前时刻。
16.channel equalization ['tʃæn(ə)l] [,ikwəlɪ'zeʃən] 信道均衡是指为了提高衰落信道中的通信系统的传输性能而采取的一种抗衰落措施。
它主要是为了消除或者是减弱宽带通信时的多径时延带来的码间串扰（ISI）问题。
b filter [kəʊm]['fɪltə] 梳状滤波器梳状滤波器是由许多按一定频率间隔相同排列的通带和阻带，只让某些特定频率范围的信号通过。
梳状滤波器其特性曲线象梳子一样，故称为梳状滤波器。
parator [kəm'pærətə]比较器指能够实现对两个或多个数据项进行比较，以确定它们是否相等，或确定它们之间的大小关系及排列顺序等功能的电路或装置。
plex conjugate pares ['kɒmpleks] ['kɒndʒʊgeɪt] [peəs] 复共轭对指互为共轭的一对复数。
20.continuous signal [kən'tɪnjʊəs] ['sɪgn(ə)l]连续信号是指在连续时间范围内（—∞<t<∞）有定义的信号。
21.continuous system [kən'tɪnjʊəs] ['sɪstəm] 连续系统是指当输入信号为连续信号时，输出信号也是连续信号的系统。
22.convolution [,kɒnvə'luːʃ(ə)n] 卷积是指将一个函数f 经过翻转和平移与另一个函数g 的重叠部分进行累积的算法。
23.cross-correlation ['krɔs,kɔrə'leiʃən] 互相关是用来表示两个信号之间相似性的一个度量，通常通过与已知信号比较用于寻找未知信号中的特性。
24.cutoff frequency ['kʌt,ɔːf]['friːkw(ə)nsɪ]截止频率是用来说明电路频率特性指标的特殊频率。
当保持电路输入信号的幅度不变，改变频率使输出信号降至最大值的0.707倍，或某一特殊额定值时，此时的该频率称为截止频率。
25.D/A conversion [diː] [eɪ] [kən'vɜːʃ(ə)n] 数模转换是指为把数字信号转换为信息基本相同的模拟信号而设计的处理过程。
26.DC gain [diː][si] [geɪn] 直流增益是指频率取极限趋近于零时的交流信号增益。
27.deconvolution [di:,kɔnvə'lu:ʃən] 解卷积是指与卷积运算相反的运算，也称反卷积。
28.delay [dɪ'leɪ] 延时性是指信号输入或者输出时间上推迟的性质。
29.denominator [dɪ'nɒmɪneɪtə]分母指分数式中写在横线下面的数、字母或代数式。
30.DFT (discrete Fourier transform) [dɪ'skriːt] ['fʊriər] [træns'fɔːm]离散傅立叶变换是指将时域信号的采样信号变换为在离散时间傅里叶变换（DTFT）频域的采样信号的数学运算的变换过程。
31.difference equation['dɪf(ə)r(ə)ns] [ɪ'kweɪʒ(ə)n]差分方程差分方程是含有未知函数及其导数的方程，满足该方程的函数称为差分方程的解。
32.differentiator [,difə'renʃieitə] 微分器微分器就是能将输入信号进行微分运算的元件。
33.digital filter ['dɪdʒɪt(ə)l] ['fɪltə] 数字滤波器指由数字乘法器、加法器和延时单元组成的一种算法或装置。
其功能是对输入离散信号的数字代码进行运算处理，以达到改变信号频谱的目的。
34.digital frequency ['dɪdʒɪt(ə)l] ['friːkw(ə)nsɪ]数字角频率的归一化结果，它表示离散信号数字角频率是指模拟域频率对采样频率fs序列值变化快慢的速率。
35.digital signal processing ['dɪdʒɪt(ə)l] ['sɪgn(ə)l] ['prɑsɛs in]数字信号处理是将信号以数字方式表示并处理的理论和技术。
36.digital signal ['dɪdʒɪt(ə)l] ['sɪgn(ə)l] 数字信号是指幅度的取值是离散的，幅值表示被限制在有限个数值之内的信号。
二进制码就是一种数字信号，它受噪声的影响小，易于有数字电路进行处理，所以得到了广泛的应用。
37.digital waveform generator ['dɪdʒɪt(ə)l] ['wevfɔrm] ['dʒenəreɪtə]数字波形产生器是指可数字调频调幅的信号发生器。
38.discrete system[dɪ'skriːt] ['sɪstəm] 离散系统是指激励与响应都是离散时间信号的系统。
39.discrete-time signal [dɪ'skriːt] [taɪm] ['sɪgn(ə)l]离散时间信号是指按一定的时间间隔依次出现的幅度取值离散的信号序列。
40.discrete-time system [dɪ'skriːt] [taɪm] ['sɪstəm]离散时间系统是指按预先设定的算法规则，能够将输入的离散时间信号转换为所要求的离散时间信号并输出的特定功能的系统。
41.distort [dɪ'stɔːt]误传是指由于通信系统的缺陷或者受到噪声干扰使得信号在传输中出现差错的现象。
42.diverge [daɪ'vɜːdʒ] 发散定义：令f(x)为定义在R上的函数，如果存在实数b>0,对于任意给出的c>0，任意x1,x2满足|x1-x2|<c，有|f(x1)-f(x2)|>b，则函数为发散函数。
43.double-sided band ['dʌbl'saidid] [bænd]双边带是指为研究信号传输或发射过程，而被同时保留在信号频谱原点两侧的由调幅产生的两个有效频谱分量带。
44. DTFT (Discrete-time Fourier Transform) [dɪ'skriːt][taɪm] ['fʊriər][træns'fɔːm]离散时间傅里叶变换是指将时间域上的离散时间信号X(n)=X(nT)（其中n为整数，T为采样间隔）作为变量变换到连续的频域上的傅里叶变换。
45.DTMF (Dual-Tone Multi-Frequency) ['djuːəl] [təʊn] ['mʌlti]['friːkw(ə)nsɪ]双音多频指使用两个音频段频率的固定组合的多频信令。
两个音频段频率一个从四低频组中取出，另一个从四高频组中取出，是被使用在电话系统中电话机与交换机之间的一种用户信令，通常用于发送被叫号码。