The frequency domain
专业英语翻译
专业英语翻译第一章1.An open-loop control system utilizes an actuating device to control the process directly without using feedback.一个开环控制系统使用直接装置控制，而无需使用反馈的过程。
2.A close-loop control system uses a measurement of the output and feedback of this signal to compare it with the desired output(reference or command).闭环控制系统采用了输出的测量值和输出的反馈并将输出和期望输出进行比较（参考或命令）。
词汇automation自动化Close-loop feedback control system闭环反馈控制系统complexity of design复杂的设计control system控制系统feedback signal反馈信号engineering design工程设计，multivariable control system多变量控制系统negative feedback负反馈productivity生产力. robot机器人. specifications规格. synthesi s综合. trade-off权衡第二章1.A linear system satisfies the properties of superposition and homogeneity.线性系统满足叠加性和其次性。
2.The denominator polynominal q(s),when set equal to zero,is called the characteristic equation because the roots of this equation determine the character of the time reponse.当分母多项式q（S）设置等于零时称为特征方程，因为这个方程的根确定的时间响应的特点。
信号与系统》专业术语中英文对照表
《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（nth 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）。
(完整版)电子技术专业英语
1、汉译英1)直流电路direct current circuits2)放大器（扩音器）amplifier3)模拟电子技术analog electronics4)半导体二极管semiconductor diode5)晶体管效应transistor effect6)微处理器microprocessor7)电气工程electrical engineering8)能源工程（或电力工程）power engineering9)通信工程telecommunications engineering10)内部器件internal devices11)电子元件electrical components12)欧姆定律Ohm law13)限制电流limit current14)分压器voltage divider15)晶体管偏置电路transistor biasing circuits16)阻碍电流block DC current17)存储点能store electrical energy18)感抗inductive reactance19)绝缘材料insulating material20)交流阻抗AC resistancea)通用仪表general-purpose meterb)模拟仪表analog meterc)交换测试笔reverse the test leadsd)机械调节mechanical adjuste)测量电阻measure resistancef)正向电压positive voltageg)测量电流measure currenth)电压幅度voltage amplitudei)双踪示波器dual-trace oscilloscopej)信号发生器signal generator21)PN结PN junction22)三极管bipolar transistor23)电子和空穴electron and hole24)稳压电源electronic power supply或steady DC voltage source25)桥式整流器bridge rectifier26)脉冲直流电pulsating DC27)二极管的正极anode of diode28)峰值电压peak voltage29)电容滤波器capacitor filter30)充电和放电charge and discharge31)稳压管Zener diode32)电器电子工程师学会IEEE(Institute of Electrical and Electronics Engineers)33)专业技术组织technical professional association34)基尔霍夫电压定律Kirchhoff’s V oltage Law35)电压源voltage sources36)电荷守恒定律the law of conservation of electric charge37)在每一瞬时at every instant of time38)元件两端的电压voltages across elements39)无线电传输radio transmission40)频率调制或调频frequency modulation41)频域the frequency domain42)线性电阻linear resistor43)调幅波形amplitude modulation wave44)专用集成电路（ASIC）45)快速时间响应fast response time46)有效信号valid signal47)十进制数字系统decimal system48)逻辑运算logic operation1)控制信号线the control bus2)中断线interrupt lines1)结构化语言structured language2)局部变量local variables3)副作用side effect4)汇编语言指令assembly language instructions1)静止图像still image2)阴极射线管，显像管CRT or the cathode ray tube3)像素pixel4)电子束electron beam2、英译汉1)assembler language汇编语言2)alternating current circuits交流电路3)passive electrical circuits无源电路4)three phase circuits三相电路5)digital electronics数字电子技术6)logic gates逻辑门7)3D virtual reality image三维虚拟图像8)computer programming计算机编程9)major in（在大学里）主修10)advanced programming techniques高级编程技术1)known as capacitive reactance称为容抗2)with units ohms单位为欧姆3)prevent device from burning out防止器件烧掉4)has an AC resistance to AC current对交流电流由阻抗5)adjustment with a screw用一个螺丝调节6)in the shape of a cylinder 呈圆柱形式7)block DC current，but pass AC current阻直流通交流8)to vary the inductance改变电感9)be given by the formula 由公式给出10)the RF amplifier 音频放大器1)analog multimeter模拟万用表2)extended range扩展范围3)specific meters特殊仪表4)includes the function and range switches具有功能及范围选择旋钮5)present an electronic picture呈现一幅电子图像6)display the voltage waveform显示电压波形7)appear on the screen在屏幕上出现8)phase relationships相位关系9)an example例如，作为一个例子10)in series with the circuit串连接入电路1)Semiconductor material半导体材料2)forward biased正向偏置3)depend on the external circuit resistance取决于外部电路的电阻4)excessive reverse-biased voltage过高的反偏电压5)is directly proportional to the amount ofbase current是正比于基极电流6)may even appear almost as a short几乎可看成是短路7)cause stability problems for a transistorcircuit引起晶体管电路的稳定性问题8)digital technology数字技术9)the most popular technology最常用的技术10)use two complementary typeset oftransistors N-channel and P-channel用两种互补型的晶体管——N沟道和P沟道1)equipment operation设备的运行2)device that converts AC into DC把交流电转换成直流电的器件3)the power lines电源线4)depending on the value of DC voltageneeded 根据所需要的直流电压值5) a half-wave rectifier平波整流器6)so as to produce a constant DC output从而产生一个稳定的直流输出7)in the negative side of the capacitor在电容的负极8)flow through the load流过负载9)in the forward-biased condition在加正向偏置电压的条件下10) a series（current-limiting）resistor一个串联（限制电流）电阻1)current source电流源2)under this circumstance在这种情况下3)present the second of Kirchhoff’s laws给出基尔霍夫第二定律4)introduce the concept of a “loop”引入“回路”的概念5)An alternative statement of KVLKVL的另一种表述法6)voltages algebraically sum电压代数和7)sinusoidal steady-syate response正弦稳态响应8)ordinary household voltage日常用电的电压9)time-invariant circuit时不变电路10)percentage of modulation调制百分比reduce the power consumption减小消耗功率flip-flop 触发器the octal and hexadecimal systems当时钟脉冲信号来到时改变状态①直流电路direct current circuits②放大器（扩音器）amplifier③欧姆定律Ohm law④正极positive electrode⑤充电与放电Charge and discharge⑥无线电传输Radio transmission⑦模拟仪表Analogue Meters⑧模拟电子技术analog electronics⑨半导体二极管semiconductor⑩晶体管效应transistor effect⑪微处理器microprocessor⑫通信工程telecommunications engineering ⑬汇编语言assembler language⑭电子元件electrical components⑮限制电流limit current⑯分压器voltage divider⑰偏置电路biasing circuits⑱阻碍电流block DC current⑲感抗inductive reactance⑳容抗capacitive21正向电压positive voltage22扩展范围extended range23电压波形voltage waveform24连接入电路in series with the circuit25PN结PN junction 26三极管bipolar transistor27电子与空穴electron and hole28半导体材料semiconductor material29正向偏置forward biased30数字技术digital technology31桥式整流器bridge rectifier32稳压管Zener diode33电源线the power lines34在电容的负极in the negative side of the capacitor 在加正向偏置的条件下in the forward-biased condition一个串联电阻 a series (current-limiting)resistor35电压源voltage sources36在每一瞬时at every instant of time37无线电传输radio transmission38频率调制或调频frequency modulation39快速时间响应fast response time40有效信号valid signal41结构化语言structured language42局部变量local variables43副作用side effect44静止图像still image45阴极射线管pixel46电子束electron beam1.resistors are used to limit current flowing to adevice ,thereby preventing it from burning out, as voltage dividers to reduce voltage for other circuits, as transistor biasing circuits, and to serve as circuit loads.电阻常用做限流器，限制流过器件的电流防止烧坏器件，电阻也可用作分压器，以减小其他电路电压，还可以用在晶体管偏执电路中和作为电路负载。
自动控制原理常用名词解释知识分享
自动控制原理常用名词解释词汇第一章自动控制 ( Automatic Control) ：是指在没有人直接参与的条件下，利用控制装置使被控对象的某些物理量（或状态）自动地按照预定的规律去运行。
开环控制 ( open loop control )：开环控制是最简单的一种控制方式。
它的特点是，按照控制信息传递的路径，控制量与被控制量之间只有前向通路而没有反馈通路。
也就是说，控制作用的传递路径不是闭合的，故称为开环。
闭环控制 ( closed loop control) ：凡是将系统的输出量反送至输入端，对系统的控制作用产生直接的影响，都称为闭环控制系统或反馈控制 Feedback Control 系统。
这种自成循环的控制作用，使信息的传递路径形成了一个闭合的环路，故称为闭环。
复合控制 ( compound control ）：是开、闭环控制相结合的一种控制方式。
被控对象：指需要给以控制的机器、设备或生产过程。
被控对象是控制系统的主体，例如火箭、锅炉、机器人、电冰箱等。
控制装置则指对被控对象起控制作用的设备总体，有测量变换部件、放大部件和执行装置。
被控量 (controlled variable ) ：指被控对象中要求保持给定值、要按给定规律变化的物理量。
被控量又称输出量、输出信号。
给定值 (set value ) ：是作用于自动控制系统的输入端并作为控制依据的物理量。
给定值又称输入信号、输入指令、参考输入。
干扰 (disturbance) ：除给定值之外，凡能引起被控量变化的因素，都是干扰。
干扰又称扰动。
第二章数学模型 (mathematical model) ：是描述系统内部物理量（或变量）之间动态关系的数学表达式。
传递函数 ( transfer function) ：线性定常系统在零初始条件下，输出量的拉氏变换与输入量的拉氏变换之比，称为传递函数。
零点极点 (z ero and pole) ：分子多项式的零点（分子多项式的根）称为传递函数的零点；分母多项式的零点（分母多项式的根）称为传递函数的极点。
BIT医学图像答案2015.1.24
医学图像答案1. Image terminology explanation（医学图像术语解释）(1) image smoothing（图像平滑）Image smoothing is used to highlight the image of wide area, the low frequency component, trunk or suppress image noise and interference of high frequency components, make the image brightness flat gradient, gradient decrease mutations, improve the image quality of the image processing methods.Image smoothing methods include: interpolation method, linear smoothing method, convolution method and so on.(2)image sharpening（图像锐化）Image sharpening is to compensate the image contour, enhancing image edge and gray level jump, images by an average or integral operation, thus on the inverse operation, make the image clear.Image sharpening method includes: gradient method and Laplace algorithm, Robert algorithm and so on.(3)low-pass filter（低通滤波器）A low-pass filter is a filter that passes signals with a frequency lower than a certain cutoff frequency and attenuates signals with frequencies higher than the cutoff frequency. The amount of attenuation for each frequency depends on the filter design.(4)high-pass filter（高通滤波器）A high-pass filter is an electronic filter that passes signals with a frequency higher than a certain cutoff frequency and attenuates signals with frequencies lower than the cutoff frequency. The amount of attenuation for each frequency depends on the filter design. A high-pass filter is usually modeled as a linear time-invariant system. It is sometimes called a low-cut filter or bass-cut filter.High-pass filters have many uses, such as blocking DC from circuitry sensitive to non-zero average voltages or radio frequency devices.(5)image restoration（图像复原）Image restoration is the operation of taking a corrupted/noisy image and estimating the clean original image. Corruption may come in many forms such as motion blur, noise, and camera misfocus.Image restoration is different from image enhancement in that the latter is designed to emphasize features of the image that make the image more pleasing to the observer, but not necessarily to produce realistic data from a scientific point of view.(6)image segmentation（图像分割）image segmentation is the process of partitioning a digital image into multiple segments (sets of pixels, also known as superpixels). The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze. Image segmentation is typically used to locate objects and boundaries (lines, curves, etc.) in images. More precisely, image segmentation is the process of assigning a label to every pixel in an image such that pixels with the same label share certain characteristics.The result of image segmentation is a set of segments that collectively cover the entire image, or a set of contours extracted from the image (see edge detection). Eachof the pixels in a region are similar with respect to some characteristic or computed property, such as color, intensity, or texture. Adjacent regions are significantly different with respect to the same characteristic(s).When applied to a stack of images, typical in medical imaging, the resulting contours after image segmentation can be used to create 3D reconstructions with the help of interpolation algorithms like Marching cubes.(7) image registration（图像配准）Image registration is to different time, different sensors (imaging equipment) or under different conditions (weather, illumination, camera position and Angle, etc.) to obtain two or more image matching, superposition, the process of image registration is to point to in a medical image to seek a space (or a series of transformation, to make it with another medical image is the same on the corresponding points to the space.2.Write down the 2D Discrete Fourier transform, and discuss the relationship between the frequency components of the Fourier transform and spatial features of an image.（写出二维离散傅里叶变换，并讨论图像的傅里叶变换的频率分量与空间特性之间的关系）The 2D DFT F(u,v) can be obtained by:(1) taking the 1D DFT of every row of image f(x,y), F(u,y), (2)taking the 1D DFT of every column of F(u,y).Frequency is directly related to rate of change. The frequency of fast varying components in an image is higher than slowly varying components.The high frequency part reflects the details information(variance of gray level) of image, The low frequency part reflects the general gray-level appearance.3.What is image histogram? Which areas of histogram can be used in? What is the basic concept of histogram equalization?（什么是图像（灰度）直方图？有哪些用途？直方均衡的基本思想是什么？）Image histogram：Gray histogram is a function of grayscale, describes the number of each pixel gray levels in the image, reflect the frequencies of each gray level images.Here is a grayscale, ordinate is frequency of gray levels. Purpose: evaluation of imaging conditions, image enhancement, image segmentation, image compression, extends the conditional histogram, the joint histogram etc.The basic concept of histogram equalization：the basic idea of histogram equalization of the basic idea is to put the original figure is evenly distributed in the form of a histogram transformation, thus increasing the dynamic range of pixel gray value which can achieve the result that to enhance the overall image contrast.4.What is image enhancement in the frequency (spatial) domain? List the some of the main methods of frequency (spatial) enhancement.（什么是频率域的图像增强，什么是空间域的图像增强？列出两者各有哪些主要方法）Image enhancement：According to the specific need to highlight certain parts of the image information, at the same time, to weaken or remove some unwantedinformation processing method.Image enhancement methods: image enhancement in the spatial domain and frequency domain image enhancement.image enhancement in the frequency domain ：The image as a two-dimensional signal, carries on the two-dimensional Fourier transform, the image of a frequency domain transform coefficient for processing, then enhanced images were obtained through the inverse transformation.Frequency domain image smoothing and fuzzy mainly through the low-pass filter of high frequency attenuation.While sharpening image mainly by high frequency filter filter out low frequency.Main methods : high-pass filter, low-pass filter and homomorphic filtering enhancement method;image enhancement in the spatial domain ：Spatial domain method:In space domain of image point operations, it can allow users to change the grey value of pixels in the image, so through some processing will create a new image.Main methods : average filtering method, the median filtering method, gradient method, mask matching method, the statistical difference method.5. Write the mathematical model of image restoration, explain the main cause of image degeneration, and list some main image restoration methods.（写出图像复原的数学模型，解释图像降质的主要原因，并列出图像复原的主要方法）mathematical model ：For an input image f (x, y) for processing, to produce a picture of a degraded image g (x, y).A given g (x, y) and some knowledge about the degradation function H as well as some knowledge of additive noise item, a recovery filter is designed, the purpose of image restoration is for an estimate of the original image ),(y x f .the main cause of image degeneration ：Image degradation mainly comes from image Retrieval and transmission process: Retrieval process: as the optical imaging system aberration, diffraction, nonlinear distortion, defocusing, nonlinear, imaging process of photosensitive components of relative motion, atmospheric turbulence effect, environmental factors of random noise,will make the image produces a certain degree of degradation;Transmission process: due to the transmission channel interference to lower image quality.image restoration methods：1. Spatial filtering restoration (the only degradation is noise): mean filters, order statistic filter, the adaptive filter;2.The frequent filtering (to eliminate the periodic noise): band stop filter, bandpass, notch filtering, optimal notch filter;3. Estimating the degradation function;4. The inverse filtering;5. The minimum mean square error (mse);6. The constrained least squares filtering;7. The geometric mean filter；6.Give major medical imaging techniques, and take examples in clinical applications.（列出主要的医学成像技术，并给出临床应用实例）In modern medicine, medical imaging has undergone major advancements. Today, this ability to achieve information about the human body has many useful clinical applications. Over the years, different sorts of medical imaging have been developed, each with their own advantages and disadvantages.X-ray based methods of medical imaging include conventional X-ray, computed tomography (CT) andmammography. To enhance the X-ray image, contrast agents can be used for example for angiography examinations.Molecular imaging is used in nuclear medicine and uses a variety of methods to visualize biological processes taking place in the cells of organisms. Small amounts of radioactive markers, called radiopharmaceuticals, are used for molecular imaging.Other types of medical imaging are magnetic resonance imaging (MRI) and ultrasound imaging. Unlike conventional X-ray, CT and Molecular Imaging, MRI and ultrasound operate without ionizing radiation. MRI uses strong magnetic fields, which produce no known irreversible biological effects in humans.Diagnostic ultrasound systems use high-frequency sound waves to produce images of soft tissue and internal body organs.Imaging using X-raysX-ray imaging uses an X-ray beam that is projected on the body. When passing through the body, parts of the x-ray beam are absorbed. On the opposite side of the body, the X-rays are detected, resulting in an image.Molecular ImagingMolecular imaging provides detailed information of the biological processes taking place in the body at cellular and molecular levels and can indicate disease in its earliest stages.Other Types of Medical ImagingSome types of medical imaging work without using ionizing radiation, for example magnetic resonance imaging (MRI) and ultrasound imaging, and have specific uses in the diagnosis of disease.7. The physics, characteristics, advantage and disadvantage, and clinical applications of X-ray, MR, NMI, US.（基本原理、特点、优势、不足、临床应用）（1）X-ray(X射线)The physics:When a roughly uniform beam intensity X-ray exposure to human body, one part of X-ray absorption and scattering, the other part along the direction of the original transmission through the human body. Due to the human body all kinds of tissue and organ differences in density, thickness and so on , the absorption amount of projection on the X ray of each are not identical, so that the human body through X-ray intensity distribution change and carry human body information, and forming X-ray image information eventually. Namely for X ray imaging body.Characteristics：X-ray image information cannot identify for the human eye, it must pass a certain collection, conversion, display system of X-ray intensity distribution is converted into visible light intensity distribution, formation of X ray image visible to the human eye. Advantage：It has high resolution, which can clear the organ and structure development, and can clearly show the lesions;Disadvantage：(1) High-energy gamma ray source can cause irreversible damage to the human body tissue and the environment, even the medical X-ray CT, the accumulation of multiple use, X ray will have influence on patient is according to the organization.(2) Due to X-ray computed tomography (ct) imaging rather rely on intravenous contrast agent to development, so there is a potential danger, which may make some patients of renal injury.Clinical applications：1、Diagnosis: according to different human groups of X-ray absorption and transmittance, using high sensitivity of the instrument to measure to the human body, so that it can be taken under the body section of the inspected or stereo image, and find small lesions in any parts of the body.2、Treatment: X-rays through the body's tissues could produce ionization effect, Compton scattering, and generates electron pair, which may induce a series of biological effects.Research shows that X-ray has damage to the biological tissues, especially for the separatist activities or is the division of the cell, its damage ability is stronger.（2）MR（Magnetic Resonance磁共振）The physics：MR is the use of nuclear magnetic resonance (NMR) principle, through extra gradient magnetic field to detect the electromagnetic waves which is emitted by objects, and use it to drow into objects within the structure of the image.The imaging of the medical is the use of hydrogen nuclei in the body's tissues (protons) in magnetic field by rf pulse excitation and nuclear magnetic resonance phenomenon, produce magnetic resonance (NMR) signal, through computer processing, gives a certain level of human body image reconstruction imaging techniques.Characteristics：1、Multi-parameter imaging, it can provide abundant diagnostic information;2、High contrast imaging, it can she come to the anatomy atlas;3、Implementation from the three dimensional space observation of human body;4、Human energy metabolism,it may directly observe the biological blueprint of cell activity;5、Do not use contrast medium, it can observe the heart and blood vessels structure;6、No ionizing radiation, it can be involved in magnetic resonance imaging (MRI) treatment;7、Without the disturbance of gas and bone artifacts;Advantage：(1)without radioactive damage to human body’s organization, also do not have the biological damage;(2)soft tissue density resolution is higher than that of CT, the spatial resolution can be equivalent to that of CT.(3)It can directly do the transverse, sagittal and coronal layer and a variety of cant image;(4)More imaging parameters and methods, and more diagnostic information than CT;(5)With the help of the proton flow effect, it can clearly show that blood vessels; Disadvantage：(1)Calcification and bone disease cannot display oven;(2)Scan for a long time, daily can check the number of relatively less CT;(3)On abdominal MRI remains motion artifact interference;(4)In the body of magnetic metals cannot check;(5)It is too expensive.Clinical applications：Magnetic resonance imaging (MRI) has been used throughout the system of imaging diagnosis.Effect is the best brain, and spinal cord, heart, great vessels, joint and pelvic bone, soft tissue.For cardiovascular disease can not only observe the chamber, great vessels and valvular anatomy changes, and can make ventricular analysis, qualitative and semi-quantitative diagnosis, can make multiple sectional drawing, high spatial resolution, a heart and lesions, and its relationship with surrounding structures.In diagnosis of cerebrospinal lesions, can make coronal, sagittal and transverse section. （3）NMI（Nuclear Medical Imaging核医学成像）The physics：Introducing a radioactive isotope labeling on the drugs and into the body, when it is absorbed by the body's organs and organizations, formed the radiation source in the body.From the body in vitro were tested by nuclear detection device can rays emitted by isotope in the process of decay, radioactive isotope distribution density of the image in the body.Due to radioactive drugs remain relatively stable nuclide or marked the chemical properties and biological behavior of drugs, normally involved in the metabolism of the body, so the radioisotope images not only reflect the viscera and organization form, more important is to provide the related viscera function and related physiological, biochemical information.Characteristics：It can provide both morphological and functional of the organ or tissue.Advantage：(1) High specificity;(2) The whole body imaging;(3) Good safety;Disadvantage：It is the main problem is the price of the equipment is too high, and need to form a complete set of cyclotron to generate the required super short half-life positron tracer, which means the hospital must be equipped with cyclotron.Clinical applications：Use PET imaging, it should be injected in the patient of radioactive drugs, radioactive drugs release signals in a patient, and received by in vitro of the PET scanner, then to form images, it can appear organ or tissue chemical change, the degree of the metabolism of a portion of the pointed out that different from the norm.（4）US（UltraSound超声成像）The physics:Various organs and organizations has its specific acoustic impedance and attenuation characteristics, and therefore constitute the difference on the acoustic impedance and attenuation differences.When the ultrasonic into the body, from surface to the deep, will go through with different acoustic impedance and attenuation characteristics of different organs and tissues, resulting in a different reflection and attenuation.The different reflection and attenuation is the basis of the composition of ultrasonic bining with the received echo, according to the echo intensity, with different shades of light show on the screen, in turn, it can show section ultrasound images of the human body, called the ultrasonographic (sonogram or echogram). Characteristics：Ultrasonic imaging is an ultrasonic acoustic properties can obtain the internal structure of human organs, ultrasonic imaging technology will these information into image viewable to the human eye, so as to checking methods for the diagnosis of disease.Advantage：(1) Good real-time;(2) No damage;(3) There is no pain;(4) Low cost;Disadvantage：The contrast of the image resolution and space resolution is lower than CT and MRI. Clinical applications：Ultrasonic diagnosis foundation focuses on the detailed observation and analysis.Capture a variety of features, comprehensive analysis of the cause, the various changes in physiological condition, and combined with other forms of diagnosis.。
自动控制原理常用名词解释
词汇第一章自动控制 ( Automatic Control) ：是指在没有人直接参与的条件下，利用控制装置使被控对象的某些物理量（或状态）自动地按照预定的规律去运行。
开环控制 ( open loop control )：开环控制是最简单的一种控制方式。
它的特点是，按照控制信息传递的路径，控制量与被控制量之间只有前向通路而没有反馈通路。
也就是说，控制作用的传递路径不是闭合的，故称为开环。
闭环控制 ( closed loop control) ：凡是将系统的输出量反送至输入端，对系统的控制作用产生直接的影响，都称为闭环控制系统或反馈控制 Feedback Control 系统。
这种自成循环的控制作用，使信息的传递路径形成了一个闭合的环路，故称为闭环。
复合控制 ( compound control ）：是开、闭环控制相结合的一种控制方式。
被控对象：指需要给以控制的机器、设备或生产过程。
被控对象是控制系统的主体，例如火箭、锅炉、机器人、电冰箱等。
控制装置则指对被控对象起控制作用的设备总体，有测量变换部件、放大部件和执行装置。
被控量 (controlled variable ) ：指被控对象中要求保持给定值、要按给定规律变化的物理量。
被控量又称输出量、输出信号。
给定值 (set value ) ：是作用于自动控制系统的输入端并作为控制依据的物理量。
给定值又称输入信号、输入指令、参考输入。
干扰 (disturbance) ：除给定值之外，凡能引起被控量变化的因素，都是干扰。
干扰又称扰动。
第二章数学模型 (mathematical model) ：是描述系统内部物理量（或变量）之间动态关系的数学表达式。
传递函数 ( transfer function) ：线性定常系统在零初始条件下，输出量的拉氏变换与输入量的拉氏变换之比，称为传递函数。
零点极点 (z ero and pole) ：分子多项式的零点（分子多项式的根）称为传递函数的零点；分母多项式的零点（分母多项式的根）称为传递函数的极点。
Frequencydomainfiltering：频率域滤波
Objective. Frequency domain methods can be used.
Sections 4.1.2, 4.4 & 4.5
Image Restoration, chapter 5
• Objective: reconstruct an image that has been degraded in some way. • Main idea: Model the degradation using (a priori) information about the degradation process and apply inverse filtering
Frequency domain filter (Gaussian function)
Convolution in spatial domain, multiplication in frequency domain
Example: frequency domain filtering
input image f
Theory used in the degradation model:
If H is linear and position-invariant then: g(x,y)=h(x,y)*f(x,y)+ n(x,y) G(u,v)=H(u,v)·F(u,v)+N(u,v)
Image restoration
2D transform example 2
2D transform example 3
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）。
信号完整性分析课件03 Time and Frequency Domain
rise time and bandwidth bandwidth to interconnects, models, and measurements
2.1 The Time Domain
T I P The time domain is the real world. It is the only domain that actually exists. The 10–90 rise time is how long it takes for the signal to transition from 10% of its final value to 90% of its final value. This is usually the default meaning of rise time. The second definition is the 20–80 rise time. The fall time is typically slightly shorter than the rise time and sometimes creates more noise.
We will find that there are multiple ways of looking at a signal, each providing a different perspective. The quickest path to the answer may not be the most obvious path. The different perspectives we will use to look at signals are called domains. In particular we’ll use the time domain and the frequency domain.
Chap 4看不懂,你妹啊!!Image Enhancement in the Frequency Domain
3
(a)
(b)
(c)
(d)
4
图像变换是许多图像处理和分析的基础。 图像变换是许多图像处理和分析的基础。 是许多图像处理和分析的基础
Fourier Transform (FT)在图像处理和分析技术 在图像处理和分析技术 曾经起过并仍在起着重要的作用， 中 ， 曾经起过并仍在起着重要的作用 ， 被用于图像 增强、复原、编码和描绘。 增强、复原、编码和描绘。
常见函数的1 常见函数的1-D CFT： CFT：
函数 高斯 矩形脉冲 三角脉冲 冲激 单位阶跃 余弦 正弦 复指数
f (t) e
−π t 2
F ( u) e
2 −π u2
Π( t ) Λ( t ) δ (t) u( t )
sin (π u) π u sin (π u) (π u) 1 δ ( u) − j π u 2 δ ( u + f ) +δ ( u − f ) 2
18
4.1.3 1-D DFT 被抽样函数的DFT可表示为 被抽样函数的DFT可表示为
1 N−1 − j 2π ux / N F ( u) = ∑ f ( x)e N x=0
DFT反变换 DFT反变换
N− N−1 u=0
u = 0,1,L, N −1
f ( x) = ∑F ( u) e j 2πux / N
F ( u) = ∫ f ( x) e− j 2πuxdx = R( u) + jI ( u)
−∞
∞
从F(u)中恢复f(x)，定义为Inverse FT F(u)中恢复f(x)，定义为Inverse 中恢复f(x)
f ( x) = ∫ F ( u ⇔ f ( x)
j 2π ( ux+vy)
dft估计频谱方法的流程
dft估计频谱方法的流程英文回答：DFT (Discrete Fourier Transform) is a widely used method for estimating the frequency spectrum of a signal. It is a mathematical algorithm that transforms a discrete-time signal from the time domain to the frequency domain. The DFT can be computed using various techniques, such as the Fast Fourier Transform (FFT).The general flow of the DFT spectrum estimation method can be summarized as follows:1. Preprocessing: Before applying the DFT, it is often necessary to preprocess the signal to remove any unwanted components or artifacts. This may involve filtering, detrending, or windowing the signal.2. Discretization: The continuous-time signal is sampled at regular intervals to obtain a discrete-timesignal. The sampling rate should be at least twice the highest frequency component in the signal to avoid aliasing.3. Zero-padding (optional): To improve the frequency resolution of the DFT, zero-padding can be applied to the discrete-time signal. This involves adding zeros to the end of the signal, effectively increasing its length.4. DFT computation: The DFT is calculated using the discrete-time signal as input. The DFT algorithm decomposes the signal into a sum of sinusoidal components at different frequencies. The result is a complex-valued spectrum, which represents the amplitude and phase of each frequency component.5. Spectrum visualization: The DFT spectrum can be visualized by plotting the magnitude or power of the complex-valued spectrum against the corresponding frequencies. This provides a representation of the signal's frequency content.6. Interpretation: The DFT spectrum can be analyzed toidentify the dominant frequencies and their amplitudes.This can be useful in various applications, such as audio processing, vibration analysis, and signal classification.To illustrate the DFT spectrum estimation method, let's consider an example. Suppose we have a recorded audiosignal of a guitar playing a chord. We want to estimate the frequency spectrum of the chord using the DFT.First, we preprocess the signal by removing any background noise using a bandpass filter. Then, wediscretize the signal by sampling it at a rate of twice the highest frequency in the chord. Next, we apply zero-padding to the discrete-time signal to improve frequency resolution.We then compute the DFT of the zero-padded signal using an FFT algorithm. The resulting complex-valued spectrum represents the amplitudes and phases of the frequency components in the chord.Finally, we visualize the DFT spectrum by plotting the magnitude of the complex-valued spectrum against thecorresponding frequencies. This plot shows the frequency content of the chord, with the dominant frequencies andtheir amplitudes clearly visible.中文回答：DFT（离散傅里叶变换）是一种广泛应用的估计信号频谱的方法。
Signal processing part I_cn_85
宽带噪声: 很宽的频率范围组成, 典型的例子就是工业噪声和环境 噪声
Modulated frequencies.
调制频率
II. Fourier Transform 傅立叶变换
Is limited to stationary signal. 比较适合稳态信号 A signal is stationary if its frequency contents do not change with time. 频率成分不随时间变化的信号就是稳态信号 Therefore the frequency contents are independent of time. 因此频率成分和时间无关
X(f)=
+∞
−∞
∫
x ( t ) e − j 2 π ft dt ⇔ x ( t ) =
+∞
−∞
∫
X ( f ) e j 2 π ft df
频谱
时间历程
Fourier transform is obtained by transforming Cn from discrete variable to a continuous signal as the length T tends to infinity 傅立叶变换将Cn通过离散到连续和长度T 到无限来实现
T 2
A periodic signal (time domain) will have frequency spectrum of rays. 周期信号（时域）在频域上为谱线
Fourier transform
傅立叶变换
When the signal is no periodic the Fourier series is replaced by the Fourier integral. (This suppose that the functions under investigation are integrabled). 如果信号是非周期的，傅立叶级数被傅立叶积分取代（假设此函数可积）
子波提取
子波提取褶积模型是所有反演的基础:地震道=地震子波*反射系数+噪声频率域内, 褶积则为乘积的关系.反演相当于地震道除以地震子波, 得到反射系数:反射系数=地震道/地震子波频域内窄频段的子波限制了信息的获取范围.The narrow band wavelet restricts the available range of information in the frequency domain.地震子波完全由它的振幅谱和相位谱来定义:The Wavelet is defined completely by its amplitudespectrum and its phase spectrum:在有限频率范围内, 相位谱通常可近似为一条直线. 直线的截距是子波的常数相位旋转, 它是子波的最佳表征. 直线的斜率标示着子波的时移.The intercept of the line is the constant phase rotation which best characterizes this wavelet.The slope of the line measures the time-shift of the wavelet.极性的约定:极性约定是一个特殊的子波相位问题. 默认的约定便是: 声阻抗的增加在零相位的地震数据上代表一个波峰.A special wavelet phase issue is the Polarity convention.The default convention is that an increase in acoustic impedance is represented as a peak on zero-phase seismic data:另一个默认的约定便是: 声阻抗的增加在零相位的地震数据上代表一个波谷.The alternate convention is that an increase in acoustic impedance is represented as a trough on zero-phase seismic data:使用ì极性约定菜单î可以设置极性约定:The polarity convention is set using the SyntheticPolarity Convention menu:地震子波在时间和空间上都存在着变化, 即具有时变性和空变性, 这是基于以下几个原因:Wavelets in the earth vary both laterally (spatially) and temporally for a variety of reasons:近地表效应(空变)Near surface effects (space variant)频率吸收(时变和空变)Frequency-dependent absorption (space and time variant)层间多次波(时变和空变)Inter-bed multiples (space and time variant)NMO 拉伸处理过程中的人为因素Processing artifactsSTRATA 假定子波是常数, 不随时间和空间变化: 时间不变性: 这意味着反演就是在有限的时窗内求最优化的波阻抗Time invariant: This means that the inversion is optimized for a limited time window.空间不变性: 这意味着去除子波的空变后被最优化处理. 通常, 许多方法有可以用来提取子波. STRATA中用了以下几种:In general, a variety of methods can be used for wavelet extraction. Some are available in STRATA. (1) 仅用地震数据估计地震子波的振幅谱. 假设相位谱已经从别的渠道得知.子相关autocorrelation最大熵谱分析maximum entropy spectral analysis交互谱分析cross spectral analysisSTRATA中统计子波的提取用自相关: Statistical wavelet extraction uses the autocorrelation(2) 单独使用地震数据估算振幅谱和相位谱Estimate both amplitude and phase spectra from the seismic data alone.最小熵子波估计高阶力矩法higher order momentsSTRATA 不用这种方法, 因为STRATA认为该方法不可靠.(3) 使用给定的测量数据估计振幅谱和相位谱Estimate both amplitude and phase spectra using deterministic measurements.海洋信号marine signaturesVSP 分析STRATA中, 以ASCII文件形式读入外部子波(4) 用地震和测井资料估算振幅谱和相位谱Estimate both amplitude and phase spectra using both seismic and well log measurements.STRATA中用测井资料提取全子波.(5) 用地震资料和测井资料估算振幅谱和常数相位谱STRATA中用测井资料提取常数相位子波.STRATA中提取子波的方法:第一步, 是否用测井资料来估算子波的相位. 关键是看测井资料与地震资料的相关性是否好. 通常情况下, 必须首先进行手动校正测井曲线. The critical issue for this decision is how well the logs tie the seismic data. Usually, manual correlation must be done to align the logs first.1 提取统计子波(不用井资料):这个过程只是通对地震道进行自相关计算子波的振幅谱, 并假设已知子波的相位.主要参数:ï道范围(通常设置为较大值以增加统计所用的道数) Trace range (usually set this large to increase statistics)ï时窗(至少应该为子波长度的两倍)ï子波长度(取决于层厚和分辨率, 层厚一般取200ms, 薄层取50~100ms).2 用测井资料提取子波:用测井资料提取子波:此方法用测井资料估算子波的振幅谱和相位谱. 效果取决于测井曲线和地震道的相关程度.主要参数:选择要用的井(只用标定效果好的井)道范围(距井的距离)时窗子波长度3 用测井资料计算单一常数相位值该方法使用地震道的自相关计算子波的振幅谱, 与统计子波提取方法中一样, 用测井资料计算子波的相位谱, 并且相位谱被近似为一个单一的常数谱.This procedure calculates the amplitude spectrum of the wavelet using the autocorrelation of the seismic traces,exactly as in the statistical procedure.The phase spectrum is approximated as a single constant value, using the well logs.这种方法比较稳定, 特别是测井资料与地震数据的相关性较差时.This procedure is more robust than the full phase spectrum calculation, especially when the tie between logs and seismic is poor.计算相位的步骤:(1) 用统计子波提取方法计算子波(不用井资料).(2) 对所提取的子波进行一系列的常相位旋转(3) 用每一次旋转后的子波计算合成道, 并且与地震道进行相关.(4) 选出与地震道产生最大相关值的相位旋转子波提取中的问题:用井提取子波时, 必须首先求出测井曲线之间的最优化相关To extract a wavelet using logs, an optimum correlation must be done first.正确地相关必须以子波已知为前提To perform correlation properly, the wavelet must already be known.实际子波提取的流程:(1) 用统计子波提取来确定一个初步的子波, 假设子波的近似相位已知.(2) 拉伸或压缩测井曲线来标定地震道.(3) 使用新的测井曲线来提取新的子波.(4) 重复第(2)、（3）步，直到提取的子波达到要求为止.。
正弦量的三种表达方法
正弦量是指一种类型的信号，它具有周期性变化，其特征为输出特定持续幅度的定强度信号。
正弦量常用于物理中的运动表示、声学中的音频表示，以及数学中的正余弦函数表示。
正弦量可以使用三种不同的方法来表示：函数、波形图和频谱分析。
In mathematical terms, sine waves are represented using a trigonometric function, known as a sine wave or sinusoidal function. The most basic form of a sine wave is defined by the following equation which shows the relationship between an angle θ and the a mplitude A of the wave at any given moment in time t:y=A sin((2πft)+θ)在数学上，正弦波使用三角函数进行表示，也称之为正弦波函数。
正弦波的最基本形式可以用下面的方程来进行定义，该方程显示了时间t 内角度θ与波形振幅A之间的关系：y=A sin((2πft)+θ)Function representations of sine waves can also be shown graphically. When graphed, the wave will have an oscillatory shape, with a smooth and continuous curve that has a constant amplitude, or height, and a constant period, or time elapsed between two points on the wave.正弦波也可以通过函数形式来进行图形表示。
医学图像处理考试复习重点
C h a p t e r11.A n i m a g e m a y b e d e f i n e d a s a t w o-d i m e n s i o n a l f u n c t i o n,f(x,y),w h e r e x a n d y a r e s p a t i a l c o o r d i n a t e s,a n d t h e a m p l i t u d e o f f a t a n y p a i r o f c o o r d i n a t e s (x,y)i s c a l l e d t h e i n t e n s i t y o r g r a y l e v e l o f t h e i m a g e a t t h a t p o i n t.2.I m a g e p r o c e s s i n g i n c l u d e s i m a g e a c q u i s i t i o n,i m a g e s t o r a g e,i m a g e t r a n s m i s s i o n a n dd i g i t a l i m a ge p r o c e s s i n g.3.L o w l e v e l p r o c e s s i n v o l v e s p r i m i t i v e o p e r a t i o n s s u c h a s i m a g e p r e p r o c e s s i n g t o r e d u c e n o i s e,c o n t r a s t e n h a n c e m e n t,a n d i m a g e s h a r p e n i n g.4.M i d-l e v e l p r o c e s s i n v o l v e s t a s k s s u c h a s s e g m e n t a t i o n,d e s c r i p t i o n,a n d c l a s s i f i c a t i o n (r e c o g n i t i o n)o f i n d i v i d u a l o b j e c t s.5.A s f o r m i d-l e v e l p r o c e s s,i t s i n p u t s a r e i m a g e s,b u t i t s o u t p u t s a r e a t t r i b u t e s e x t r a c t e d f r o m t h o s ei m a g e s.6.D i g i t a l i m a g e p r o c e s s i n g e n c o m p a s s e s p r o c e s s e s w h o s e i n p u t s a n d o u t p u t s a r ei m a g e s a n d,i n a d d i t i o n,e n c o m p a s s e s p r o c e s s e s t h a t e x t r a c t a t t r i b u t e s f r o m i m a g e s,u p t o a n d i n c l u d i n g t h e r e c o g n i t i o n o f i n d i v i d u a l o b j e c t s.7.I m a g e r e s t o r a t i o n i s b a s e d o n m a t h e m a t i c a l o r p r o b a b i l i s t i c m o d e l s o f i m a g ed e g r a d a t i o n.8.I m a g e c o m p r e s s i o n i s t o r e d u c e t h e s t o r a g e r e q u i r e d t o s a v e a n i m a g e,o r t h eb a n d w i d t h r e q u i r e d t o t r a n s m i t i t.9.M o r p h o l o g i c a l p r o c e s s i n g i s t o e x t r a c t i m a g e c o m p o n e n t s t h a t a r e u s e f u l i n t h er e p r e s e n t a t i o n a n d d e s c r i p t i o n o f s h a p e.10.W h i c h o f t h e f o l l o w i n g c a n h i g h l i g h t c e r t a i n f e a t u r e s o f i n t e r e s t o f a n i m a g e?(A)I m a g e e n h a n c e m e n t(B)I m a g e r e s t o r a t i o n(C)I m a g e c o m p r e s s i o n(D)I m a g e S e g m e n t a t i o nC h a p t e r21.在晚上光线低的情况下锥状细胞起主要作用。
8.4 频域-举例
19
Phase angle 0°~0° n=m
转折频率：300, 2450, 20000 低频段斜率为0，且过A(1,0) 第一个转折频率ω=300, 之后 斜率改变-20dB/dec
1/ ( jw / 300 + 1)
第二个转折频率ω=2450， 之后斜率改变+40dB/dec ( jw / 2450)2 + j 2zw / 2450 + 1 第三个转折频率ω=20000， 之后斜率改变-20dB/dec
频带宽：闭环传递函数的幅值下降到低频段幅值的0.707倍对应的频率
表明 (1)复现输入信号的能力(2)系统通过高频信号的能力
26
As the bandwidth B increases, the rise time (Tr ) of the step response of the system will decrease (B Tr )；
2
( )
0
G 1
90
G2
180
14
k Example for nonminimum phase G (s ) s(Ts 1)
0
[G ]
L ( )
20
( ) 90 (180 tan 1 T )
= 270 tan 1 T
| G ( j ) |
( ) tan 1 T1 tan 1 T2
k
相 角 计 算
0
0 90 90 180
1 0 jT1 1 1 0 jT2 1 总和： 0
1/ T1 ( ) 45 1/ T2 ( ) 135
与虚轴交点为 (0, V(ω1))
单个无限窄脉冲 均匀频率分量
单个无限窄脉冲均匀频率分量English Answer：A single infinitely narrow pulse is a mathematical idealization that represents a signal that is non-zero only at a single point in time. In the frequency domain, this corresponds to a uniform frequency spectrum, since all frequencies are equally represented in the pulse.The Fourier transform of a single infinitely narrow pulse is a sinc function, which is a function that oscillates with decreasing amplitude around zero. The sinc function is defined as:sinc(x) = sin(x) / x.The Fourier transform of a single infinitely narrow pulse is given by:F(ω) = ∫_{-∞}^{+∞} f(t) e^(-iωt) dt = ∫_{-ε}^{+ε} A e^(-iωt) dt = A sinc(ωε)。
where:A is the amplitude of the pulse.ε is the width of the pulse.The sinc function has a main lobe that is centered at ω = 0 and has a width of approximately 2π/ε. The side lobes of the sinc function decay rapidly with increasing frequency.A single infinitely narrow pulse is often used as a mathematical model for a Dirac delta function, which is a function that is zero everywhere except at a single point. The Dirac delta function has a Fourier transform that is a uniform frequency spectrum.中文回答：单个无限窄脉冲。
matlab 频域特征
matlab 频域特征英文回答：Frequency domain analysis is a powerful technique used in signal processing and image processing to analyze the frequency content of a signal or an image. It allows us to understand the distribution of different frequencies present in the signal and provides valuable insights into the underlying characteristics of the data.In MATLAB, there are several functions and techniques available to perform frequency domain analysis. The most commonly used function is the Fourier Transform, which converts a signal from the time domain to the frequency domain. The MATLAB function fft() can be used to compute the discrete Fourier transform (DFT) of a signal. This function returns a complex-valued vector representing the frequency spectrum of the signal. By taking the absolute value of the complex spectrum, we can obtain the magnitude spectrum, which represents the distribution of differentfrequencies in the signal.For example, let's say we have a recorded audio signalof a musical instrument playing a note. We can use the fft() function in MATLAB to analyze the frequency content of the signal. By plotting the magnitude spectrum, we can identify the dominant frequencies present in the note. This information can be used for various applications, such as music analysis, audio classification, or pitch detection.Another important concept in frequency domain analysisis the power spectrum. The power spectrum represents the distribution of power across different frequencies in a signal. In MATLAB, the periodogram function, periodogram(), can be used to estimate the power spectrum of a signal.This function computes the power spectral density (PSD) using the Welch method, which provides a smoothed estimateof the power spectrum.For instance, let's consider an EEG signal recordedfrom a patient's brain. By applying the periodogramfunction in MATLAB, we can estimate the power spectrum ofthe EEG signal. The power spectrum can reveal important information about the brain activity, such as the dominant frequency bands associated with different mental states or disorders.中文回答：频域特征分析是信号处理和图像处理中常用的一种技术，用于分析信号或图像的频率内容。
（频率分析法）
8. Frequency Response Methods(频率分析法)本章主要知识点、重点：1、频率特性的概念(The Concept of Frequency Response)：幅频特性(Magnitude)，相频特性(Phase)；2、系统开环频率特性的绘制：极坐标图（polar plot ）or 奈氏曲线（Nyquist ），伯德图（Bode Diagram ），对数幅频特性(Log Magnitude Diagram)，对数相频特性(Log Phase Diagram);3、系统闭环频率特性与性能指标的关系（Performance Specifications In The Frequency Domain ）：谐振频率（r ω）、谐振峰值（p M ω）、带宽（B ω）时域法：列写微分方程，拉氏变换，拉氏反变换，得y(t); 性能指标：Tr ， Tp ， Ts ， P.O% 频率（域）法(1)克服系统分析上的困难；(2) 便于研究系统结构、参数变化对系统性能的影响； (3)频率法特性可通过实验获得； (4)图解法直观。
频率响应法的基本思想，是把控制系统中的各个变量看成是一些信号，而这些信号又是由许多不同频率的正弦信号合成的；各个变量的运动就是系统对各个频率的信号的响应的总合。
起源于通讯科学---音频、视频等是由不同频率正弦信号合成的，并以此观点进行处理和传递。
20世纪30年代引入控制科学，对控制理论发展起了强大推动作用，克服了直接用微分方程的种种困难，解决了许多理论和工程问题，迅速形成了分析和综合控制系统的一整套方法，是控制理论中极为重要的内容。
按频率响应的观点：一个控制系统的运动，无非是信号在一个一个环节之间依次传递，每个信号又是不同频率的正弦信号合成的，这些不同频率的正弦信号的振幅和相角在传递过程中，依一定的函数关系变化，就产生形式多样的运动。
近年来，还发展到可以应用于多输入多数出系统的多变量频域理论。
功率谱密度英文
功率谱密度英文IntroductionIn signal processing, power spectral density (PSD) is a measure of the power distribution of a signal over the frequency domain. Power spectral density is an essential metric for analyzingvarious image and signal processing techniques. In statistical signal processing, power spectral density represents a fundamental tool for analyzing the probabilistic properties of a stochastic signal.Power Spectral Density DefinitionThe power spectral density (PSD) of a signal is the distribution of the signal's power over the frequency domain. The idea of PSD is to examine the power of a signal of different frequency components. The formula for PSD can be expressed in terms of Fourier transform as follows:S(f) = |F(f)|^2where S(f) is the PSD of the signal, and F(f) is the Fourier transform of the signal.PSD is often used in communication systems for analyzing the power distribution of a transmitted signal over the frequency domain. The PSD of a signal helps in characterizing the signal's noise and interference from other sources. The PSD of a signal can be used to design filters, demodulators, and other signal processing techniques.Properties of Power Spectral DensityThe PSD has some unique properties that can be useful in analyzing the signal. Some of these properties are:1. Stationarity: The PSD of a signal is stationary if it has constant power over time. If a signal is stationary, its PSD will remain constant regardless of the time window.2. Fourier transform: The PSD of a signal is obtained by applying the Fourier transform to the signal. The PSD is calculated by squaring the magnitude of the Fourier transform.3. Bandwidth: The PSD of a signal gives information about the distribution of power over the frequency domain. The bandwidth of a signal isdirectly related to the power spectral density of a signal.4. Power: The total power of the signal is equal to the integral of the PSD over all frequencies.Applications of Power Spectral DensityPower spectral density has many useful applications in various fields of science and engineering. Some of the applications of PSD are:1. Antenna design: The PSD of a signal can be used to design antennas that can match the signal's frequency range.2. Image analysis: PSD is used in image processing to analyze the power distribution of an image over the frequency domain.3. Audio analysis: In audio processing, PSD is used to analyze the power distribution of a sound signal over the frequency domain.4. Signal filtering: PSD is used to design filters to remove unwanted frequencies from a signal.5. Communication systems: PSD is used in communication systems to analyze the power distribution of a transmitted signal over the frequency domain.ConclusionPower spectral density is a powerful tool for analyzing the probability distribution of a signal over the frequency domain. PSD is used in various fields of science and engineering, including antenna design, image analysis, audio analysis, signal filtering, and communication systems. Having a good understanding of PSD will help in characterizing the noise and interference in a signal and in designing filters, demodulators, and other signal processing techniques.。