数字信号处理词汇英文翻译

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。

最全电子行业术语英文翻译本文档收集了电子行业中最常见的术语及其英文翻译，以帮助读者更好地理解和使用这些术语。

1. 常见术语及英文翻译- 电子设备 (Electronic device)- 半导体 (Semiconductor)- 集成电路 (Integrated circuit)- 电路板 (Circuit board)- 芯片 (Microchip)- 电 (Capacitor)- 电阻器 (Resistor)- 电感器 (Inductor)- 发光二极管 (Light-emitting diode)- 二极管 (Diode)- 可编程逻辑门阵列 (Programmable logic gate array)- 可编程逻辑控制器 (Programmable logic controller)- 集成封装 (Integrated packaging)- 数字信号处理 (Digital signal processing) - 触摸屏 (Touchscreen)- 无线充电 (Wireless charging)- 人工智能 (Artificial intelligence)- 物联网 (Internet of Things)- 虚拟现实 (Virtual reality)- 增强现实 (Augmented reality)- 机器研究 (Machine learning)2. 其他相关术语- 电池 (Battery)- 蓝牙 (Bluetooth)- Wi-Fi (Wi-Fi)- 供应链管理 (Supply chain management) - 电子支付 (Electronic payment)- 信息安全 (Information security)- 数据隐私 (Data privacy)- 用户界面 (User interface)- 数据存储 (Data storage)- 硬件 (Hardware)- 软件 (Software)- 网络安全 (Network security)- 数据备份 (Data backup)- 电子签名 (Electronic signature)- 电子邮箱 (Email)- 数据恢复 (Data recovery)- 电子证书 (Digital certificate)- 电子表格 (Spreadsheet)- 数据分析 (Data analysis)- 电子文档 (Electronic document)- 云存储 (Cloud storage)请注意，本文档收集的是最常见的电子行业术语及其英文翻译，如果有其他术语需要翻译或有任何疑问，请随时与我联系。

电工翻译词汇D235digital feedback system,数字反馈系统digital filter,数字滤波器digital fluxmeter,数字磁通表digital frequency meter,数字频率表digital information processing system,数字信息处理系统digital input,数字输入digital integrating fluxmeter,数字积分式磁通表digital logging instrument,数字测井仪digital magnetic tape record type strong-motion instrument, 数字磁带记录强震仪 digitalmagnetic telluro sounding instrument,数字大地电磁测深仪digital measuring instrument,数字式测量仪器仪表digital multimeter,数字万用表；数字复用表digital ohmmeter,数字电阻表digital ouput,数字输出digital phase meter,数字相位表digital position transmitter,数字式位置发送器digital positioner,数字式定位器digital power driver,数字功率表digital pressure gauge,数字压力表digital readout,数字读出digital representation of a physical quantity,物理量的数字表示digital seismic recoridng system,数字地震仪digital signal,数字信号digital signal analyzer,数字信号分析仪digital signal processing,数字信号处理digital simulation,数字仿真digital simulation computer,数字仿真计算机digital strain indicator,数字应变仪digital system,数字系统digital telemetering system,数字遥测系统digital transducer[sensor],数字传感器digital valve,数字阀digital voltmeter,数字电压表digital-analog conversion,楼模转换(digital-analog)hybrid computer,（数字模拟）混合计算机digital-analog simulator,数字模拟仿真器digital-analogue converter;D/A converter,数-模转换器；D/A 转换器digitalization error,数字化误差digitization,数字化digitization error,数字化误差digitizer,数字化仪dilatometry,膨胀法diluent gas,稀释气dilution factor,稀释因数36dilution methods,稀释法dilution ratio[rate],稀释比[率]dimension,尺度dimension transducer[semsor],尺度传感器Dines anemometer,达因风速表diopter,视度dip logger,地层倾角测井仪direct acting instrument,直接作用仪表direct acting recording instrument,直流作用记录仪direct action,正作用direct action solenoid valve,直动式电磁阀direct actuator,正作用执行机构direct-comparison method of measurement,直接比较测量法direct control layer,直接控制层direct-current linear variable differential transformer(DC-DC LVDT), 直流差动变压器 directdigital control station ,直接数字控制站direct digital control,直接数字控制direct heated type thermistor,直热式热敏电阻器direct-imaging mass analyser,直接成象质量分析仪direct injection burner,直接注入燃烧器direct injector,直流进样器direct method of measurement,直接测量法direct mounting gauge,直接安装压力表direct-operated regulator,直接作用式调节阀；自力式调节阀direct probe inlet,直接探头进样direct reading current meter,直读式海流计direct reading instrument,直读式仪器direct record strong-motion instrument,直接记录式强震仪direct resistance heating,直接电阻加热direction focusing,方向聚焦direction indicator,中心指示器direction mark meter,方位标仪directional frequency response of microphone,传声器指向性频率响应directional pattern of microphone,传声器指向性图案directivity,指向性directivity index of microphone,传声器指向性指数directly controlled system,直接被控系统directly controlled variable,直接被控变量director,指挥站disappearing-filament optical pyrometer,隐丝式光学高温计disc,阀板disc plug,盘形阀芯disc recorder,圆盘（形）记录仪discharge coefficient,流出系数37discharge lamp,放电灯discontinuous control,不连续控制discontinuous control system,不连续控制系统discontinuous simultaneous techniques,间歇联用技术；不连续同时串用技术discrete control system,离散控制系统discrete signal,离散信号discrete system model,离散系统模型discrete system simulation,离散系统仿真discrete system simulation language,离散系统仿真语言discriminant function,判别函数discrimination,鉴别力discrimination threshold,鉴别力阀diskette,软磁盘dispersion dose,散射剂量dispersion power,色散本领dispersive crystal,分光晶体dispersive infra-red gas analyzer,色散红外线气体分析器displacement,位移displacement divelopment,顶替展开法displacement pickup,位移传感器displacement transducer[sensor],位移传感器displacement,velocity and acceleration shock response spectrum, 位移、速度和加速度冲击响应谱display attribute,显示属性display console,显示控制台display device,显示器；显示设备display element,显示元件display unit,显示单元dissipation constant,耗散常数dissipation power,耗散功率dissolved oxygen analyzer,溶解氧分析器dissolved oxygen analyzer for seawater,海水溶解氧测定仪dissolved oxygen of seawater,海水中的溶解氧distance amplitude compensation,距离振幅补偿distance amplitude curve,距离振幅曲线distance constant,距离常数distance factor,距离系数distance marder,距离刻度distance meter,测距仪distance of centre of gravity,重心距distorted peak,畸峰distortion,失真；畸变distributed computer-control SDAS,分布式遥测型数字地震仪distributed computer control system, 分散型计算机控制系统；分布式计算机控制系统38distributed control,分散控制；分布控制distributed control system,分散型控制系统；分布式控制系统distributed data base,分布式数据库distributed intelligence,分散智能 distributed networkm,分布式网络distributed parameter control system,分散[分布]能数控制系统distributed telemetry SDAS,分布式遥测型数字地震仪distribution temperature,分布温度disturbance,扰动dither,颤振dithering,颤动diverging three way valve,三通分流阀diverter,换向器diving bell,潜水钟document．文件；文献document．tion,文件管理；文件集domestic package,内销包装dominant frequency,优势频率；主频率Doppler current meter,多普勒海流计Doppler effect,多普勒效应Doppler flowmeter,多普勒流量计Doppler radar,多普勒雷达Doppler sonar,多普勒声纳dose,剂量dose rate,剂量率dose rate meter,剂量率计dosementer,剂量计dot matrix printer,点阵式打印机dot printer,点阵印刷机；点阵打印机dotted line recorder,断续线记录仪dotting time,打点时间double acting positioner,双作用定位器double-beam mass spectrometer,双束质谱计double beam spectrum radiator,双光束光谱福射计double bounce technique,二次反射法double collectors,双接收器double-cone viscometer,双锥粘度计double crystal probe,双振子探头double-dry calorimeter,双干式热量计double-focusing mass spectroscope,双聚焦质谱仪器double-focus X-ray tube,双焦点X 射线管double focusing,双聚焦double focusing analyzer,双聚焦分析器double focusing at all masses,全质量双聚焦double-image tacheometer,双像速测仪。

数字信号处理中的英文缩写在数字信号处理领域中，有许多常用的英文缩写，以下是一些常见的缩写及其含义：1. DSP：数字信号处理（Digital Signal Processing）2. FFT：快速傅里叶变换（Fast Fourier Transform）3. FIR：有限脉冲响应（Finite Impulse Response）4. IIR：无限脉冲响应（Infinite Impulse Response）5. DFT：离散傅里叶变换（Discrete Fourier Transform）6. IDFT：离散傅里叶逆变换（Inverse Discrete Fourier Transform）7. ADC：模数转换器（Analog-to-Digital Converter）8. DAC：数模转换器（Digital-to-Analog Converter）9. LTI：线性时不变（Linear Time-Invariant）10. SNR：信噪比（Signal-to-Noise Ratio）11. MSE：均方误差（Mean Squared Error）12. PDF：概率密度函数（Probability Density Function）13. CDF：累积分布函数（Cumulative Distribution Function）14. PSD：功率谱密度（Power Spectral Density）15. FIR filter：有限脉冲响应滤波器16. IIR filter：无限脉冲响应滤波器17. AWGN：加性白噪声（Additive White Gaussian Noise）18. QAM：正交振幅调制（Quadrature Amplitude Modulation）19. BPSK：二进制相移键控（Binary Phase-Shift Keying）20. FSK：频移键控（Frequency-Shift Keying）这些缩写在数字信号处理的理论、算法、实现中都有广泛应用，了解这些缩写有助于更好地理解和掌握数字信号处理相关知识。

英文原文The simulation and the realization of the digital filter With the information age and the advent of the digital world, digital signal processing has become one of today's most important disciplines and door technology. Digital signal processing in communications, voice, images, automatic control, radar, military, aerospace, medical and household appliances, and many other fields widely applied. In the digital signal processing applications, the digital filter is important and has been widely applied.1、figures Unit on :Analog and digital filtersIn signal processing, the function of a filter is to remove unwanted parts of the signal, such as random noise, or to extract useful parts of the signal, such as the components lying within a certain frequency range.There are two main kinds of filter, analog and digital. They are quite different in their physical makeup and in how they work. An analog filter uses analog electronic circuits made up from components such as resistors, capacitors and op amps to produce the required filtering effect. Such filter circuits are widely used in such applications as noise reduction, video signal enhancement, graphic equalisers in hi-fi systems, and many other areas. There are well-established standard techniques for designing an analog filter circuit for a given requirement. At all stages, the signal being filtered is an electrical voltage or current which is the direct analogue of the physical quantity (e.g. a sound or video signal or transducer output) involved. A digital filter uses a digital processor to perform numerical calculations on sampled values of the signal. The processor may be a general-purpose computer such as a PC, or a specialised DSP (Digital Signal Processor) chip. The analog input signal must first be sampled and digitised using an ADC (analog to digital converter). The resulting binary numbers, representing successive sampled values of the input signal, are transferred to the processor, which carries out numerical calculations on them. These calculations typically involve multiplying the input values by constants and adding the products together. If necessary, the results of these calculations, which now represent sampled values of the filtered signal, are output through a DAC (digital to analog converter) to convert the signal back to analog form.Note that in a digital filter, the signal is represented by a sequence of numbers, rather than a voltage or current.Unit refers to the input signals used to filter hardware or software. If the filter input, output signals are separated, they are bound to respond to the impact of the Unit is separated, such as digital filters filter definition. Digital filter function, which was to import sequences X transformation into export operations through a series Y.According to figures filter function 24-hour live response characteristics, digital filters can be divided into two, namely, unlimited long live long live the corresponding IIR filter and the limited response to FIR filters. IIR filters have the advantage of the digital filter design can use simulation results, and simulation filter design of a large number of tables may facilitate simple. It is the shortcomings of the nonlinear phase; Linear phase if required, will use the entire network phase-correction. Image processing and transmission of data collection is required with linear phase filters identity. And FIR linear phase digital filter to achieve, but an arbitrary margin characteristics. Impact from the digital filter response of the units can be divided into two broad categories : the impact of the limited response (FIR) filters, and unlimited number of shocks to (IIR) digital filters.FIR filters can be strictly linear phase, but because the system FIR filter function extremity fixed at the original point, it can only use the higher number of bands to achieve their high selectivity for the same filter design indicators FIR filter called band than a few high-IIR 5-10 times, the cost is higher, Signal delay is also larger. But if the same linear phase, IIR filters must be network-wide calibration phase, the same section also increase the number of filters and network complexity. FIR filters can be used to achieve non-Digui way, not in a limited precision of a shock, and into the homes and quantitative factors of uncertainty arising from the impact of errors than IIR filter small number, and FIR filter can be used FFT algorithms, the computational speed. But unlike IIR filter can filter through the simulation results, there is no ready-made formula FIR filter must use computer-aided design software (such as MATLAB) to calculate. So, a broader application of FIR filters, and IIR filters are not very strict requirements on occasions.2、MATLAB introducedMATLAB is a matrix laboratory (Matrix Laboratory) is intended. In addition to anexcellent value calculation capability, it also provides professional symbols terms, word processing, visualization modeling, simulation and real-time control functions. MATLAB as the world's top mathematical software applications, with a strong engineering computing, algorithms research, engineering drawings, applications development, data analysis and dynamic simulation, and other functions, in aerospace, mechanical manufacturing and construction fields playing an increasingly important role. And the C language function rich, the use of flexibility, high-efficiency goals procedures. High language both advantages as well as low level language features. Therefore, C language is the most widely used programming language. Although MATLAB is a complete, fully functional programming environment, but in some cases, data and procedures with the external environment of the world is very necessary and useful. Filter design using Matlab, could be adjusted with the design requirements and filter characteristics of the parameters, visual simple, greatly reducing the workload for the filter design optimization.In the electricity system protection and secondary computer control, many signal processing and analysis are based on are certain types Yeroskipou and the second harmonics of the system voltage and current signals (especially at D process), are mixed with a variety of complex components, the filter has been installed power system during the critical components. Current computer protection and the introduction of two digital signal processing software main filter. Digital filter design using traditional cumbersome formula, the need to change the parameters after recalculation, especially in high filters, filter design workload. Uses MATLAB signal processing boxes can achieve rapid and effective digital filter design and simulation.MATLAB is the basic unit of data matrix, with its directives Biaodashi mathematics, engineering, commonly used form is very similar, it is used to solve a problem than in MATLAB C, Fortran and other languages End precision much the same thing. The popular MATLAB 5.3/Simulink3.0 including hundreds of internal function with the main pack and 30 types of tool kits (Toolbox). kits can be divided into functional tool kits and disciplines toolkit. MATLAB tool kit used to expand the functional symbols terms, visualization simulation modelling, word processing and real-time control functions. professional disciplines toolkit is a stronger tool kits, tool kits control, signal processing tool kit, tool kits, etc. belonging to such communicationsMATLAB users to open widely welcomed. In addition to the internal function, all thepackages MATLAB tool kits are readable document and the document could be amended, modified or users through Yuanchengxu the construction of new procedures to prepare themselves for kits.3、Digital filter designDigital filter design of the basic requirementsDigital filter design must go through three steps :(1) Identification of indicators : In the design of a filter, there must be some indicators. These indicators should be determined on the basis of the application. In many practical applications, digital filters are often used to achieve the frequency operation. Therefore, indicators in the form of general jurisdiction given frequency range and phase response. Margins key indicators given in two ways. The first is absolute indicators. It provides a function to respond to the demands of the general application of FIR filter design. The second indicator is the relative indicators. Its value in the form of answers to decibels. In engineering practice, the most popular of such indicators. For phase response indicators forms, usually in the hope that the system with a linear phase frequency bands human. Using linear phase filter design with the following response to the indicators strengths：①it only contains a few algorithms, no plural operations；②there is delay distortion, only a fixed amount of delay; ③the filter length N (number of bands for N-1), the volume calculation for N/2 magnitude.(2) Model approach : Once identified indicators can use a previous study of the basic principles and relationships, a filter model to be closer to the target system.(3) Achieved : the results of the above two filters, usually by differential equations, system function or pulse response to describe. According to this description of hardware or software used to achieve it.4、Introduced FPGAProgrammable logic device is a generic logic can use a variety of chips, which is to achieve ASIC ASIC (Application Specific Integrated Circuit) semi-customized device, Its emergence and development of electronic systems designers use CAD tools to design their own laboratory in the ASIC device. Especially FPGA (Field Programmable Gate Array) generated and development, as a microprocessor, memory, the figures for electronic system design and set a new industry standard (that is based on standard product sales catalogue in the market to buy).Is a digital system for microprocessors, memories, FPGA or three standard building blocks constitute their integration direction.Digital circuit design using FPGA devices, can not only simplify the design process and can reduce the size and cost of the entire system, increasing system reliability. They do not need to spend the traditional sense a lot of time and effort required to create integrated circuits, to avoid the investment risk and become the fastest-growing industries of electronic devices group. Digital circuit design system FPGA devices using the following main advantages(1)Design flexibleUse FPGA devices may not in the standard series device logic functional limitations. And changes in system design and the use of logic in any one stage of the process, and only through the use of re-programming the FPGA device can be completed, the system design provides for great flexibility.(2) Increased functional densityFunctional density in a given space refers to the number of functional integration logic. Programmable logic chip components doors several high, a FPGA can replace several films, film scores or even hundreds of small-scale digital IC chip illustrated in the film. FPGA devices using the chip to use digital systems in small numbers, thus reducing the number of chips used to reduce the number of printed size and printed, and will ultimately lead to a reduction in the overall size of the system.(3) Improve reliabilityPrinting plates and reduce the number of chips, not only can reduce system size, but it greatly enhanced system reliability. A higher degree of integration than systems in many low-standard integration components for the design of the same system, with much higher reliability. FPGA device used to reduce the number of chips required to achieve the system in the number printed on the cord and joints are reduced, the reliability of the system can be improved.(4) Shortening the design cycleAs FPGA devices and the programmable flexibility, use it to design a system for longer than traditional methods greatly shortened. FPGA device master degrees high, use printed circuit layout wiring simple. At the same time, success in the prototype design, the development of advanced tools, a high degree of automation, their logic is very simple changes quickly.Therefore, the use of FPGA devices can significantly shorten the design cycle system, and speed up the pace of product into the market, improving product competitiveness.(5) Work fastFPGA/CPLD devices work fast, generally can reach several original Hertz, far larger than the DSP device. At the same time, the use of FPGA devices, the system needed to achieve circuitclasses and small, and thus the pace of work of the entire system will be improved.(6)Increased system performance confidentialityFPGA is the English abbreviation Field of Programmable Gate Array for the site programmable gate array, which is in Pal, Gal, Epld, programmable device basis to further develop the product. It is as ASIC (ASIC) in the field of a semi-customized circuit and the emergence of both a customized solution to the shortage circuit, but overcome the original programmable devices doors circuit few limited shortcomings.FPGA logic module array adopted home (Logic Cell Array), a new concept of internal logic modules may include CLB (Configurable Logic Block), export import module IOB (Input Output Block) and internal links (Interconnect) 3. FPGA basic features are :(1) Using FPGA ASIC design ASIC using FPGA circuits, the chip can be used,while users do not need to vote films production.(2) FPGA do other customized or semi-customized ASIC circuits throughout the Chinese specimen films.3) FPGA internal capability and rich I/O Yinjue.4) FPGA is the ASIC design cycle, the shortest circuit, the lowest development costs, risks among the smallest device5) FPGA using high-speed Chmos crafts, low consumption, with CMOS, TTL low-power compatibleIt can be said that the FPGA chip is for small-scale systems to improve system integration, reliability one of the bestCurrently FPGA many varieties, the Revenue software series, TI companies TPC series, the fiex ALTERA company seriesFPGA is stored in films from the internal RAM procedures for the establishment of the state of its work, therefore, need to programmed the internal Ram. Depending on the differentconfiguration, users can use a different programming methodsPlus electricity, FPGA, EPROM chips will be read into the film, programming RAM中data, configuration is completed, FPGA into working order. Diaodian, FPGA resume into white films, the internal logic of relations disappear, FPGA to repeated use. FPGA's programming is dedicated FPGA programming tool, using generic EPROM, prom programming device can. When the need to modify functional FPGA, EPROM can only change is. Thus, with a FPGA, different programming data to produce different circuit functions. Therefore, the use of FPGA very flexible.There are a variety of FPGA model : the main model for a parallel FPGA plus a EPROM manner; From the model can support a number of films FPGA; serial prom programming model could be used serial prom FPGA programming FPGA; The external model can be engineered as microprocessors from its programming microprocessors.Verilog HDL is a hardware description language for the algorithm level, doors at the level of abstract level to switch-level digital system design modelling. Modelling of the target figure by the complexity of the system can be something simple doors and integrity of electronic digital systems. Digital system to the levels described, and in the same manner described in Hin-time series modelling.Verilog HDL language with the following description of capacity : design behaviour characteristics, design data flow characteristics, composition and structure designed to control and contain the transmission and waveform design a certification mechanism. All this with the use of a modelling language. In addition, Verilog HDL language programming language interface provided by the interface in simulation, design certification from the external design of the visit, including specific simulation control and operation.Verilog HDL language grammar is not only a definition, but the definition of each grammar structure are clear simulation, simulation exercises. Therefore, the use of such language to use Verilog simulation models prepared by a certification. From the C programming language, the language inherited multiple operating sites and structures. Verilog HDL provides modelling capacity expansion, many of the initial expansion would be difficult to understand. However, the core subsets of Verilog HDL language very easy to learn and use, which is sufficient for most modelling applications. Of course, the integrity of the hardware description language is the most complex chips from the integrity of the electronic systems described.5、In troduction of DSPToday, DSP is w idely used in the modern techno logy and it has been the key part of many p roducts and p layed more and mo re impo rtant ro le in our daily life.Recent ly, Northw estern Po lytechnica lUniversity Aviation Microelect ronic Center has comp leted the design of digital signal signal p rocesso r co re NDSP25, w h ich is aim ing at TM S320C25 digital signal p rocesso r of Texas Inst rument TM S320 series. By using top 2dow n design flow , NDSP25 is compat ible w ith inst ruct ion and interface t im ing of TM S320C25.Digital signal processors (DSP) is a fit for real-time digital signal processing for high-speed dedicated processors, the main variety used for real-time digital signal processing to achieve rapid algorithms. In today's digital age background, the DSP has become the communications, computer, and consumer electronics products, and other fields based device.Digital signal processors and digital signal processing is inseparably, we usually say "DSP" can also mean the digital signal processing (Digital Signal Processing), is that in this digital signal processors Lane. Digital signal processing is a cover many disciplines applied to many areas and disciplines, refers to the use of computers or specialized processing equipment, the signals in digital form for the collection, conversion, recovery, valuation, enhancement, compression, identification, processing, the signals are compliant form. Digital signal processors for digital signal processing devices, it is accompanied by a digital signal processing to produce. DSP development process is broadly divided into three phases : the 20th century to the 1970s theory that the 1980s and 1990s for the development of products. Before the emergence of the digital signal processing in the DSP can only rely on microprocessors (MPU) to complete. However, the advantage of lower high-speed real-time processing can not meet the requirements. Therefore, until the 1970s, a talent made based DSP theory and algorithms. With LSI technology development in 1982 was the first recipient of the world gave birth to the DSP chip. Years later, the second generation based on CMOS工艺DSP chips have emerged. The late 1980s, the advent of the third generation of DSP chips. DSP is the fastest-growing 1990s, there have been four successive five-generation and the generation DSP devices. After 20 years of development, the application of DSP products has been extended to people's learning, work and all aspects of life and gradually become electronics products determinants.中文翻译数字滤波器的仿真与实现随着信息时代和数字世界的到来，数字信号处理已成为当今一门极其重要的学科和技术领域。

Chapter 1 Signal Processing 信号处理classification 分类variable 变量vector 矢量scalar 标量multichannel 多通道multidimensional 多维的，多面的amplitude 幅度waveform 波形continuous-time 连续时间discrete-time 离散时间analog signal 模拟信号digital signal 数字信号normalize 使恢复正常deterministic signal 确定信号random signal 随机信号sample 抽样numerical 数字的quantized 量子化的(数字转化)time-domain 时域frequency-domain 频域elementary 基本的implement 实现amplification 放大scaling 加权delay 延时addition 相加gain 增益attenuation 衰减advance 超前product 乘积integration 积分differentiation 微分filter 滤波器lowpass filter 低通滤波器highpass filter 高通滤波器bandpass filter 带通滤波器bandstop filter 带阻滤波器block 屏蔽passband 通带stopband 阻带quantized boxcar signal 量化阶梯信号linear 线性time-invariant 时不变cutoff-frequency 截止频率Chapter 2algorithm 算法horizontal 水平面vertical 垂直面consecutive samples 相邻样本sampling interval 抽样间隔sampling period 抽样周期sampling frequency 抽样频率real/complex sequence 实数/虚数序列conjugate 共轭analog-to-digital converter 模数转换器sample-and-hold circuit 采样保持电路equivalent 等效的infinite/finite 无限的/有限的finite/infinite-length 有限/无限长finite-extent 有限范围finite-duration 有限时宽causal/anticausal sequence 因果序列/非因果序列reversal 反转even/odd sequence 偶/奇序列conjugate-symmetric/ conjugate-antisymmetric 共轭对称/共轭非对称periodic/aperiodic 周期性的/非周期性的energy signal 能量信号power signal 功率信号average power 平均功率appending with zeros 补零bounded 有界的bounded-input,bounded-output 有界输入有界输出(BIBO)left-sided/right-sided/two-sided sequence 左边/右边/双边序列time-shifting operation 时移delaying operation 延时运算advancing operation 超前运算unit delay 单位延时time-reversal operation 时间反转运算folding operation 折叠运算absolutely summable 绝对可和square-summable 平方可和N-periodic extension N倍周期延拓unit sample sequence 单位抽样序列unit step sequence 单位阶跃序列exponential sequence 指数序列complex exponential sequence 复指数序列discrete-time impulse 离散时间冲激in-phase component 同相分量quadrature component 正交分量real sinusoidal sequence 实正弦序列sinusoidal envelope 正弦包络angular frequency 角频率decomposition 分解phase 相位radian 弧度exponential sequence 指数序列fundamental period 基本周期arbitrary sequence 任意序列Shift-Invariant System 时不变系统Impulse Response 冲激响应Step Response 阶跃响应Linear system 线性系统Stable system 稳定系统commutative 交换律associative 结合律distributive 分配率Superposition 叠加accumulator 累加convolution 卷积property 性质cascade connection 级联parallel connection 并联constant 常数coefficient 系数precisely 精确地Chapter 3Discrete-Time-Fourier Transform 离散时间傅里叶变换Fourier integral 傅里叶积分Finite discontinuities 有限个不连续点spectrum 谱magnitude/phase spectrum 幅度/相位谱finite interval 有限区间absolutely integrable 绝对可积Energy Density Spectrum 能量密度谱Parseval’s relation 帕斯瓦尔定理Principal value 主值Frequency response 频率响应magnitude/phase response 幅度/相位响应gain/attenuation/loss function 增益/衰减/损耗函数band-limited 带限bandwidth 带宽integer 整数periodic impulse train 周期脉冲序列Frequency-Shifting 频移Modulation 调制eigenfunctions 特征值digital filer 数字滤波器Chapter 4Digital Processing of Continuous-Time Signals 连续时间信号的数字化处理aliasing 混叠anti-aliasing 反混叠reconstruction 重建sampling process 抽样过程Mathematical representation 数学表示ideal sampling model 理想抽样模型folding frequency 折叠频率recovery 恢复oversampling 过抽样undersampling 欠抽样critical sampling 临界抽样aliasing distortion 混叠失真passband 通带stopband 阻带passband edge frequency 通带截止频率stopband edge frequency 阻带截止频率Chapter 5Finite-Length Discrete Transforms 有限长离散变换Discrete Fourier transform 离散傅里叶变换Basis sequences 基本序列Inverse discrete Fourier transform 离散傅里叶逆变换frequency samples 频率样本circular Shift 圆周（循环）移位circular time-shifting operation 圆周时移运算circular frequency-shifting operation 圆周频移运算circular time-reversal operation 圆周时间反转运算modulo operation 模运算circular convolution 圆周（循环）卷积N-point circular convolution N点圆周（循环）卷积circulant matrix 圆周矩阵Chapter 6z-Transform Z变换unit circle 单位圆region of convergence（ROC）收敛域Rational z-transform 有理z变换Polynomial 多项式zero point 零点pole point 极点Inverse z-Transform z反变换Partial-Fraction Expansion 部分分式展开法residue 留数transfer function 传输函数system function 系统函数Chapter 8Digital Filter Structures 数字滤波器的结构IIR: Infinite Impulse Response 无限冲激响应FIR: Finite Impulse Response 有限冲激响应Block Diagram Representation 方框图表示Basic Building Blocks 基本结构单元Analysis of Block Diagrams 方框图的分析Delay-Free Loop 无延时回路Signal Flow-Graph 信号流图node 节点branch 支路addition 加法器multiplication 乘法器(增益)unit delay 单位延时Equivalent Structures 等效结构transpose operation 转置运算direct form 直接型cascade realizations 级联型parallel realizations 并联型linear-phase FIR structures 线性相位FIR滤波器结构allpass filter 全通滤波器Chapter 9IIR Digital Filter Design IIR数字滤波器设计Digital Filter Specifications 数字滤波器指标passband 通带stopband 阻带transition band 过渡带passband edge frequency 通带截止频率stopband edge frequency 阻带截止频率peak ripple values 峰波纹值peak passband ripple 峰值通带波纹minimum stopband attenuation 最小阻带衰减maximum passband attenuation 最大通带衰减selection of the Filter Type 滤波器类型的选择First-Order Butterworth lowpass filter 一阶巴特沃斯低通滤波器magnitude-squared response 幅度平方函数Scaling the Digital Transfer Function 缩放数字传输函数Bilinear Transformation method 双线性变换法Frequency warping 频率畸变Spectral Transformation 谱变换Chapter 10FIR Digital Filter Design FIR数字滤波器设计filter order 滤波器阶数window-based method 窗函数法lowpass filter 低通滤波器highpass filter 高通滤波器bandpass filter 带通滤波器bandstop filter 带阻滤波器differentiator 差分器Gibbs phenomenon 吉布斯效应rectangular window 矩形窗fixed window function 固定窗函数main lobe width 主瓣宽度relative sidelobe level 相对旁瓣级minimum-phase 最小相位Chapter 11DFT Algorithm Implementation DSP算法实现computation 计算fast Fourier transform(FFT) algorithms 快速傅里叶变换算法complex multiplications 复乘complex additions 复加Decimation-in-Time(DIT) FFT Algorithm 按时间抽取FFT算法butterfly computation 蝶形运算decomposition 分解in-place computation 同址计算(原位计算)twiddle factor 旋转因子bit-reversed order 倒位序Decimation-in-Frequency(DIF) FFT Algorithm 按频率抽取FFT算法Inverse DFT Computation 离散傅里叶逆变换计算。

数字信号处理词汇集1 章系统：system 信号：signal 模拟信号： analog signal 数字信号： digital signal 频谱： spectrum模/数转换： analog-to-digital conversion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 2 章anti-imaging filter 抗镜像滤波器 sampling interval 采样间隔anti-aliasing filter 抗混叠滤波器=sampling period 采样周期sampling frequency 采样频率=sampling rate 采样速率sampling theorem 采样定理 N yquistsam pling 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3 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 4 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m oving average filter 滑动平均滤波器 step response 阶跃响应5 章卷积： convolution 差分方程： difference equation 滑动平均滤波器： moving average filter脉冲响应： impulse response 镜像： mirror image边界效应： boundary effect输入序列： input sequence暂态效应： transient effect 稳态： steady state锐变： shape transition低通特征:low pass characteristic卷积表： convolution table6 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7 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 frequency8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9 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 10 章infinite impulse response filter(IIR) 无限脉冲响应滤波器bilinear transformation 双线性变换prewarping equation Butterworth filter 预扭曲方程巴特沃斯滤波器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。

DIGITAL SIGNAL PROCESSING TERMINOLOGY1/f noise: A type of random noise that increases in amplitude at lower frequencies. It is widely observable in physical systems, but not well understood. See white noise for comparison.-3dB cutoff frequency: The division between a filter's passband and transition band. Defined as the frequency where the frequency response is reduced to -3dB (0.707 in amplitude)."A" law: Companding standard used in Europe. Allows digital voice signals to be represented with only 8 bits instead of 12 bits by making the quantization levels unequal. See mu law for comparison.AC: Alternating Current. Electrical term for the portion of a signal that fluctuates around the average (DC) value.Accuracy: The error in a measurement (or a prediction) that is repeatable from trial to trial. Accuracy is limited by systematic (repeatable) errors. See precision for comparison. Additivity: A mathematical property that is necessary for linear systems. If input a produces output p, and if input b produces output q, then an input of a+b produces an output of p+q.Aliasing: The process where a sinusoid changes from one frequency to another as a result of sampling or other nonlinear action. Usually results in a loss of the signal's information. Amplitude modulation: Method used in radio communication for combining an information carrying signal (such as audio) with a carrier wave. Usually carried out by multiplying the two signals.Analysis: The forward Fourier transform; calculating the frequency domain from the time domain. See synthesis for comparison.Antialias filter: Low-pass analog filter placed before an analog-to-digital converter. Removes frequencies above one-half the sampling rate that would alias during conversion.ASCII: A method of representing letters and numbers in binary form. Each character is assigned a number between 0 and 127. Very widely used in computers and communication.Aspect ratio: The ratio of an image's width to its height. Standard television has an aspect ratio of 4:3, while motion pictures have an aspect ratio of 16:9.Assembly: Low-level programming language that directly manipulates the registers and internal hardware of a microprocessor. See high-level language for comparison. Associative property of convolution: Written as: . This is (a[n]t b[n] )t c[n] ’a[n]t(b[n]t c[n]) important in signal processing because it describes how cascaded stages behave.Autocorrelation: A signal correlated with itself. Useful because the Fourier transform of the autocorrelation is the power spectrum of the original signal.Backprojection: A technique used in computed tomography for reconstructing an image from its views. Results in poor image quality unless used with a more advanced method. BASIC: A high-level programming language known for its simplicity, but also for its many weaknesses. Most of the programs in this book are in BASIC.Basilar membrane: Small organ in the ear that acts as a spectrum analyzer. It allows different fibers in the cochlear nerve to be stimulated by different frequencies.Basis functions: The set of waveforms that a decomposition uses. For instance, the basis functions for the Fourier decomposition are unity amplitude sine and cosine waves. The Scientist and Engineer's Guide to Digital Signal Processing 632Bessel filter: Analog filter optimized for linear phase. It has almost no overshoot in the step response and similar rising and falling edges. Used to smooth time domain encoded signals.Bidirectional filtering: Recursive method used to produce a zero phase filter. The signal is first filtered from left-to-right, then the intermediate signal is filtered from right-to-left. Bilinear transform: Technique used to map the s-plane into the z-plane. Allows analog filters to be converted into equivalent digital filters.Binning: Method of forming a histogram when the data (or signal) has numerous quantization levels, such as in floating point numbers.Biquad: An analog or digital system with two poles and up to two zeros. Often cascaded to create a more sophisticated filter design.Bit reversal sorting: Algorithm used in the FFT to achieve an interlaced decomposition of the signal. Carried out by counting in binary with the bits flipped left-for-right. Blackman window: A smooth curve used in the design of filters and spectral analysis, calculated from : , 0.42& 0.5cos(2B n/M)% 0.08cos(4B n/M) where n runs from 0 to M. Brightness: The overall lightness or darkness of an image. See contrast for comparison. Butterfly: The basic computation used in the FFT. Changes two complex numbers into two other complex numbers.Butterworth filter: Separates one band of frequencies from another; fastest roll-off while keeping the passband flat; can be analog or digital. Also called a maximally flat filter.C: Common programming language used in science, engineering and DSP. Also comes in the more advanced C++.Carrier wave: Term used in amplitude modulation of radio signals. Refers to the high frequency sine wave that is combined with a lower frequency information carrying signal.Cascade: A combination of two or more stages where the output of one stage becomes the input for the next.Causal signal: Any signal that has a value of zero for all negative numbered samples. Causal system: A system that has a zero output until a nonzero value has appeared on its input (i.e., the input causes the output). The impulse response of a causal system is a causal signal.Central Limit Theorem: Important theorem in statistics. In one form: a sum of many random numbers will have a Gaussian pdf, regardless of the pdf of the individual random numbers.Cepstrum: A rearrangement of "spectrum." Used in homomorphic processing to describe the spectrum when the time and frequency domains are switched.Charge coupled device (CCD): The light sensor in electronic cameras. Formed from athin sheet of silicon containing a two-dimensional array of light sensitive regions called wells.Chebyshev filter: Used for separating one band of frequencies from another. Achieves a faster roll-off than the Butterworth by allowing ripple in the passband. Can be analog or digital.Chirp system: Used in radar and sonar. An impulse is converted into a longer duration signal before transmission, and compressed back into an impulse after reception. Circular buffer: Method of data storage used in real time processing; each newly acquired sample replaces the oldest sample in memory.Circular convolution: Aliasing that can occur in the time domain when frequency domain signals are multiplied. Each period in the time domain overflows into adjacent periods.Circularity: The appearance that the end of a signal is connected to its beginning. This arises when considering only a single period of a periodic signal.Classifiers: A parameter extracted from and representing a larger data set. For example: size of a region, amplitude of a peak, sharpness of an edge, etc. Used in pattern recognition.Closing: A morphological operation defined as an erosion operation followed by a dilation operation.Cochlea: Organ in the ear where sound in converted into a neural signal.Cochlear nerve: Nerve that transmits audio information from the ear to the brain. Coefficient-of-variation (CV): Common way of stating the variation (noise) in data. Defined as: 100% × standard deviation / mean.Commutative property of convolution: Written as: . a[n]t b[n] ’ b[n]t a[n] Companding: An "s" shaped nonlinearity allows voice signals to be digitized using only 8 bits instead of 12 bits. Europe uses "A" law, while the United States uses the mu law version.Complex conjugation: Changing the sign of the imaginary part of a complex number. Often denoted by a star placed next to the variable. Example: if , then . A ’ 3% 2j A( ’ 3& 2 jComplex DFT: The discrete Fourier transform using complex numbers. A more complicated and powerful technique than the real DFT.Complex exponential: A complex number of the form: . They are useful in engineering and e a % bj science because Euler's relation allows them to represent sinusoids. Complex Fourier transform: Any of the four members of the Fourier transform family written using complex numbers. See real Fourier transform for comparison.Complex numbers: The real numbers (used in everyday math) plus the imaginary numbers (numbers containing the term j, where ). j ’ &1 Example: . 3% 2jComplex plane: A graphical interpretation of complex numbers, with the real part on the x-axis and the imaginary part on the y-axis. This is analogous to the number line used with ordinary numbers.Composite video: An analog television signal that contains synchronization pulses to separate the fields or frames.Computed tomography (CT): A method used to reconstruct an image of the interior of an object from its x-ray projections. Widely used in medicine; one of the earliest applications of DSP. Old name: CAT scanner.Continuous signal: A signal formed from continuous (as opposed to discrete) variables. Example: a voltage that varies with time. Often used interchangeably with analog signal. Contrast: The difference between the bright-ness of an object and the brightness of the background. See brightness for comparison.Converge: Term used in iterative methods to indicate that progress is being made toward a solution ("The algorithm is converging") or that a solution has been reached ("The algorithm has converged").Convolution integral: Mathematical equation that defines convolution in continuous systems; analogous to the convolution sum for discrete systems.Convolution kernel: The impulse response of a filter implemented by convolution. Also known as the filter kernel and the kernel.Convolution sum: Mathematical equation defining convolution for discrete systems. Cooley and Tukey: J.W. Cooley and J.W. Tukey, given credit for bringing the FFT to the world in a paper they published in 1965.Correlation: Mathematical operation carried out the same as convolution, except aleft-for-right flip of one signal. This is an optimal way to detect a known waveform in a signal.Cross-correlation: The signal formed when one signal is correlated with another signal. Peaks in this signal indicate a similarity between the original signals. See also autocorrelation.Cutoff frequency: In analog and digital filters, the frequency separating the passband from the transition band. Often measured where the amplitude is reduced to 0.707 (-3dB). CVSD: Continuously Variable Slope Delta modulation, a technique used to convert a voice signal into a continuous binary stream.DC: Direct Current. Electrical term for the portion of the signal that does not change with time; the average value or mean. See AC for comparison.Decibel SPL: Sound Pressure Level. Log scale used to express the intensity of a sound wave: 0 dB SPL is barely detectable; 60 dB SPL is normal speech, and 140 dB SPL causes ear damage.Decimation: Reducing the sampling rate of a digitized signal. Generally involveslow-pass filtering followed by discarding samples. See interpolation for comparison. Decomposition: The process of breaking a signal into two or more additive components. Often refers specifically to the forward Fourier transform, The Scientist and Engineer's Guide to Digital Signal Processing 634 breaking a signal into sinusoids. Deconvolution: The inverse operation of convolution: if , find given x[n]t h[n] ’ y[n] x[n] only . Deconvolution is usually h[n] and y[n] carried out by dividing the frequency spectra.Delta encoding: A broad term referring to techniques that store data as the difference between adjacent samples. Used in ADC, data compression and many other applications.Delta function: A normalized impulse. The discrete delta function is a signal composed of all zeros, except the sample at zero that has a value of one. The continuous delta function is similar, but more abstract.Delta-sigma: Analog-to-digital conversion method popular in voice and music processing. Uses a very high sampling rate with only a single bit per sample, followed by decimation.Dependent variable: In a signal, the dependent variable depends on the value of the independent variable. Example: when a voltage changes over time, time is the independent variable and voltage is the dependent variable.Difference equation: Equation relating the past and present samples of the output signal with past and present samples of the input signal. Also called a recursion equation. Dilation: A morphological operation. When applied to binary images, dilation makes the objects larger and can combine disconnected objects into a single object.Discrete cosine transform (DCT): A relative of the Fourier transform. Decomposes a signal into cosine waves. Used in data compression.Discrete derivative: An operation for discrete signals that is analogous to the derivative for continuous signals. A better name is the first difference.Discrete Fourier transform (DFT): Member of the Fourier transform family dealing with time domain signals that are discrete and periodic.Discrete integral: Operation on discrete signals that is analogous to the integral for continuous signals. A better name is the running sum.Discrete signal: A signal that uses quantized variables, such as a digitized signal residing in a computer.Discrete time Fourier transform (DTFT): Member of the Fourier transform family dealing with time domain signals that are discrete and aperiodicDithering: Adding noise to an analog signal before analog-to-digital conversion to prevent the digitized signal from becoming "stuck" on one value.Domain: The independent variable of a signal. For example, a voltage that varies with time is in the time domain. Other common domains are the spatial domain (such as images) and the frequency domain (the output of the Fourier transform).Double precision: A standard for floating point notation that used 64 bits to represent each number. See single precision for comparison.DSP microprocessor: A type of microprocessor designed for rapid math calculations. Often has a pipeline and/or Harvard architecture. Also called a RISC.Dynamic range: The largest amplitude a system can deal with divided by the inherent noise of the system. Also used to indicate the number of bits used in an ADC. Can also be used with parameters other than amplitude; see frequency dynamic range.Edge enhancement: Any image processing algorithm that makes the edges more obvious. Also called a sharpening operation.Edge response: In image processing, the output of a system when the input is an edge. The sharpness of the edge response is often used as a measure of the resolution of the system.Elliptic filter: Used to separate one band of frequencies from another. Achieves a fastroll-off by allowing ripple in the passband and the stopband. Can be used in both analog and digital designs.End effects: The poorly behaved ends of a filtered signal resulting from the filter kernel not being completely immersed in the input signal.Erosion: A morphological operation. When applied to binary images, erosion makes the objects smaller and can break objects into two or more pieces.Euler's relation: The most important equation in complex math, relating sine and cosine waves with complex exponentials.Even/odd decomposition: A way of breaking a signal into two other signals, one having even symmetry, and the other having odd symmetry.Even order filter: An analog or digital filter having an even number of poles.False-negative: One of four possible outcomes of a target detection trial. The target is present, but incorrectly indicated to be not present.False-positive: One of four possible outcomes of a target detection trial. The target is not present, but incorrectly indicated to be present.Fast Fourier transform (FFT): An efficient algorithm for calculating the discrete Fourier transform (DFT). Reduces the execution time by hundreds in some cases.FFT convolution: A method of convolving signals by multiplying their frequency spectra. So named because the FFT is used to efficiently move between the time and frequency domains.Field: Interlaced television displays the even lines of each frame (image) followed by the odd lines. The even lines are called the even field, and the odd lines the odd field.Filter kernel: The impulse response of a filter implemented by convolution. Also known as the convolution kernel and the kernel.Filtered backprojection: A technique used in computed tomography for reconstructing an image from its views. The views are filtered and then backprojected.Finite impulse response (FIR): An impulse response that has a finite number of nonzero values. Often used to indicate that a filter is carried out by using convolution, rather than recursion.First difference: An operation for discrete signals that mimics the first derivative for continuous signals; also called the discrete derivative.Fixed point: One of two common ways that computers store numbers; usually used to store integers. See floating point for comparison.Flat-top window: A window used in spectral analysis; provides an accurate measurement of the amplitudes of the spectral components. The windowed-sinc filter kernel can be used.Floating point: One of the two common ways that computers store numbers. Floating point uses a form of scientific notation, where a mantissa is raised to an exponent. See fixed point for comparison.Forward transform: The analysis equation of the Fourier transform, calculating the frequency domain from the time domain. See inverse transform for comparison.Fourier reconstruction: One of the methods used in computed tomography to calculatean image from its views.Fourier series: The member of the Fourier transform family that deals with time domain signals that are continuous and periodic.Fourier transform: A family of mathematical techniques based on decomposing signals into sinusoids. In the complex version, signals are decomposed into complex exponentials.Fourier transform pair: Waveforms in the time and frequency domains that correspond to each other. For example, the rectangular pulse and the sinc function.Fovea: A small region in the retina of the eye that is optimized for high-resolution vision. Frame: An individual image in a television signal. The NTSC television standard uses 30 frames per second.Frame grabber: A analog-to-digital converter used to digitize and store a frame (image) from a television signal.Frequency domain: A signal having frequency as the independent variable. The output of the Fourier transform.Frequency domain aliasing: Aliasing that occurs occurring in the frequency domain in response to an action taken in the time domain. Aliasing during sampling is an example. Frequency domain convolution: Convolution carried out by multiplying the frequency spectra of the signals.Frequency domain encoding: One of two main ways that information can be encoded in a signal. The information is contained in the amplitude, frequency, and phase of the signal's component sinusoids. Audio signals are the best example. See time domain encoding for comparison.Frequency domain multiplexing: A method of combining signals for simultaneous transmission by shifting them to different parts of the frequency spectrum.Frequency dynamic range: The ratio of the largest to the lowest frequency a system can deal with. Analog systems usually have a much larger frequency dynamic range than digital systems.Frequency resolution: The ability to distinguish or separate closely spaced frequencies. Frequency response: The magnitude and phase changes that sinusoids experience when passing through a linear system. Usually expressed as a function of frequency. Often found by taking the Fourier transform of the impulse response.Fricative: Human speech sound that originates as random noise from air turbulence, such as: s, f, sh, z, v and th. See voiced for comparison.Full-width-at-half-maximum (FWHM): A common way of measuring the width of a peak in a signal. The width of the peak is measured at one-half of the peak's maximum amplitude.Fundamental frequency: The frequency that a periodic waveform repeats itself. See harmonic for comparison.Gamma curve: The mathematical function or look-up table relating a stored pixel value and the brightness it appears in a displayed image. Also called a grayscale transform. Gaussian: A bell shaped curve of the general form: The Gaussian has many unique e x 2 properties. Also called the normal distribution.Gibbs effect: When a signal is truncated in one domain, ringing and overshoot appear at edges and corners in the other domain.GIF: A common image file format using LZW (lossless) compression. Widely used on the world wide web for graphics. See TIFF and JPEG for comparison.Grayscale: image A digital image where each pixel is displayed in shades of gray between black and white; also called a black and white image.Grayscale stretch: Greatly increasing the contrast of a digital image to allow the detailed examination of a small range of quantization levels. Quantization levels outside of this range are displayed as saturated black or white.Grayscale transform: The conversion function between a stored pixel value and the brightness that appears in a displayed image. Also called a gamma curve.Halftone: A common method of printing images on paper. Shades of gray are created by various patterns of small black dots. Color halftones use dots of red, green and blue. Hamming window: A smooth curve used in the design of filters and spectral analysis, calculated from: , where n runs from 0.54 & 0.46cos(2B n/M) 0 to M.Harmonics: The frequency components of a periodic signal, always consisting of integer multiples of the fundamental frequency. The fundamental is the first harmonic, twice this frequency is the second harmonic, etc.Harvard Architecture: Internal computer layout where the program and data reside in separate memories accessed through separate busses; common in microprocessors used for DSP. See Von Neumann Architecture for comparison.High fidelity: High quality music reproduction, such as provided by CD players.High-level language: Programming languages such as C, BASIC and FORTRAN.High-speed convolution: Another name for FFT convolution.Hilbert transformer: A system having the frequency response: Mag = 1, Phase = 90E, for all frequencies. Used in communications systems for modulation. Can be analog or digital.Histogram equalization: Processing an image by using the integrated histogram of the image as the grayscale transform. Works by giving large areas of the image higher contrast than the small areas.Histogram: Displays the distribution of values in a signal. The x-axis show the possible values the samples can take on; the y-axis indicates the number of samples having each value.Homogeneity: A mathematical property of all linear systems. If an input produces an x[n] output of , then an input produces an y[n] kx[n] output of , for any constant k. ky[n] Homomorphic: DSP technique for separating signals combined in a nonlinear way, such as by multiplication or convolution. The nonlinear problem is converted to a linear oneby an appropriate transform.Huffman encoding: Data compression method that assigns frequently encountered characters fewer bits than seldom used characters.Hyperspace: Term used in target detection and neural network analysis. One parameter can be graphically interpreted as a line, two parameters a plane, three parameters a space, and more than three parameters a hyperspace.Imaginary part: The portion of a complex number that has a j term, such as 2 in . In 3% 2j the real Fourier transform, the imaginary part also refers to the portion of the frequency domain that holds the amplitudes of the sine waves, even though j terms are not used.Impulse: A signal composed of all zeros except for a very brief pulse. For discrete signals, the pulse consists of a single nonzero sample. For continuous signals, the width of the pulse must be much shorter than the inherent response of any system the signal is used with.Impulse decomposition: Breaking an N point signal into N signals, each containing a single sample from the original signal, with all the other samples being zero. This is the basis of convolution.Impulse response: The output of a system when the input is a normalized impulse (a delta function).Impulse train: A signal consisting of a series of equally spaced impulses. Independent variable: In a signal, the dependent variable depends on the value of the independent variable. Example: when a voltage changes over time, time is the independent variable and voltage is the dependent variable.Infinite impulse response (IIR): An impulse response that has an infinite number of nonzero values, such as a decaying exponential. Often used to indicate that a filter is carried out by using recursion, rather than convolution.Integers: Whole numbers: 0, 1, 2,Also refers to numbers stored in fixed point notation. See floating point for comparison.Interlaced decomposition: Breaking a signal into its even numbered and odd numbered samples. Used in the FFT.Interlaced video: A video signal that displays the even lines of each image followed by the odd lines. Used in television; developed to reduce flicker.Interpolation: Increasing the sampling rate of a digitized signal. Generally done by placing zeros between the original samples and using a low-pass filter. See decimation for comparison.Inverse transform: The synthesis equation of the Fourier transform, calculating the time domain from the frequency domain. See forward transform for comparison.Iterative: Method of finding a solution by gradually adjusting the variables in the right direction until convergence is achieved. Used in CT reconstruction and neural networks. JPEG: A common image file format using transform (lossy) compression. Widely used on the world wide web for graphics. See GIF and TIFF for comparison.Kernel: The impulse response of a filter implemented by convolution. Also known as the convolution kernel and the filter kernel.Laplace transform: Mathematical method of analyzing systems controlled by differential equations. A main tool in the design of electric circuits, such as analog filters. Changes a signal in the time domain into the s-domainLearning algorithm: The procedure used to find a set of neural network weights based on examples of how the network should operate.Line pair: Imaging term for cycle. For example, 5 cycles per mm is the same as 5 linepairs per mm.Line pair gauge: A device used to measure the resolution of an imaging system. Contains a series of light and dark lines that move closer together at one end.Line spread function (LSF): The response of an imaging system to a thin line in the input image.Linear phase: A system with a phase that is a straight line. Usually important because it means the impulse response has left-to-right symmetry, making rising edges in the output signal look the same as falling edges. See also zero phase.Linear system: By definition, a system that has the properties of additivity and homogeneity.Lossless compression: Data compression technique that exactly reconstructs the original data, such as LZW compression.Lossy compression: Data compression methods that only reconstruct an approximation to the original data. This allows higher compression ratios to be achieved. JPEG is an example.Matched filtering: Method used to determine where, or if, a know pattern occurs in a signal. Matched filtering is based on correlation, but implemented by convolution. Mathematical equivalence: A way of using complex numbers to represent real problems. Based on Euler's relation equating sinusoids with complex exponentials. See substitution for comparison.Mean: The average value of a signal or other group of data.Memoryless: Systems where the current value of the output depends only on the current value of the input, and not past values.MFLOPS: Million-Floating-Point-Operations- Per-Second; a common way of expressing computer speed. See MIPS for comparison.MIPS: Million-Instructions-Per-Second; a common way of expressing computer speed. See MFLOPS for comparison.Mixed signal: Integrated circuits that contain both analog and digital electronics, such as an ADC placed on a Digital Signal Processor.Modulation transfer function (MTF): Imaging jargon for the frequency response. Morphing: Gradually warping an image from one form to another. Used for special effects, such as a man turning into a werewolf.Morphological: Usually refers to simple nonlinear operations performed on binary images, such as erosion and dilation.Moving average filter: Each sample in the output signal is the average of many adjacent samples in the input signal. Can be carried out by convolution or recursion.MPEG: Compression standard for video, such as digital television.Mu law: Companding standard used in the United States. Allows digital voice signals to be represented with only 8 bits instead of 12 bits by making the quantization levels unequal. See "A" law for comparison.Multiplexing: Combining two or move signals together for transmission. This can be carried out in many different ways.。