数字信号专业英语翻译

1、电子与通信专业英语DigitalSignalProcessing（英文翻译）姓名：赵 豪 班级：信工 122 学号：2012020217DigitalSignalProcessing1、IntroductionDigitalsignalprocessing(DSP)isconcernedwiththerepresentationofthesignalsbyasequenceofnumbersorsymbolsandtheprocessingofthesesignals.Digitalsignalprocessingandanalogsignalprocessingaresubfieldsofs

2、ignalprocessing.DSPincludessubfieldslikeaudioandspeechsignalprocessing,sonarandradarsignalprocessing,sensorarrayprocessing,spectralestimation,statisticalsignalprocessing,digitalimageprocessing,signalprocessingforcommunications,biomedicalsignalprocessing,seismicdataprocessing,etc.SincethegoalofDSPisu

3、suallytomeasureorfiltercontinuousreal-worldanalogsignals,thefirststepisusuallytoconvertthesignalfromananalogtoadigitalform,byusingananalogtodigitalconverter.Often,therequiredoutputsignalisanotheranalogoutputsignal,whichrequiresadigitaltoanalogconverter.Evenifthisprocessismorecomplexthananalogprocess

4、ingandhasadiscretevaluerange,thestabilityofdigitalsignalprocessingthankstoerrordetectionandcorrectionandbeinglessvulnerabletonoisemakesitadvantageousoveranalogsignalprocessingformany,thoughnotall,applications.DSPalgorithmshavelongbeenrunonstandardcomputers,onspecializedprocessorscalleddigitalsignalp

5、rocessors(DSP)s,oronpurpose-builthardwaresuchasapplication-specificintegratedcircuit(ASICs).Todaythereareadditionaltechnologiesusedfordigitalsignalprocessingincludingmorepowerfulgeneralpurposemicroprocessors,field-programmablegatearrays(FPGAs),digitalsignalcontrollers(mostlyforindustrialapplications

6、suchasmotorcontrol),andstreamprocessors,amongothers.InDSP,engineersusuallystudydigitalsignalsinoneofthefollowingdomains:timedomain(one-dimensionalsignals),spatialdomain(multidimensionalsignals),frequencydomain,autocorrelationdomain,andwaveletdomains.Theychoosethedomaininwhichtoprocessasignalbymaking

7、aninformedguess(orbytryingdifferentpossibilities)astowhichdomainbestrepresentstheessentialcharacteristicsofthesignal.Asequenceofsamplesfromameasuringdeviceproducesatimeorspatialdomainrepresentation,whereasadiscreteFouriertransformproducesthefrequencydomaininformationthatisthefrequencyspectrum.Autoco

8、rrelationisdefinedasthecross-correlationofthesignalwithitselfovervaryingintervalsoftimeorspace.2、SignalSamplingWiththeincreasinguseofcomputerstheusageofandneedfordigitalsignalprocessinghasincreased.Inordertouseananalogsignalonacomputeritmustbedigitizedwithananalogtodigitalconverter(ADC).Samplingisus

9、uallycarriedoutintwostages,discretizationandquantization.Inthediscretizationstage,thespaceofsignalsispartitionedintoequivalenceclassesandquantizationiscarriedoutbyreplacethesignalwithrepresentativesignalvaluesareapproximatedbyvaluesfromafiniteset.TheNyquist-Shannonsamplingtheoremstatesthatasignalcan

10、beexactlyreconstructedfromitssamplesifthesamplesifthesamplingfrequencyisgreaterthantwicethehighestfrequencyofthesignal.Inpractice,thesamplingfrequencyisoftensignificantlymorethantwicetherequiredbandwidth.Adigitaltoanalogconverter(DAC)isusedtoconvertthedigitalsignalbacktoanalogsignal.Theuseofadigital

11、computerisakeyingredientindigitalcontrolsystems.3、TimeandSpaceDomainsThemostcommonprocessingapproachinthetimeorspacedomainisenhancementoftheinputsignalthroughamethodcalledfiltering.Filteringgenerallyconsistsofsometransformationofanumberofsurroundingsamplesaroundthecurrentsampleoftheinputoroutputsign

12、al.Therearevariouswaystocharacterizefilters,forexample:A“linear”filterisalineartransformationofinputsamples;otherfiltersare“non-linear.”Linearfilterssatisfythesuperpositioncondition,i.e.ifaninputisaweightedlinearcombinationofdifferentsignals,theoutputisanequallyweightedlinearcombinationofthecorrespo

13、ndingoutputsignals.A“causal”filterusesonlyprevioussamplesoftheinputoroutputsignals;whilea“non-causal”filterusesfutureinputsamples.Anon-causalfiltercanusuallybechangedintoacausalfilterbyaddingadelaytoit.A“time-invariant”filterhasconstantpropertiesovertime;otherfilterssuchasadaptivefilterschangeintime

14、.Somefiltersare“stable”,othersare“unstable”.Astablefilterproducesanoutputthatconvergestoaconstantvaluewithtime,orremainsboundedwithinafiniteinterval.Anconvergestoaconstantvaluewithtime,orremainsboundedwithinafiniteinterval.Anunstablefiltercanproduceanoutputthatgrowswithoutbounds,withboundedorevenzer

15、oinput.A“FiniteImpulseResponse”(FIR)filterusesonlytheinputsignal,whilean“InfiniteImpulseResponse”filter(IIR)usesboththeinputsignalandprevioussamplesoftheoutputsignal.FIRfiltersarealwaysstable,whileIIRfiltersmaybeunstable.MostfilterscanbedescribedinZ-domain(asupersetofthefrequencydomain)bytheirtransf

16、erfunctions.Afiltermayalsobedescribedasadifferenceequation,acollectionofzeroesandpolesor,ifitisanFIRfilter,animpulseresponseorstepresponse.TheoutputofanFIRfiltertoanygiveninputmaybecalculatedbyconvolvingtheinputsignalwiththeimpulseresponse.Filterscanalsoberepresentedbyblockdiagramswhichcanthenbeused

17、toderiveasampleprocessingalgorithmtoimplementthefilterusinghardwareinstructions.4、FrequencyDomainSignalsareconvertedfromtimeorspacedomaintothefrequencydomainusuallythroughtheFouriertransform.TheFouriertransformconvertsthesignalinformationtoamagnitudeandphasecomponentofeachfrequency.OftentheFouriertr

18、ansformisconvertedtothepowerspectrum,whichisthemagnitudeofeachfrequencycomponentsquared.Themostcommonpurposeforanalysisofsignalsinthefrequencydomainisanalysisofsignalproperties.Theengineercanstudythespectrumtodeterminewhichfrequenciesarepresentintheinputsignalandwhicharemissing.Filtering,particularl

19、yinnonreal-timeworkcanalsobeachievedbyconvertingtothefrequencydomain,applyingthefilterandthenconvertingbacktothetimedomain.Thisisafast,O(nlogn)operation,andcangiveessentiallyanyfiltershapeincludingexcellentapproximationstobrickwallfilters.Therearesomecommonlyusedfrequencydomaintransformations.Forexa

20、mple,thecepstrumconvertsasignaltothefrequencydomainFouriertransform,takesthelogarithm,thenappliesanotherFouriertransform.Thisemphasizesthefrequencycomponentswithsmallermagnitudewhileretainingtheorderofmagnitudesoffrequencycomponents.Frequencydomainanalysisisalsocalledspectrumorspectralanalysis.5、 si

21、gnal processing,Signal usually need in different ways.For example, from a sensor output signal may be contaminated the redundant electrical noise.Electrode is connected to a patients chest, electrocardiogram (ecg) is measured by the heart and other muscles activity caused by small voltage variation.

22、Due to the strong effect electrical interference from the power supply, signal picked up the main is usually adopted.Processing signal filter circuit can eliminate or at least reduce unwanted part of the signal.Now, more and more, is by the DSP technology to extract the signal filter to improve the

23、quality of signal or important information, rather than the analog electronic technology.6、the development of DSPThe development of digital signal processing (DSP) in the 1960 s to large Numbers of digital computing applications using fast Fourier transform (FFT), which allows the frequency spectrum

24、 of a signal can be quickly calculated.These techniques have not been widely used at the time, because suitable computing equipment is usually only in university and other research institutions can be used.7、 the digital signal processor (DSP)In the late 1970 s and early 1980 s the introduction of m

25、icroprocessor makes DSP technology is used in the wider range.General microprocessor, such as Intel x86 family, however, is not suitable for the calculation of DSP intensive demand, with the increase of DSP importance in the 1980 s led to several major electronics manufacturers (such as Texas instru

26、ments, analog devices and MOTOROLA) to develop a digital signal processor chip, microprocessor, specifically designed for use in the operation of the digital signal processing requirements type of architecture.(note that abbreviation DSP digital signal processing (DSP) of different meanings, this wo

27、rd is used in digital signal processing, a variety of technical or digital signal processor, a special type of microprocessor chips).As a common microprocessors, DSP is one kind has its own local instruction code of programmable devices.DSP chip is able to millions of floating point operations per s

28、econd, as they are of the same type more famous universal device, faster and more powerful versions are introduced.DSP can also be embedded in a complex system chip devices, usually includes analog and digital circuit.8、the application of digital signal processorsDSP technology is widespread in mobi

29、le phones, multimedia computers, video recorders, CD players, hard disk drives and controller of the modem equipment, and will soon replace analog circuits in TV and telephone service.DSP is an important application of signal compression and decompression.Signal compression is used for digital cellu

30、lar phone, in every place of the unit let more phone is processed at the same time.DSP signal compression technology not only makes people can talk to each other, and can be installed on the computer by using the small camera make people through the monitor to see each other, and these together is t

31、he only needs to be a traditional phone line.In audio CD system, DSP technology to perform complex error detection and correction of raw data, because it is read from CD.Although some of the underlying mathematical theory of DSP technology, such as Fourier transform and Hilbert transform, the design

32、 of digital filter and signal compression, can be quite complex, and the actual implementation of these technologies needed for numerical computation is very simple, mainly including operations can be in a cheap four function calculator.A kind of structure design of the DSP chip to operate very fast

33、, deal with the sample of the hundreds of millions of every second, and provide real-time performance: that is, to a real-time signal processing, because it is sample, and then the output signal processing, such as speakers or video display.All of the DSP applications mentioned above instance, such

34、as hard disk drives and mobile phone, for real-time operation.Major electronics manufacturers have invested heavily in DSP technology.Because they now find application in mass-market products, DSP chip electronic device occupies very large proportion in the world market.Sales of billions of dollars

35、a year, and may continue to grow rapidly.DSP is mainly used of audio signal processing, audio compression, digital image processing, video compression, speech processing, speech recognition, digital communication, radar, sonar, earthquake, and biological medicine.Concrete example is in digital mobil

36、e telephone voice compression and transmission, space balanced stereo matching, amplification area, good weather forecasts, economic forecasts, seismic data processing, and analysis of industrial process control, computer generated animation film, medical image such as CAT scans and magnetic resonan

37、ce imaging (MRI), MP3compression, image processing, hi-fi speaker divider and equilibrium, and compared with electric guitar amplifier using audio effect.9、the experiment of digital signal processingDigital signal processing is often use special microprocessor, such as dsp56000 TMS320, or SHARC.Thes

38、e often processing data using the fixed point operation, although some versions can use floating-point arithmetic and more powerful.Faster application of FPGA can flow from a slow start the emergence of application processor Freescale company, traditional slower processors, such as single chip may b

39、e appropriate.数字信号处理1、介绍数字信号处理(DSP)的关心表示信号序列的数字或符号和处理这些信号。数字信号处理与模拟信号处理是信号处理的分支学科。DSP包括分支学科如音频和语音信号处理、声纳和雷达信号处理、传感器阵列处理、谱估计,统计信号处理,数字图像处理,信号处理,通信、生物医学信号处理、地震数据处理等。由于DSP的目标通常是测量或过滤连续真实世界的模拟信号,第一步通常是将信号从模拟转换成数字形式,通过使用一个模拟数字转换器。通常,所需的输出信号是另一个模拟输出信号,这就需要一个数字模拟转换器。即使这个过程比模拟加工和复杂的离散值范围,数字信号处理的稳定性由于错误检测和校正

40、和不太容易受到噪声使它优于模拟信号处理对许多人来说,虽然并不是所有的应用程序。DSP算法一直是标准的计算机上运行,在专门的处理器称为数字信号处理器(DSP),或在专用硬件如专用集成电路(asic)。今天有额外的技术用于数字信号处理包括更强大的通用微处理器,现场可编程门阵列(fpga),数字信号控制器(主要是电机控制等工业应用),和流处理器等等。在DSP,工程师通常在以下领域之一:研究数字信号时间域(一维信号),空间域(多维信号),频域,自相关域,和小波域。他们选择的域来处理信号通过一个消息灵通的猜测(或尝试不同的可能性),域最能代表信号的基本特征。一个序列样本的测量装置产生一个时间或空间域表示

41、,而离散傅里叶变换会产生频谱的频域信息。自相关是指信号的互相关与本身在不同时间间隔的时间和空间。2、信号采样随着计算机的应用越来越多地使用，对数字信号处理的需要增加了。为了在电脑上使用一个模拟信号必须数字化模拟到数字转换器(ADC)。抽样通常在两个阶段进行,离散化和量化,在离散化阶段信号的空间划分等价类和量化进行了信号替换为代表的信号值从一个有限集值来近似。Nyquist-Shannon抽样定理指出,一个信号可以准确重建的样品如果样品采样频率大于信号最高频率的两倍。在实践中,采样频率往往远远超过所需的带宽的两倍。数字模拟转换器（DAC）用于将数字信号转化到模拟信号。数字计算机的使用是数字控制系

42、统中的一个关键因素。3、时间域和空间域在时间或空间域中最常见的处理方法是对输入信号进行一种称为滤波的操作。滤波通常包括对一些周边样本的输入或输出信号电流采样进行一些改造。现在有各种不同的方法来表征的滤波器，例如：一个线性滤波器的输入样本的线性变换；其他的过滤器都是“非线性”。线性滤波器满足叠加条件，即如果一个输入不同的信号的加权线性组合，输出的是一个同样加权线性组合所对应的输出信号。“因果”滤波器只使用以前的样本的输入或输出信号；而“非因果”滤波器使用未来的输入样本。一个非因果滤波器通常可以通过增加一个延迟将它变成了一个因果滤波器。“时间不变”滤波器随着时间的推移性具有稳定特性；其他滤波器如随

43、时间变化的自适应滤波器。一些滤波器是“稳定”的，别的是“不稳定的”。一个稳定的滤波器产生的输出信号随时间收敛于一个恒定值，或在一个有限的时间间隔内是有界的。一种不稳定的滤波器可以产生一个没有增长界限的输出，甚至零输入有界。“有限脉冲响应”过滤器只使用输入信号,而一个“无限脉冲响应滤波器(IIR)使用的输入信号和之前的样本输出信号。冷杉过滤器总是稳定的,虽然IIR滤波器可能不稳定。大多数滤波器可以被描述在z域（频域的一个超集）的传递函数。如果它是一个FIR滤波器的脉冲响应和阶跃响应，滤波器也可以被描述为一个差分方程，或对零点和极点的收集。一个FIR滤波器的输出是通过对任何给定的输入与脉冲响应的卷

44、积计算得到的。滤波器也可以被用来推导出一个样品的处理算法的方块图利用硬件指令实现滤波器所代表。4、频域信号从时间或空间域转换到频率域通常通过傅里叶变换,傅里叶变换将信号转换为信息级每个频率和相位组成部分。通常转换为功率谱的傅里叶变换,这是每个频率分量的幅度的平方。在频域对信号分析的最常见的用途是信号特性分析。工程师可以研究频谱来确定哪一频率的存在于输入信号中。滤波，特别是在非实时的工作也可以被转换到频域实现，应用滤波器，然后转换回时域。这是一个快速，O（nlogn）操作，可以基本上给出任何滤波器的形状包括砖墙滤波器优良的逼近。有一些常用的频域转换。例如,倒频谱的信号转换为频率域傅里叶变换,将对数,然后应用另一个傅里叶变换,这强调了规模较小的频率成分,同时保留的震级components.Frequency频率域分析也称为光谱和光谱分析。5、信号处理信号通常需要以不同的方式进行处理。例如，从一个传感器的输出信号可能被污染的多余电“噪音”。电极连接到一个病人的胸部时，心电图是测量由心脏和其他肌肉的活动引起的微小的电压变化。由于电的干扰从电源的强烈影响，信号通常是采用“总