现代数字信号处理AdvancedDigitalSignalProcessing-introdu

AdvancedDigitalSignalProcessingSchoolofInformationEngineering,HebeiUniversityofTechnologyZengCheng20011.4,Introduction,TheClassicalDigitalSignalProcessing(CDSP)andtheAdvancedDigitalSignalProcessing(ADSP)CDSPSignal:one-dimensionaldeterministicsignalMethods:nonparametric(wave-based)methods,suchasDFTLinear,causalandminimum-phasesystems(mostly)Invariantsamplingrate,CDSPanditsgeneralization,Method:wave-based,System:LTI,minimal-phase,Samplerate:invariant,Signal:1-D,deterministic,CDSP,MaintopicsinADSPClassicalstatisticalsignalprocessingSignals:stationaryrandom(stochastic)signal(oftenwithGaussianornormaldistributions)Methods:model-basedmethods(e.g.ARlinearpredictionmodel),BayesianStatisticalSignalProcessing(basedonstochasticprocessanalysis)MainsubjectsStationarystochasticsignalanalysisBayesianestimationOptimalfiltering(Wienerfilter&Kalmanfilter)AdaptivesignalprocessingPowerspectrumestimation(especiallythemodernmethods),Non-stationarystochasticsignalprocessingHiddenMarkovModels(HMM)Widelyappliedintheprocessingof“naturallygenerated”signals,suchasaudiosignals,imagesignals,biomedicalsignalsandseismicsignalsTime-frequencyanalysis(short-timeFouriertransform(STFT),Gabordecomposition,Wignerdistribution)WaveletanalysisMultiratesignalprocessingApplications:discrete-timesystemswithsignalssampledinunequalsamplingratesDown-sampling,up-sampling,filterbanks,Non-GaussianstochasticsignalprocessingSignals:stochasticsignalswithoutGaussiandistributionsMethods:high-orderstatisticanalysisMulti-dimensiondigitalsignalprocessingSignals:multi-dimension(oftentwo-dimension)stochasticordeterministicsignals,suchasdigitalimagesignalsSometheoriesbasedonone-dimensionsignalscannotbegeneralizedintomulti-dimensionsignalsdirectlyTheprocessingofmulti-dimensionsignalsconfrontssomenewproblemswhichneveroccurinthecaseofone-dimension,NonlinearsignalprocessingProcessingsignalswithnonlinearsystemtheoryandmethod(noticethatwhatisnonlinearhereisthesystem,notthesignal)MethodsNonlinearfilteringCepstrumandhomogenousdeconvolutionNeuralnetworksignalprocessing,AboutOurCoursesContentorganizationBasictheoriesandalgorithmsfortheprocessingofdiscrete(digital)randomsignals,includingtheirimplementationsandapplicationsFundamentalsofdiscreterandomsignalAnalysisWienerfilteranddiscreteKalmanfilterAdaptivesignalprocessingPowerspectrumestimationTime-frequencyanalysis(STFT)Waveletanalysis,TheprincipalobjectivesGiveanintroductiontobasicconceptsandmethodologiesthatcanprovidethefoundationforfurtherstudy,researchandapplicationBasicrequirementsForalldiscussedsubjects(theoryoralgorithm),UnderstandingtheirfundamentalmathematicalprinciplesKnowingtheircharacteristicsandappreciatingtheirlimitationsImplementation&applicationsUsingthemtoanalyzesimplepracticalproblems,PrerequisitesSignalandsystemDigitalsignalprocessing(classical)ProbabilitytheoryandstochasticprocessLinearalgebraFinalexaminationAwrittenexaminationforthestudentsmajoringin“communicationandinformationsystem”，“circuitandsystem”Atermpaperforothers?,Textbookandreferences丁玉美，阔永红，高新波.数字信号处理时域离散随机信号处理（研究生教材）.西安电子科技大学出版社，2002(textbook)姚天任.现代数字信号处理.华中理工大学出版社，1999陆传贲.现代信号处理导论.北京邮电大学出版社，2003张明友,吕明.近代信号处理理论与方法.国防工业出版社，2005S.V.Vaseghi.AdvancedDigitalSignalProcessingandNoiseReduction,SecondEdition.JohnWileysSons