數(shù)字信號處理：原理、算法與應用

定　價：￥89.00

作　者：	（美）John G.Proakis，（美）Dimitris G.Manolakis著
出版社：	中國電力出版社
叢編項：	國外經(jīng)典計算機科學教材
標　簽：	通信技術理論與基礎

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ISBN：	9787508324999	出版時間：	2004-09-01	包裝：	膠版紙
開本：	23cm	頁數(shù)：	968	字數(shù)：

內(nèi)容簡介

　　為了給讀者在理論和實踐應用之間進行合理的平衡，本書嚴謹?shù)亟榻B了現(xiàn)代數(shù)字信號處理的基本概念和技術，并介紹了相關的算法和應用。本書涵蓋了線性離散時間系統(tǒng)分析的時域和頻域方法，還涉及了諸如采樣、數(shù)字濾波器設計、濾波器實現(xiàn)、去卷積、插值、狀態(tài)矢量空間方法、頻譜分析等相關主題的內(nèi)容。本書不僅要求對諸多示例、練習的理解，而且更強調(diào)對數(shù)字信號算法進行軟件實現(xiàn)的實踐環(huán)節(jié)。本書特點：·覆蓋離散傅立葉變換（DFT）和快速傅立葉變換（FFT）算法，并對其進行了更加合理清晰的重組——介紹DFT，并在闡明傅立葉分析后描述其快速計算·描述模擬信號模數(shù)轉換中涉及的運算和技術·在時域研究線性時不變離散時間系統(tǒng)和離散時間信號的特性·考慮雙邊z變換和單邊z變換，并描述了求z反變換的方法·在頻域分析信號與系統(tǒng)，給出連續(xù)時間信號與離散時間信號的傅立葉級數(shù)與傅立葉變換·實現(xiàn)無限沖激響應（IIR）與有限沖激響應（FIR）系統(tǒng)的結構形式，包括直接型、級聯(lián)型、并聯(lián)型、格型和格梯型·采樣頻率轉換基礎與多采樣率轉換系統(tǒng)·功率譜估計的詳細測試，并討論了非參數(shù)方法、基于模型的方法和基于特征分解的方法，包括MUSIC算法和ESPRIT算法·全書囊括了許多實例，并提供大約500個可解決的問題本書既適合作為本科生學習離散系統(tǒng)和數(shù)字信號處理課程的教材，又適合研究生一年級學習數(shù)字信號處理課程時作為教材使用。

作者簡介

　　JohnG.Proakis長期擔任美國東北大學的電氣工程教授，并擔任該校電氣與計算機工程系主任之職達14年之久。他分別從麻省理工學院和哈佛大學獲得了碩士和博士學位。Proakis教授是眾多成功教材的作者，其教材在世界上具有相當?shù)挠绊懥Α?/div>

圖書目錄

IINTRODUCTION
1.1Signals,Systems,andSignalProcessing2
1.1.1BasicElementsofaDigitalSignalProcessingSystem,4
1.1.2AdvantagesofDigitaloverAnalogSignalProcessing,5
1.2ClassificationofSignals6
1.2.1MultichannelandMultidimensionalSignals,7
1.2.2Continuous-TimeVersusDiscrete-TimeSignals,8
1.2.3Continuous-ValuedVersusDiscrete-ValuedSignals,10
1.2.4DeterministicVersusRandomSignals,11
1.3TheConceptofFrequencyinContinuous-Timeand
Discrete-TimeSignals14
1.3.1Continuous-TimeSinusoidalSignals,14
1.3.2Discrete-TimeSinusoidalSignals,16
1.3.3HarmonicallyRelatedComplexExponentials,19
1.4Analog-to-DigitalandDigital-to-AnalogConversion21
1.4.1SamplingofAnalogSignals,23
1.4.2TheSamplingTheorem,29
1.4.3QuantizationofContinuous-AmplitudeSignals,33
1.4.4QuantizationofSinusoidalSignals,36
1.4.5CodingofQuantizedSamples,38
1.4.6Digital-to-AnalogConversion,38
1.4.7AnalysisofDigitalSignalsandSystemsVersusDiscrete-Time
SignalsandSystems,39
1.5SummaryandReferences39
Problems40
2DISCRETE-TIMESIGNALSANDSYSTEMS
2.1Discrete-TimeSignals43
2.1.1SomeElementaryDiscrete-TimeSignals,45
2.1.2ClassificationofDiscrete-TimeSignals,47
2.1.3SimpleManipulationsofDiscrete-TimeSignals,52
2.2Discrete-TimeSystems56
2.2.1Input-OutputDescriptionofSystems,56
2.2.2BlockDiagramRepresentationofDiscrete-TimeSystems,59
2.2.3ClassificationofDiscrete-TimeSystems,62
2.2.4InterconnectionofDiscrete-TimeSystems,70
2.3AnalysisofDiscrete-TimeLinearTime-InvariantSystems72
2.3.1TechniquesfortheAnalysisofLinearSystems,72
2.3.2ResolutionofaDiscrete-TimeSignalintoImpulses,74
2.3.3ResponseofLTISystemstoArbitraryInputs:TheConvolution
Sum.75
2.3.4PropertiesofConvolutionandtheInterconnectionofLTl
Systems,82
2.3.5CausalLinearTime-InvariantSystems,86
2.3.6StabilityofLinearTime-InvariantSystems,87
2.3.7SystemswithFinite-DurationandInfinite-DurationImpulse
Response.90
2.4Discrete-TimeSystemsDescribedbyDifferenceEquations91
2.4.1RecursiveandNonrecursiveDiscrete-TimeSystems.92
2.4.2LinearTime-InvariantSystemsCharacterizedby
Constant-CoefficientDifferenceEquations,95
2.4.3SolutionofLinearConstant-CoefficientDifferenceEquations.100
2.4.4TheImpulseResponseofaLinearTime-InvariantRecursive
System.108
2.5ImplementationofDiscrete-TimeSystems111
2.5.1StructuresfortheRealizationofLinearTime-Invariant
Systems.111
2.5.2RecursiveandNonrecumveRealizationsofFIRSystems.116
2.6CorrelationofDiscrete-TimeSignals118
2.6.1CrosscorrelationandAutocorrelationSequences,120
2.6.2PropertiesoftheAutocorrelationandCrosscorrelation
Sequences.122
2.6.3CorrelationofPeriodicSequences,124
2.6.4ComputationofCorrelationSequences,130
2.6.5Input-OutputCorrelationSequences,131
2.7SummaryandReferences134
Problems135
3THEZ-TRANSFORMANDITSAPPLICATIONTOTHEANALYSIS
OFLTlSYSTEMS151
3.1Thez-Transform151
3.1.1TheDirectz-Transform.152
3.1.2TheInversez-Transform,160
3.2Propertiesofthez-Transform161
3.3Rationalz-Transforms172
3.3.1PolesandZeros.172
3.3.2PoleLocationandTime-DomainBehaviorforCausalSignals.178
3.3.3TheSystemFunctionofaLinearTime-InvariantSystem,181
3.4Inversionofthez-Transform184
3.4.1TheInversez-TransformbyContourIntegration,184
3.4.2TheInversez-TransformbyPowerSeriesExpansion.186
3.4.3TheInversez-TransformbyPartial-FractionExpansion,[88
3.4.4DecompositionofRationalz-Transforms.195
3.5TheOne-sidedz-Transform197
3.5.1DefinitionandProperties,197
3.5.2SolutionofDifferenceEquations,201
3.6AnalysisofLinearTime-InvariantSystemsinthez-Domain203
3.6.1ResponseofSystemswithRationalSystemFunctions.203
3.6.2ResponseofPole-ZeroSystemswithNonzeroInitial
Conditions.204
3.6.3TransientandSteady-StateResponses.206
3.6.4CausalityandStability.208
3.6.5Pole-ZeroCancellations,210
3.6.6Multiple-OrderPolesandStability,211
3.6.7TheSchur-CohnStabilityTest,213
3.6.8StabilityofSecond-OrderSystems,215
3.7SummaryandReferences219
Problems220
4FREQUENCYANALYSISOFSIGNALSANDSYSTEMS230
4.1FrequencyAnalysisofContinuous-TimeSignals230
4.1.1TheFourierSeriesforContinuous-TimePeriodicSignals.232
4.1.2PowerDensitySpectrumofPeriodicSignals,235
4.1.3TheFourierTransformforContinuous-TimeAperiodic
Signals,240
4.1.4EnergyDensitySpectrumofAperiodicSignals.243
4.2FrequencyAnalysisofDiscrete-TimeSignals247
4.2.1TheFourierSeriesforDiscrete-TimePeriodicSignals,247
4.2.2PowerDensitySpectrumofPeriodicSignals,250
4.2.3TheFourierTransformofDiscrete-TimeAperiodicSignals,253
4.2.4ConvergenceofttxeFourierTransform,256
4.2.5EnergyDensitySpectrumofAperiodicSignals,260
4.2.6RelationshipoftheFourierTransformtothez-Transform,264
4.2.7TheCepstrum,265
4.2.8TheFourierTransformofSignalswithPolesontheUnit
Circle,267
4.2.9TheSamplingTheoremRevisited,269
4.2.10Frequency-DomainClassificationofSignals:TheConceptof
Bandwidth,279
4.2.11TheFrequencyRangesofSomeNaturalSignals,282
4.2.12PhysicalandMathematicalDualities,282
4.3PropertiesoftheFourierTransformforDiscrete-Time
Signals286
4.3.1SymmetryPropertiesoftheFourierTransform,287
4.3.2FourierTransformTheoremsandProperties,294
4.4Frequency-DomainCharacteristicsofLinearTime-Invariant
Systems305
4.4.1ResponsetoComplexExponentialandSinnsoidalSignals:The
FrequencyResponseFunction,306
4.4.2Steady-StateandTransientResponsetoSinusoidalInput
Signals,314
4.4.3Steady-StateResponsetoPeriodicInputSignals,315
4.4.4ResponsetoAperiodicInputSignals,316
4.4.5RelationshipsBetweentheSystemFunctionandtheFrequency
ResponseFunction,319
4.4.6ComputationoftheFrequencyResponseFunction,321
4.4.7Input-OutputCorrelationFunctionsandSpectra,325
4.4.8CorrelationFunctionsandPowerSpectraforRandomInput
Signals,327
4.5LinearTime-InvariantSystemsasFrequency-Selective
Filters330
4.5.1IdealFilterCharacteristics,331
4.5.2Lowpass,Highpass,andBandpassFilters,333
4.5.3DigitalResonators,340
4.5.4NotchFilters,343
4.5.5CombFilters,345
4.5.6All-PassFilters,350
4.5.7DigitalSinusoidalOscillators,352
4.6InverseSystemsandDeconvolution355
4.6.1InvertibilityofLinearTime-InvariantSystems,356
4.6.2Minimum-Phase,Maximum-Phase,andMixed-PhaseSystems,359
4.6.3SystemIdentificationandDeconvolution,363
4.6.4HomomorphicDeconvolution,365
SummaryandReferences367
Problems368
5THEDISCRETEFOURIERTRANSFORM:ITSPROPERTIESAND
APPLICATIONS394
5.1FrequencyDomainSampling:TheDiscreteFourier
Transform394
5.1.1Frequency-DomainSamplingandReconstructionof
Discrete-TimeSignals,394
5.1.2TheDiscreteFourierTransform(DFT),399
5.1.3TheDFTasaLinearTransformation,403
5.1.4RelationshipoftheDFTtoOtherTransforms,407
5.2PropertiesoftheDFT409
5.2.1Periodicity,Linearity,andSymmetryProperties,410
5.2.2MultiplicationofTwoDFTsandCircularConvolution,415
5.2.3AdditionalDFTProperties,421
5.3LinearFilteringMethodsBasedontheDFT425
5.3.1UseoftheDFTinLinearFiltering,426
5.3.2FilteringofLongDataSequences,430
5.4FrequencyAnalysisofSignalsUsingtheDFT433
5.5SummaryandReferences440
Problems440
6EFFICIENTCOMPUTATIONOFTHEOFT:FASTFOURIER
TRANSFORMALGORITHMS448
6.1EfficientComputationoftheDFT:FFTAlgorithms448
6.1.1DirectComputationoftheDFT,449
6.1.2Divide-and-ConquerApproachtoComputationoftheDFT,450
6.1.3Radix-2FFTAlgorithms,456
6.1.4Radix-4FFTAlgorithms,465
6.1.5Split-RadixFFTAlgorithms,470
6.1.6ImplementationofFFTAlgorithms,473
6.2ApplicationsofFFTAlgorithms475
6.2.1EfficientComputationoftheDFTofTwoRealSequences,475
6.2.2EfficientComputationoftheDFTofa2N-PointReal
Sequence,476
6.2.3UseoftheFFTAlgorithminLinearFilteringandCorrelation,477
6.3ALinearFilteringApproachtoComputationoftheDFT479
6.3.1TheGoertzelAlgorithm,480
6.3.2TheChirp-zTransformAlgorithm,482
QuantizationEffectsintheComputationof'theDFT486
6.4.1QuantizationErrorsintheDirectComputationoftheDFT,487
6.4.2QuantizationErrorsinFFTAlgorithms,489
6.5SummaryandReferences493
Problems494
7IMPLEMENTATIONOFDISCRETE-TIMESYSTEMS500
7.1StructuresfortheRealizationofDiscrete-TimeSystems500
7.2StructuresforFIRSystems502
7.2.1Direct-FormStructure,503
7.2.2Cascade-FormStructures,504
7.2.3Frequency-SamplingStructures*,506
7.2.4LatticeStructure,511
7.3StructuresforIIRSystems519
7.3.1Direct-FormStructures,519
7.3.2SignalFlowGraphsandTransposedStructures,521
7.3.3Cascade-FormStructures,526
7.3.4Parallel-FormStructures,529
7.3.5LatticeandLattice-LadderStructuresforIIRSystems,531
7.4State-SpaceSystemAnalysisandStructures539
7.4.1State-SpaceDescriptionsofSystemsCharacterizedbyDifference
Equations,540
7.4.2SolutionoftheState-SpaceEquations,543
7.4.3RelationshipsBetweenInput-OutputandState-Space
Descriptions,545
7.4.4State-SpaceAnalysisinthez-Domain,550
7.4.5AdditionalState-SpaceStructures,554
7.5RepresentationofNumbers556
7.5.1Fixed-PointRepresentatknvofNumbers,557
7.5.2BinaryFloating-PointRepresentationofNumbers,561
7.5.3ErrorsResultingfromRoundingandTruncation,564
7.6QuantizationofFilterCoefficients569
7.6.1AnalysisofSensitivitytoQuantizationofFilterCoefficients,569
7.6.2QuantizationofCoefficientsinFIRFilters,578
7.7Round-OffEffectsinDigitalFilters582
7.7.1Limit-CycleOscillationsinRecursiveSystems,583
7.7.2ScalingtoPreventOverflow,588
7.7.3StatisticalCharacterizationofQuantizationEffectsinFixed-Point
RealizationsofDigitalFilters,590
7.8SummaryandReferences598
Problems600
8DESIGNOFDIGITALFILTERS614
8.1GeneralConsiderations614
8.1.1CausalityandItsImplications,615
8.1.2CharacteristicsofPracticalFrequency-SelectiveFilters,619
8.2DesignofFIRFilters620
8.2.1SymmetricandAntisymmetricFIRFilters,620
8.2.2DesignofLinear-PhaseFIRFiltersUsingWindows,623
8.2.3DesignofLinear-PhaseFIRFiltersbytheFrequency-Sampling
Method,630
8.2.4DesignofOptimumEquirippleLinear-PhaseFIRFilters,637
8.2.5DesignofFIRDifferentiators,652
8.2.6DesignofHilbertTransformers,657
8.2.7ComparisonofDesignMethodsforLinear-PhaseFIRFilters,662
8.3DesignofIIRFiltersFromAnalogFilters666
8.3.1IIRFilterDesignbyApproximationofDerivatives,667
8.3.2IIRFilterDesignbyImpulseInvariance.671
8.3.3IIRFilterDesignbytheBilinearTransformation,676
8.3.4TheMatched-zTransformation,681
8.3.5CharacteristicsofCommonlyUsedAnalogFilters,681
8.3.6SomeExamplesofDigitalFilterDesignsBasedontheBilinear
Transformation,692
8.4FrequencyTransformations692
8.4:1FrequencyTransformationsintheAnalogDomain,693
8.4.2FrequencyTransformationsintheDigitalDomain,698
8.5DesignofDigitalFiltersBasedonLeast-SquaresMethod701
8.5.1Pad~ApproximationMethod,701
8.5.2Least-SquaresDesignMethods,706
8.5.3FIRLeast-SquaresInverse(Wiener)Filters,711
8.5.4DesignofIIRFiltersintheFrequencyDomain,719
8.6SummaryandReferences724
Problems726
9SAMPLINGANDRECONSTRUCTIONOFSIGNALS738
9.1SamplingofBandpassSignals738
9.1.1RepresentationofBandpassSignals,738
9.1.2SamplingofBandpassSignals.742
9.1.3Discrete-TimeProcessingofContinuous-TimeSignals.746
9.2Analog-to-DigitalConverSion748
9.2.1Sample-and-Hold,748
9.2.2QuantizationandCoding,750
9.2.3AnalysisofQuantizationErrors.753
9.2.4OversamplingA/DConverters,756
DESIGNOFDIGITALFILTERS614
8.1GeneralConsiderations614
8.1.1CausalityandItsImplications,615
8.1.2CharacteristicsofPracticalFrequency-SelectiveFilters,619
8.2DesignofFIRFilters620
8.2.1SymmetricandAntisymmetricFIRFilters,620
8.2.2DesignofLinear-PhaseFIRFiltersUsingWindows,623
8.2.3DesignofLinear-PhaseFIRFiltersbytheFrequency-Sampling
Method,630
8.2.4DesignofOptimumEquirippleLinear-PhaseFIRFilters,637
8.2.5DesignofFIRDifferentiators,652
8.2.6DesignofHilbertTransformers,657
8.2.7ComparisonofDesignMethodsforLinear-PhaseFIRFilters,662
8.3DesignofIIRFiltersFromAnalogFilters666
8.3.1IIRFilterDesignbyApproximationofDerivatives,667
8.3.2IIRFilterDesignbyImpulseInvariance,671
8.3.3IIRFilterDesignbytheBilinearTransformation,676
8.3.4TheMatched-zTransformation,681
8.3.5CharacteristicsofCommonlyUsedAnalogFilters,681
8.3.6SomeExamplesofDigitalFilterDesignsBasedontheBilinear
Transformation,692
8.4FrequencyTransformations692
8.4.1FrequencyTransformationsintheAnalogDomain,693
8.4.2FrequencyTransformationsintheDigitalDomain,698
8.5DesignofDigitalFiltersBasedonLeast-SquaresMethod701
8.5.1Pad6ApproximationMethod,701
8.5.2Least-SquaresDesignMethods,706
8.5.3FIRLeast-SquaresInverse(Wiener)Filters.711
8.5.4DesignofIIRFiltersintheFrequencyDomain,719
8.6SummaryandReferences724
Problems726
9SAMPLINGANDRECONSTRUCTIONOFSIGNALS738
9.1SamplingofBandpassSignals738
9.1.1RepresentationofBandpassSignals,738
9.1.2SamplingofBandpassSignals,742
9.1.3Discrete-TimeProcessingofContinuous-TimeSignals.746
9.2Analog-to-DigitalConversion748
9.2.1Sample-and-Hold,748
9.2.2QuantizationandCoding,750
9.2.3AnalysisofQuantizationErrors,753
9.2.4OversamplingA/DConverters,756
9.3Digital-to-AnalogConversion763
9.3.1SampleandHold,765
9.3.2First-OrderHold,768
9.3.3LinearInterpolationwithDelay,771
9.3.4OversamplingD/AConverters,774
9.4SummaryandReferences774
Problems775
10MULTIRATEDIGITALSIGNALPROCESSING782
10.1Introduction783
10.2DecimationbyaFactorD784
10.3InterpolationbyaFactor!787
10.4SamplingRateConversionbyaRationalFactorI/D790
10.5FilterDesignandImplementationforSampling-Rate
Conversion792
10.5.1Direct-FormFIRFilterStructures,793
10.5.2PolyphaseFilterStructures.794
10.5.3Time-VariantFilterStructures.800
10.6MultistageImplementationofSampling-RateConversion806
10.7Sampling-RateConversionofBandpassSignals810
10.7.1DecimationandInterpolationbyFrequencyConversion.812
10.7.2Modulation-FreeMethodforDecimationandInterpolation,814
10.8Sampling-RateConversionbyanArbitraryFactor815
10.8.1First-OrderApproximation.816
10.8.2Second-OrderApproximation(LinearInterpolation),819
10.9ApplicationsofMultirateSignalProcessing821
10.9.1DesignofPhaseShifters.821
10.9.2InterfacingofDigitalSystemswithDifferentSamplingRates,823
10.9.3ImplementationofNarrowbandLowpassFilters,824
10.9.4ImplementationofDigitalFilterBanks,825
10.9.5SubbandCodingofSpeechSignals,831
10.9.6QuadratureMirrorFilters,833
10.9.7Transmultiplexers,841
10.9.80versamplingA/DandD/AConversion,843
10.10SummaryandReferences844
Problems846
11LINEARPREDICTIONANDOPTIMUMLINEARFILTERS852
11.1InnovationsRepresentationofaStationaryRandom
Process852
11.1.1RationalPowerSpectra,854
11.1.2RelationshipsBetweentheFilterParametersandthe
AutocorrelationSequence,855
11.2ForwardandBackwardLinearPrediction857
11.2.1ForwardLinearPrediction,857
11.2.2BackwardLinearPrediction,860
11.2.3TheOptimumReflectionCoefficientsfortheLatticeForwardand
BackwardPredictors,863
11.2.4RelationshipofanARProcesstoLinearPrediction,864
11.3SolutionoftheNormalEquations864
11.3.1TheLevinson-DurbinAlgorithm,865
11.3.2TheSchiirAlgorithm,868
11.4PropertiesoftheLinearPrediction-ErrorFilters873
11.5ARLatticeandARMALattice-LadderFilters876
11.5.1ARLatticeStructure,877
11.5.2ARMAProcessesandLattice-LadderFilters,878
11.6WienerFiltersforFilteringandPrediction880
11.6.1FIRWienerFilter,881
11.6.20rthogonalityPrincipleinLinearMean-SquareEstimation,884
11.6.3IIRWienerFilter,885
11.6.4NoncausalWienerFilter,889
11.7SummaryandReferences890
Problems892
12POWERSPECTRUMESTIMATION898
12.1EstimationofSpectrafromFinite-DurationObservationsof
Signals896
12.1.1ComputationoftheEnergyDensitySpectrum,897
12.1.2EstimationoftheAutocorrelationandPowerSpectrumof
RandomSignals:ThePeriodogram,902
12.1.3TheUseoftheDFTinPowerSpectrumEstimation,906
12.2NonparametricMethodsforPowerSpectrumEstimation908
12.2.1TheBartlettMethod:AveragingPeriodograms,910
12.2.2TheWelchMethod:AveragingModifiedPeriodograms,911
12.2.3TheBlackmanandTukeyMethod:Smoothingthe
Periodogram,913
12.2.4PerformanceCharacteristicsofNonparametricPowerSpectrum
Estimators,916
12.2.5ComputationalRequirementsofNonparametricPowerSpectrum
Estimates,919
12.3ParametricMethodsforPowerSpectrumEstimation920
12.3.1RelationshipsBetweentheAutocorrelationandtheModel
Parameters,923
12.3.2TheYule-WalkerMethodfortheARModelParameters,925
12.3.3TheBurgMethodfortheARModelParameters,925
12.3.4UnconstrainedLeast-SquaresMethodfortheARModel
Parameters,929
12.3.5SequentialEstimationMethodsfortheARModelParameters,930
12.3.6SelectionofARModelOrder,931
12.3.7MAModelforPowerSpectrumEstimation,933
12.3.8ARMAModelforPowerSpectrumEstimation,934
12.3.9SomeExperimentalResults,936
12.4MinimumVarianceSpeCtralEstimation942
12.5EigenanalysisAlgorithmsforSpectrumEstimation946
12.5.1PisarenkoHarmonicDecompositionMethod,948
12.5.2Eigen-decompositionoftheAutocorrelationMatrixforSinusoids
inWhiteNoise,950
12.5.3MUSICAlgorithm,952
12.5.4ESPRITAlgorithm,953
12.5.5OrderSelectionCriteria,955
12.5.6ExperimentalResults,956
12.6SummaryandReferences959
Problems960
ARANDOMSIGNALS,CORRELATIONFUNCTIONS,ANDPOWER
SPECTRAA1
BRANDOMNUMBERGENERATORSB1
CTABLESOFTRANSITIONCOEFFICIENTSFORTHEDESIGNOF
LINEAR-PHASEFIRFILTERSCl
DLISTOFMATLABFUNCTIONSD1
REFERENCESANDBIBLIOGRAPHYR1
INDEX11