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Digital Signal ProcessingPDF电子书下载

外文

• 作 者：
• 出 版 社：
• 出版年份：2222
• ISBN：0133737624
• 页数：968 页

图书介绍： 查看图书目录点击购买PDF全本电子书 上一篇：THE OXFORD ENGLISH DICTIONARY SECOND EDITION VOLUME Ⅶ下一篇：CELL SURFACE REVIEWS VOLUME 6 THE CELL SURFACE AND NEURONAL FUNCTION 《Digital Signal Processing》目录 标签：

1 INTRODUCTION2

1.1 Signals,Systems,and Signal Processing2

1.1.1 Basic Elements of a Digital Signal Processing System4

1.1.2 Advantages of Digital over Analog Signal Processing5

1.2 Classification of Signals6

1.2.1 Multichannel and Multidimensional Signals7

1.2.2 Continuous-Time Versus Discrete-Time Signals8

1.2.3 Continuous-Valued Versus Discrete-Valued Signals10

1.2.4 Deterministic Versus Random Signals11

1.3 The Concept of Frequency in Continuous-Time and Discrete-Time Signals14

1.3.1 Continuous-Time Sinusoidal Signals14

1.3.2 Discrete-Time Sinusoidal Signals16

1.3.3 Harmonically Related Complex Exponentials19

1.4 Analog-to-Digital and Digital-to-Analog Conversion21

1.4.1 Sampling of Analog Signals23

1.4.2 The Sampling Theorem29

1.4.3 Quantization of Continuous-Amplitude Signals33

1.4.4 Quantization of Sinusoidal Signals36

1.4.5 Coding of Quantized Samples38

1.4.6 Digital-to-Analog Conversion38

1.4.7 Analysis of Digital Signals and Systems Versus Discrete-Time Signals and Systems39

1.5 Summary and References39

Problems40

2 DISCRETE-TIME SIGNALS AND SYSTEMS43

2.1 Discrete-Time Signals43

2.1.1 Some Elementary Discrete-Time Signals45

2.1.2 Classification of Discrete-Time Signals47

2.1.3 Simple Manipulations of Discrete-Time Signals52

2.2 Discrete-Time Systems56

2.2.1 Input-Output Description of Systems56

2.2.2 Block Diagram Representation of Discrete-Time Systems59

2.2.3 Classification of Discrete-Time Systems62

2.2.4 Interconnection of Discrete-Time Systems70

2.3 Analysis of Discrete-Time Linear Time-Invariant Systems72

2.3.1 Techniques for the Analysis of Linear Systems72

2.3.2 Resolution of a Discrete-Time Signal into Impulses74

2.3.3 Response of LTI Systems to Arbitrary Inputs:The Convolution Sum75

2.3.4 Properties of Convolution and the Interconnection of LTI Systems82

2.3.5 Causal Linear Time-Invariant Systems86

2.3.6 Stability of Linear Time-Invariant Systems87

2.3.7 Systems with Finite-Duration and Infinite-Duration Impulse Response90

2.4 Discrete-Time Systems Described by Difference Equations91

2.4.1 Recursive and Nonrecursive Discrete-Time Systems92

2.4.2 Linear Time-Invariant Systems Characterized by Constant-Coefficient Difference Equations95

2.4.3 Solution of Linear Constant-Coefficient Difference Equations100

2.4.4 The Impulse Response of a Linear Time-Invariant Recursive System108

2.5 Implementation of Discrete-Time Systems111

2.5.1 Structures for the Realization of Linear Time-Invariant Systems111

2.5.2 Recursive and Nonrecursive Realizations of FIR Systems116

2.6 Correlation of Discrete-Time Signals118

2.6.1 Crosscorrelation and Autocorrelation Sequences120

2.6.2 Properties of the Autocorrelation and Crosscorrelation Sequences122

2.6.3 Correlation of Periodic Sequences124

2.6.4 Computation of Correlation Sequences130

2.6.5 Input-Output Correlation Sequences131

2.7 Summary and References134

Problems135

3 THE Z-TRANSFORM AND ITS APPLICATION TO THE ANALYSIS OF LTI SYSTEMS151

3.1 The ?-Transform151

3.1.1 The Direct ?-Transform152

3.1.2 The Inverse ?-Transform160

3.2 Properties of the ?-Transform161

3.3 Rational ?-Transforms172

3.3.1 Poles and Zeros172

3.3.2 Pole Location and Time-Domain Behavior for Causal Signals178

3.3.3 The System Function of a Linear Time-Invariant System181

3.4 Inversion of the ?-Transform184

3.4.1 The Inverse ?-Transform by Contour Integration184

3.4.2 The Inverse ?-Transform by Power Series Expansion186

3.4.3 The Inverse ?-Transform by Partial-Fraction Expansion188

3.4.4 Decomposition of Rational ?-Transforms195

3.5 The One-sided ?-Transform197

3.5.1 Definition and Properties197

3.5.2 Solution of Difference Equations201

3.6 Analysis of Linear Time-Invariant Systems in the ?-Domain203

3.6.1 Response of Systems with Rational System Functions203

3.6.2 Response of Pole-Zero Systems with Nonzero Initial Conditions204

3.6.3 Transient and Steady-State Responses206

3.6.4 Causality and Stability208

3.6.5 Pole-Zero Cancellations210

3.6.6 Multiple-Order Poles and Stability211

3.6.7 The Schur-Cohn Stability Test213

3.6.8 Stability of Second-Order Systems215

3.7 Summary and References219

Problems220

4 FREQUENCY ANALYSIS OF SIGNALS AND SYSTEMS230

4.1 Frequency Analysis of Continuous-Time Signals230

4.1.1 The Fourier Series for Continuous-Time Periodic Signals232

4.1.2 Power Density Spectrum of Periodic Signals235

4.1.3 The Fourier Transform for Continuous-Time Aperiodic Signals240

4.1.4 Energy Density Spectrum of Aperiodic Signals243

4.2 Frequency Analysis of Discrete-Time Signals247

4.2.1 The Fourier Series for Discrete-Time Periodic Signals247

4.2.2 Power Density Spectrum of Periodic Signals250

4.2.3 The Fourier Transform of Discrete-Time Aperiodic Signals253

4.2.4 Convergence of the Fourier Transform256

4.2.5 Energy Density Spectrum of Aperiodic Signals260

4.2.6 Relationship of the Four?er Transform to the ?-Transform264

4.2.7 The Cepstrum265

4.2.8 The Fourier Transform of Signals with Poles on the Unit Circle267

4.2.9 The Sampling Theorem Revisited269

4.2.10 Frequency-Do?ain Classification of Signals:The Concept of Bandwidth279

4.2.11 The Frequency Ranges of Some Natural Signals282

4.2.12 Physical and Mathematical Dualities282

4.3 Properties of the Fcurier Transform for Discrete-Time Signals286

4.3.1 Symmetry Properties of the Fourier Transform287

4.3.2 Fourier Transform Theorems and Properties294

4.4 Frequency-Domain Characteristics of Linear Time-Invariant Systems305

4.4.1 Response to Complex Exponential and Sinusoidal Signals:The Frequency Response Function306

4.4.2 Steady-State and Transient Response to Sinusoidal Input Signals314

4.4.3 Steady-State Response to Periodic Input Signals315

4.4.4 Response to Aperiodic Input Signals316

4.4.5 Relationships Between the System Function and the Frequency Response Function319

4.4.6 Computation of the Frequency Response Function321

4.4.7 Input-Output Correlation Functions and Spectra325

4.4.8 Correlation Functions and Power Spectra for Randon Input Signals327

4.5 Linear Time-Invariant Systems as Frequency-Selective Filters330

4.5.1 Ideal Filter Characteristics331

4.5.2 Lowpass Highpass and Bandpass Filters333

4.5.3 Digital Resonators340

4.5.4 Notch Filters343

4.5.5 Comb Filters345

4.5.6 All-Pass Filters350

4.5.7 Digital Sinusoidal Oscillators352

4.6 Inverse Systems and Deconvolution355

4.6.1 Invertibility of Linear Time-Invariant Systems356

4.6.2 Minimum-Phase Maximum-Phase and Mixed-Phase Systems359

4.6.3 System Identification and Deconvolution363

4.6.4 Homomorphic Deconvolution365

4.7 Summary and References367

Problems368

5 THE DISCRETE FOURIER TRANSFORM:ITS PROPERTIES AND APPLICATIONS394

5.1 Frequency Domain Sampling:The Discrete Fourier Transform394

5.1.1 Frequency-Domain Sampling and Reconstruction of Discrete-Time Signals394

5.1.2 The Discrete Fourier Transform(DFT)399

5.1.3 The DFT as a Linear Transformation403

5.1.4 Relationship of the DFT to Other Transforms407

5.2 Properties of the DFT409

5.2.1 Periodicity,Linearity and Symmetry Properties410

5.2.2 Multiplication of Two DFTs and Circular Convolution415

5.2.3 Additional DFT Propeties421

5.3 Linear Filtering Methods Based on the DFT425

5.3.1 Use of the DFT in Linear Filtering426

5.3.2 Filtering of Long Data Sequences430

5.4 Frequency Analysis of Signals Using the DFT433

5.5 Summary and References440

Problems440

6 EFFICIENT COMPUTATION OF THE DFT:FAST FOURIER TRANSFORM ALGORITHMS448

6.1 Efficient Computation of the DFT:FFT Algorithms448

6.1.1 Direct Computation of the DFT449

6.1.2 Divide-and-Conquer Approach to Computation of the DFT450

6.1.3 Radix-2 FFT Algorithms456

6.1.4 Radix-4 FFT Algorithms465

6.1.5 Split-Radix FFT Algorithms470

6.1.6 Implementation of FFT Algorithms473

6.2 Applications of FFT Algorithms475

6.2.1 Efficient Computation of the DFT of Two Real Sequences475

6.2.2 Efficient Computation of the DFT of a 2N-Point Real Sequence476

6.2.3 Use of the FFT Algorithm in Linear Fitering and Correlation477

6.3 A Linear Filtering Approach to Computation of the DFT479

6.3.1 The Goertzel Algorithm480

6.3.2 The Chirp-?Transform Algorithm482

6.4 Quantization Effects in the Computation of the DFT486

6.4.1 Quantization Errors in the Direct Computation of the DFT487

6.4.2 Quantization Errors in FFT Algorithms489

6.5 Summary and References493

Problems494

7 IMPLEMENTATION OF DISCRETE-TIME SYSTEMS500

7.1 Structures for the Realization of Discrete-Time Systems500

7.2 Structures for FIR Systems502

7.2.1 Direct-Form Structure503

7.2.2 Cascade-Form Structures504

7.2.3 Frequency-Sampling Structures506

7.2.4 Lattice Structure511

7.3 Structures for IIR Systems519

7.3.1 Direct-Form Structures519

7.3.2 Signal Flow Graphs and Transposed Structures521

7.3.3 Cascade-Form Structures526

7.3.4 Parallel-Form Structures529

7.3.5 Lattice and Lattice-Ladder Structures for IIR Systems531

7.4 State-Space System Analysis and Structures539

7.4.1 State-Space Descriptions of Systems Characterized by Difference Equations540

7.4.2 Solution of the State-Space Equations543

7.4.3 Relationships Between Input-Output and State-Space Descriptions545

7.4.4 State-Space Analysis in the z-Domain550

7.4.5 Additional State-Space Structures554

7.5 Representation of Numbers556

7.5.1 Fixed-Point Representation of Numbers557

7.5.2 Binary Floating-Point Representation of Numbers561

7.5.3 Errors Resulting from Rounding and Truncation564

7.6 Quantization of Fiter Coefficients569

7.6.1 Analysis of Sensitivity to Quantization of Filter Coefficients569

7.6.2 Quantization of Coefficients in FIR Filters578

7.7 Round-Off Effects in Digital Filters582

7.7.1 Limit-Cycle Oscillations in Recursive Systems583

7.7.2 Scaling to Prevent Overflow588

7.7.3 Statistical Characteriztion of Quantization Effects in Fixed-Point Realizations of Digital Filters590

7.8 Summary and References598

Problems600

8 DESIGN OF DIGITAL FILTERS614

8.1 General Considerations614

8.1.1 Causality and Its Implications615

8.1.2 Characteristics of Practical Frequency-Selective Filters619

8.2 Design of EIR Filters620

8.2.1 Symmetric and Antisymmetric FIR Filters620

8.2.2 Design of Linear-Phase FIR Filters Using Windows623

8.2.3 Design of Linear-Phase FIR Filters by the Frequency-Sampling Method630

8.2.4 Design of Optimum Equiripple Linear-Phase FIR Filters637

8.2.5 Design of FIR Differentiators652

8.2.6 Design of Hilbert Transformers657

8.2.7 Comparison of Design Methods for Linear-Phase FIR Filters662

8.3 Design of IIR Filters From Analog Filters666

8.3.1 IIR Filter Design by Approximation of Derivatives667

8.3.2 IIR Filter Design by Impulse Invariance671

8.3.3 IIR Filter Design by the Bilinear Transformation676

8.3.4 The Matched-? Transformation681

8.3.5 Characteristics of Commonly Used Analog Filters681

8.3.6 Some Examples of Digital Filter Designs Based on the Bilinear Transformation692

8.4 Frequency Transformation692

8.4.1 Frequency Transformations in the Analog Domain693

8.4.2 Frequency Transformations in the Digital Domain698

8.5 Design of Digital Filters Based on Least-Squares Method701

8.5.1 Padé Approximation Method701

8.5.2 Least-Squares Design Methods706

8.5.3 FIR Least-Squares Inverse(Wiener)Filters711

8.5.4 Design of IIR Filters in the Frequency Domain719

8.6 Summary and References724

Problems726

9 SAMPLING AND RECONSTRUCTION OF SIGNALS738

9.1 Sampling of Bandpass Signals738

9.1.1 Representation of Bandpass Signals738

9.1.2 Sampling of Bandpass Signals742

9.1.3 Discrete-Time Processing of Continuous-Time Signals746

9.2 Analog-to-Digital Conversion748

9.2.1 Sample-and-Hold748

9.2.2 Quantization and Coding750

9.2.3 Analysis of Quantization Errors753

9.2.4 Oversampling A/D Converters756

9.3 Digital-to-Analog Conversion763

9.3.1 Sample and Hold765

9.3.2 First-Order Hold768

9.3.3 Linear Interpolation with Delay771

9.3.4 Oversampling D/A Converters774

9.4 Summary and References774

Problems775

10 MULTIRATE DIGITAL SIGNAL PROCESSING782

10.1 Introduction783

10.2 Decimation by a Factor D784

10.3 Interpolation by a Factor I787

10.4 Sampling Rate Conversion by a Rational Factor I/D790

10.5 Filter Design and Implementation for Sampling-Rate Conversion792

10.5.1 Direct-Form FIR Filter Structures793

10.5.2 Polyphase Filter Structures794

10.5.3 Time-Variant Filter Structures800

10.6 Multistage Implementation of Sampling-Rate Conversion806

10.7 Sampling-Rate Conversion of Bandpass Signals810

10.7.1 Decimation and Interpolation by Frequency Conversion812

10.7.2 Modulation-Free Method for Decimation and Interpolation814

10.8 Sampling-Rate Conversion by an Arbitrary Factor815

10.8.1 First-Order Approximation816

10.8.2 Second-Order Approximation(Linear Interpolation)819

10.9 Applications of Multirate Signal Processing821

10.9.1 Design of Phase Shifters821

10.9.2 Interfacing of Digital Systems with Different Sampling Rates823

10.9.3 Implementation of Narrowband Lowpass Filters824

10.9.4 Implementation of Digital Filter Banks825

10.9.5 Subband Coding of Speech Signals831

10.9.6 Quadrature Mirror Fiters833

10.9.7 Transmultiplexers841

10.9.8 Oversampling A/D and D/A Conversion843

10.10 Summary and References844

Problems846

11 LINEAR PREDICTION AND OPTIMUM LINEAR FILTERS852

11.1 Innovations Representation of a Stationary Random Process852

11.1.1 Rational Power Spectra854

11.1.2 Relationships Between the Filter Parameters and the Autocorrelation Sequence855

11.2 Forward and Backward Linear Prediction857

11.2.1 Forward Linear Prediction857

11.2.2 Backward Liear Prediction860

11.2.3 The Optimum Reflection Coefficients for the Lattice Forward and Backward Predictors863

11.2.4 Relationship of an AR Process to Linear Prediction864

11.3 Solution of the Normal Equations864

11.3.1 The Levinson-Durbin Algorithm865

11.3.2 The Schur Algorithm868

11.4 Properties of the Linear Prediction-Error Filters873

11.5 AR Lattice and ARMA Lattice-Ladder Filters876

11.5.1 AR Lattice Structure877

11.5.2 ARMA Processes and Lattice-Ladder Filters878

11.6 Wiener Filters for Filtering and Prediction880

11.6.1 FIR Wiener Filter881

11.6.2 Orthogonality Principle in Linear Mean-Square Estimation884

11.6.3 IIR Wiener Filter885

11.6.4 Noncausal Wiener Filter889

11.7 Summary and References890

Problems892

12 POWER SPECTRUM ESTIMATION896

12.1 Estimation of Spectra from Finte-Duration Observations of Signals896

12.1.1 Computation of the Energy Density Spectrum897

12.1.2 Estimation of the Autocorrelation and Power Spectrum of Random Signals:The Peridogram902

12.1.3 The Use of the DFT in Power Spectrum Estimation906

12.2 Nonparametric Methods for Power Spectrum Estimation908

12.2.1 The Bartlett Method:Averaging Periodograms910

12.2.2 The Welch Method:Averaging Modified Periodograms911

12.2.3 The Blackman and Tukey Method:Smoothing the Periodogram913

12.2.4 Performance Characteristics of Nonparametric Power Spectrum Estimators916

12.2.5 Computational Requirements of Nonparametric Power Spectrum Estimates919

12.3 Parametric Methods for Power Spectrum Estimation920

12.3.1 Relationships Between the Autocorrelation and the Model Parameters923

12.3.2 The Yule-Walker Method for the AR Model Parameters925

12.3.3 The Burg Method for the AR Model Parameters925

12.3.4 Unconstrained Least-Squares Method for the AR Model Parameters929

12.3.5 Sequential Estimation Methods for the AR Model Parameters930

12.3.6 Selection of AR Model Order931

12.3.7 MA Model for Power Spectrum Estimation933

12.3.8 ARMA Model for Power Spectrum Estimation934

12.3.9 Some Experimental Results936

2.4 Minimum Variance Spectral Estimation942

2.5 Eigenanalysis Algorithms for Spectrum Estimation946

12.5.1 Pisarenko Harmonic Decomposition Method948

12.5.2 Eigen-decomposition of the Autocorrelation Matrix for Sinusoids in White Noise950

12.5.3 MUSIC Algorithm952

12.5.4 ESPRIT Algorithm953

12.5.5 Order Selection Criteria955

12.5.6 Experimental Results956

12.6 Summary and References959

Problems960

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总结：

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