资 源 简 介
Digital Signal Processing-Principles,Algorithms,and Applications(Third Edition)数字信号处理 [美]John G. Proakis著 英文版This edition may be sold only in those countries to which it is consigned by Prentice-Hall International.It is not to be reexported and it is not for sale in the U.S.A. Mexico, or Canadac 1996 by Prentice-Hall, IncSimon schuster/A Viacom CompanyUpper Saddle River, New Jersey 07458All rights reserved. No part of this book may bereproduced. in any form or by any means,without permission in writing from the publisherThe author and publisher of this book have used their best efforts in preparing this book. Theseefforts include the development, research and testing of the theories and programs to determine theireffectiveness. The author and publisher make no warranty of any kind, expressed or implied. withregard to these programs or the documentation contained in this book. The author and publisher shallnot be liable in any event for incidental or consequential damages in connection with or arising outof the furnishing. performance. or use of these programsPrinted in the united states of americaISBN D-13-3433吕-日Prentice-Hall International(UK) Limited. LondonPrentice-Hall of A ustralia Pty. Limited, SydneyPrentice-Hall Canada. IPrentice-Hall Hispanoamericana. SA. MexicoPrentice-Hall of India Private Limited. New DelhiPrentice-Hall of Japan, Inc, TokyoSimon Schuster Asia Pte. Ltd, SingaporeEditora Prentice-Hall do Brasil. Ltda. rio de janeiroPrentice-Hall, Inc. Upper Saddie River, New JerseyContentsPREFACE1 INTRODUCTIONSignals, Systems and Signal Processing 21. 1. 1 Basic Elements of a Digital Signal Processing System. 41.1.2 Advantages of Digital over Analog Signal Processing, 5Classification of signals 61.2.1 Multichannel and Multidimensional Signals. 72.2 Continuous-Time Versus Discrete-Time Signals. 81.2.3 Continuous-Valued Versus Discrete-Valued Signals. 101.2.4 Deterministic Versus Random Signals, 111.3 The Concept of Frequency in Continuous-Time andDiscrete-Time Signals 141.3. 1 Continuous-Time Sinusoidal Signals, 141.3.2 Discrete-Time Sinusoidal Signals. 161.3.3 Harmonically Related Complex Exponentials, 191.4 Analog-to-Digital and Digital-to-Analog Conversion1.4.1 Sampling of Analog Signals, 231.4.2 The Sampling Theorem, 291.4.3 Quantization of Continuous-Amplitude Signals, 331.4.4 Quantization of Sinusoidal signals, 36Coding of Quantized Samples. 381.4.6 Digital-to-Analog Conversion, 381.4.7 Analysis of Digital Signals and Systems Versus Discrete-TimeSignals and Systems, 391. 5 Summary and references 39Problems 40Cont2 DISCRETE-TIME SIGNALS AND SYSTEMS2.1 Discrete-Time Signals 43ElemTime Signals, 452.1.2 Classification of Discrete-Time Signals, 472.1.3 Simple Manipulations of Discrete-Time Signals, 522. 2 Discrete-Time Systems 562.2.1 Input-Output Description of Systems. 562.2.2 Block Diagram Representation of Discrete- Time Systems, 592.2.3 Classification of Discrete-Time Systems. 622.2.4 Interconnection of Discrete-Time Systems, 703 Analysis of Discrete-Time Linear Time-Invariant Systems 722.3.1 Techniques for the Analysis of Linear Systems, 722.3.2 Resolution of a Discrete-Time Signal into Impulses, 742.3.3 Response of LTI Systems to Arbitrary Inputs: The ConvolutionSum. 753.4 Properties of Convolution and the Interconnection of LtiSystems. 822.3.5 Causal Linear Time-Invariant Systems. 862.3.6 Stability of Linear Time-Invariant Systems. 872.3.7 Systems with Finite-Duration and infinite-Duration ImpulsResponse. 902.4.1 Recursive and Nonrecursive Discrete- Time Systems, 92 912. 4 Discrete- Time Systems Described by Difference Equation2.4.2 Linear Time-Invariant Systems Characterized byConstant-Coefficient Difference Equations, 952.4.3 Solution of Linear Constant-Coefficient Difference Equations. 1002.4.4 The Impulse Response of a Linear Time-Invariant RecursiveSystem. 1082.5 Implementation of Discrete-Time Systems 1112.5. 1 Structures for the realization of linear Time-InvariantSystems. 1112.5.2 Recursive and Nonrecursive Realizations of Fir Systems, 1162.6 Correlation of Discrete-Time Signals 1182.6. 1 Crosscorrelation and autocorrelation Sequences. 1202.6.2 Properties of the Autocorrelation and CrosscorrelationSequences. 1222.63 Correlation of Periodic Sequences, 122.6.4 Computation of Correlation Sequences. 1306.5 Input-Output Correlation Sequences, 1312.7 Summary and references 134Problems 135Contents3 THE Z-TRANSFORM AND ITS APPLICATION TO THE ANALYSISOF LTI SYSTEMS151The --Transform 1513.1.1 The Direct --Transform 1523. 1.2 The inverse --Transform. 1603.2Pies of the --Transform 1613.3 Rational --Transforms 1723.3.1 Poles and Zeros, 1723.3.3 The System Function of a Linear Time-Invariant System. 187]783.3.2 Pole Location and Time- Domain Behavior for Causal Signals3.4 Inversion of the - Transform 1843.4.1 The Inverse :-Transform by Contour integration. 1843.4.2 The Inverse - - Transform by Power Series Expansion. 1863.4.4 Decomposition of Rational:-Transforms. expansion. 1883.4.3 The Inverse --Transform by Partial-Fraction E3.5 The One-sided --Transform 1973.5. 1 Definition and Properties. 1973.5.2 Solution of Difference Equations. 2013.6 Analysis of Linear Time-Invariant Systems in the --Domain 20336.1Rof Systems with Rational System Functions 2033.6.2 Response of Pole-Zero Systems with Nonzero initialCondilions. 2043.6.3 Transient and Steady - State responses, 2063.6.4 Causality and Stability. 2083.6.5 Pole-Zero Cancellations. 2103.6.6 Multiple-Order Poles and Stability. 2113.6.7 The Schur-Cohn Stability Test, 2133.6.8 Stabilitv of Second-Order Svstems. 2153.7 Summary and References 219Problems 2204 FREQUENCY ANALYSIS OF SIGNALS AND SYSTEMS4.1 Frequency Algals 2304.1.1 The Fourier Series for Continuous-Time Periodic Signals. 2324. 1. 2 Power Density sof periodic sig4.1.3 The Fourier Transform for Continuous-Time aperiodicSignals, 2404.1.4 Energy Density Spectrum of Aperiodic Signals. 2434.2Fncy Analysis of Discrete-Time Signals 2474.2.1 The Fourier Series for Discrete-Time Periodic Signals, 247Contents4.2.2 Power Density Spectrum of Periodic Signals. 2504.2.3 The Fourier Transform of Discrete-Time Aperiodic Signals. 2534.2.4 Convergence of the Fourier Transform. 2564.2.5 Energy Density Spectrum of Aperiodic Signals, 2604. 2.6 Relationship of the Fourier Transform to the z-Transform. 2644.2.7 The Cepstrum. 26.54.2.8 The Fourier Transform of Signals with Poles on the UnitCircle. 2674.2.9 The Sampling Theorem Revisited, 2694.2.10 Frequency-Domain Classification of Signals: The Concept ofBandwidth. 2794.2.12 Physical and Mathematical Dualities. 202 gnals. 2824.2.11 The Frequency Ranges of Some Natural Si3 Properties of the Fourier Transform for Discrete-TimeSignals 2864.3.1 Symmetry Properties of the Fourier Transform, 2874.3.2 Fourier Transform Theorems and Properties. 2944. 4 Frequency-Domain Characteristics of Linear Time-InvariantSystems 3054. 4.1 Response to Complex Exponential and Sinusoidal Signals: TheFrequency Response Function. 3064.4.2 Steady-State and Transient Response to Sinusoidal InputSignals. 3144.4.3 Steady-State Response to Periodic Input Signals. 3154.4.4 Response Lo Aperiodic Input Signals. 3164.4.5 Relationships Between the System Function and the frequencyResponse Function 3194.4.6 Computation of the Frequency Response Function. 3214.4.7 Input-Output Correlation Functions and Spectra, 3254.4.8 Correlation Functions and Power Spectra for Random InputSignals. 3274.5 Linear Time-Invariant Systems as Frequency - SelectiveFilters 3304.5.1 Ideal Filter Characteristics, 3314.5.2 Lowpass, Highpass and Bandpass Filters, 3334.5.3 Digital Resonators, 3404.5.4 Notch Filters. 3434.5.5 Comb Fitters. 3454.5.6 All-Pass Filters. 3504.5.7 Digital Sinusoidal Oscillators. 3524.6 Inverse Systems and Deconvolution 3554.6.1 Invertibility of Linear Time-Invariant Systems, 3564.6.2 Minimum-Phase. Maximum-Phase, and Mixed-Phase Systems. 3594.6.3 System Identification and Deconvolution 3634.6.4 Homomorphic Deconvolution. 36.5Contents4.7 Summary and References 367Problems 3685 THE DISCRETE FOURIER TRANSFORM: ITS PROPERTIES ANDAPPLICATIONS3945.1 Frequency Domain Sampling: The Discrete FourierTransform 3945.1. 1 Frequency-Domain Sampling and Reconstruction ofDiscrete- Time signais. 3945.1.2 The Discrete Fourier Transform(DFT). 3995.1.3 The DFt as a Linear Transformation. 4035.1.4 Relationship of the dFt to Other Transforms, 4075.2 Properties of the DFT 4095.2. 1 Periodicity, Linearity and Symmetry Properties, 4105.2.2 Multiplication of two DFTs and Circular Convolution. 4155.2.3 Additiona! DFT Properties, 4215.3 Linear Filtering methods based on the dft 4255.3. 1 Use of the dft in Linear Filtering. 4265.3.2 Filtering of Long Data Sequences. 430Frequency Analysis of Signals Using the DFT 4335 Summary and References 4406 EFFICIENT COMPUTATION OF THE DFT: FAST FOURIERTRANSFORM ALGORITHMS4486.1 Efficient Computation of the DFT: FFT Algorithms 4486.1.1 Direct Computation of the dFT. 4496. 1.2 Divide-and-Conquer Approach to Computation of the DFT. 4506. 1.3 Radix-2 FFT Algorithms. 4566.1.4 Radix-4 FFT Algorithms. 4656.1.5 Split-Radix FFT Algorithms, 4706. 1.6 Implementation of FFT Algorithms. 4736. 2 Applications of FFT Algorithms 4756. 2. 1 Efficient Computation of the dFt of Two real Sequences. 4756.2.2 Efficient Computation of the dFf of a 2N-Point RealSequence, 4766.2.3 Use of the FFT Algorithm in Linear Filtering and Correlation 4776.3 A Linear Filtering Approach to Computation of the DFT 4796.3.1 The Goertzel Algorithm, 4806.3.2 The Chirp-z Transform Algorithm, 4826.4 Quantization Effects in the Computation of the dft 4866.4.1 Quantization Errors in the Direct Computation of the DFT. 4876.4.2 Quantization Errors in FFT Algorithms. 4896.5 Summary and References 493Problems 4947 MPLEMENTATON OF DISCRETE-TIME SYSTEMS5007. 1 Structures for the Realization of Discrete-Time Systems 5007.2 Structures for FIR Systems 5027. 2.2 Cascade-Form Structures. 5047. 2.3 Frequency-Sampling Structures7.2.4 Lattice Structure. 5117.3 Structures for Iir Systems 5197.3.2 Signal Flow Graphs and Transposed Structures. 5217.3.4 Paralle]-Form structures 529Lattice and Lattice- Ladder Structures for IiR Syslems. 531State-Space Svstem Analysis and Structures 5397.4.1 State-Space Descriptions of Systems Characterized by DifferenceEquations. 5407.4.2 Solution of the State- Space Equations. 5437.4.3 Relationships Between Input-Output and State-SpaceDescriptions, 5457.4.4 State-Space Analysis in the z-Domain, 5507.4.5 Additional State-Space Structures. 5545 Representation of Numbers 5567.5.1 Fixed-Point Representation of Numbers 5577.5.2 Binary Floating-Point Representation of Numbers. 5617.5.3 Errors Resulting from Rounding and Truncation. 5647.6 Quantization of Filter Coefficients 5697.6.1 Analysis of Sensitivity to Quantization of Filter Coefficients 5697.6.2 Quantization of Coefficients in FIR Filters, 5787.7 Round-Off Effects in Digital Filters 5827.7.1 Limit-Cycle Oscillations in Recursive Systems. 5837.7. 2 Scaling to Prevent Overflow. 5887.7. 3 Statistical Characterization of Quantization Effects in Fixed-PointRealizations of Digital Filters 5907.8 Summary and References 598Problems 600Contents8 DESIGN OF DIGITAL FILTERS6148. 1 General Considerations 6148. 1.1 Causality and its implications, 6158.1.2 Characteristics of Practical Frequency-Selective Filters. 6198.2 Design of FIR Filters 6208.2.1 Symmetric and Antisymmetric FIR Filters, 6208.2.2 Design of Linear-Phase FIR Filters Using Windows, 628.2.3 Design of Linear-Phase FIR Filters by the Frequency-SamplingMethod, 6308.2.4 Design of Optimum Equiripple Linear-Phase FIR Filters. 6378.2.5 Design of FIR Differentiators, 6528.2.6 Design of hilbert Transformers. 6578.2.7 Comparison of Design Methods for Linear-Phase FIR Filters, 6628.3 Design of IIR Filters From Analog Filters 6668.3.1 IIR Filter Design by Approximation of Derivatives. 6678.3.2 IIR Filter Design by Impulse Invariance 6718.3.3 IIR Filter Design by the Bilinear Transformation. 6768.3.4 The Matched-- Transformation. 6818.3.5 Characteristics of Commonly Used Analog Filters. 6818.3.6 Some Examples of Digital Filter Designs Based on the Bilinear698.4 Frequency Transformations 69284.1FTransformations in the Analog Domain, 6938.4.2 Frequency Transformations in the dDomain, 6988.5 Design of Digital Filters Based on Least-Squares Method 7018.5.1 Pade approximation method. 7018.5.2 Least-Squares Design Methods, 7068.5.3 FIR Least-Squares Inverse(Wiener) Filters, 7118.5.4 Design of IIR Filters in the Frequency Domain, 7198.6 Summary and References 724Problems 7269 SAMPLING AND RECONSTRUCTION OF SIGNALS7389.1 Sampling of Bandpass Signals 7389.1.1 Representation of Bandpass Signals, 7389.1.2 Sampling of Bandpass Signals, 7429.1.3 Discrete-Time Processing of Continuous-Time Signals, 7469Analog-to-Digital Conversion 7489.2.1 Sample-and-Hold. 7489.2.2 Quantization and Coding, 750.2.3 Analysis of Quantization Errors 7539.2.4 Oversampling A/D Converters, 756
