| 本书是作者在总结针对本科生和研究生阶段的数字信号处理教学经验的基础上形成的。本书针对电子工程、计算机工程和计算机科学专业的学生介绍了离散时间信号、系统和现代信号处理算法的基本原理及其应用，重点集中于数字信号处理系统的分析和设计以及计算机实现。全书内容的编排既侧重于理论又深入实际应用，且每章后都有许多精心设计的习题来帮助读者掌握所学知识。 |
| John G.Proakis长期担任美国东北大学的电气工程教授，并担任该校电气与计算机工程系主任之职达14年之久。他分别从麻省理工学院和哈佛大学获得了硕士和博士学位。Proakis教授是众多成功教材的作者，其教材在世界上具有相当的影响力。 |
| PREFACE 1 INTRODUCTION 1.1 Signals,Systems,and Signal Processing 1.1.1 Basic Elements of a Digital Signal Processing System 1.1.2 Advantages of Digital over Analog Signal Processing 1.2 Classification of Signals 1.2.1 Multichannel and Multidimensional Signals 1.2.2 Continuous-Time Versus Discrete-Time Signals 1.2.3 Continuous-Valued Versus Discrete-Valued Signals 1.2.4 Deterministic Versus Random Signals 1.3 The Concept of Frequency in Continuous-Time and Discrete-Time Signals 1.3.1 Continuous-Time Sinusoidal Signals 1.3.2 Discrete-Time Sinusoidal Signals 1.3.3 Harmonically Related Complex Exponentials 1.4 Analog-to-Digital and Digital-to-Analog Conversion 1.4.1 Sampling of Analog Signals 1.4.2 The Sampling Theorem 1.4.3 Quantization of Continuous-Amplitude Signals 1.4.4 Quantization of Sinusoidal Signals 1.4.5 Coding of Quantized Samples 1.4.6 Digital-to-Analog Conversion 1.4.7 Analysis of Digital Signals and Systems Versus Discrete-Time Signals and Systems 1.5 Summary and References Problems 2 DISCRETE-TIME SIGNALS AND SYSTEMS 2.1 Discrete-Time Signals …… 2.2 Discrete-Time Systems 2.3 Analysis of Discrete-Time Linear Time-Invariant Systems 2.4 Discrete-Time Systems Described by Difference Equations 2.5 Implementation of Discrete-Time Systems 2.6 Correlation of Discrete-Time Signals 2.7 Summary andReferences Problems 3 THE Z-TRANSFORM AND ITS APPLICATION TO THEANALYSIS OF LTlSYSTEMS 3.1 The z-Transform 3.2 Properties o fthe z-Transform 3.3 Rational z-Transforms 3.4 Inversion of the z-Transform 3.5 The One-sided z-Transform 3.6 Analysis of Linear Time-Invariant Systems in the z-Domain 3.7 Summary and References Problems 4 FREQUENCY ANALYSIS OF SIGNALS AND SYSTEMS 4.1 Frequency Analysis of Continuous-Time Signals 4.2 Frequency Analysis of Discrete-Time Signals 4.3 Properties of the Fourier Transform for Discrete-Time Signals 4.4 Frequency-Domain Characteristics of Linear Time-Invariant Systems 4.5 Linear Time-Invariant Systems as Frequency-Selective Filters 4.6 Inverse Systems and Deconvolution Problems 5 THE DISCRETE FOURIER TRANSFORM:ITS PROPERTIES AND APPLICATIONS 5.1 Frequency Domain Sampling:The Discrete Fourier Transform 5.2 Properties of the DFT 5.3 Linear Filtering Methods Basedon the DFT 5.4 Frequency Analysis of Signals Using the DFT 5.5 Summary and References Problems 6 EFFICIENT COMPUTATION OF THE DFT:FAST FOURIER TRANSFORM ALGORITHMS 6.1 Efficient Computation of the DFT:FFT Algorithms 6.2 Applications of FFT Algorithms 6.3 A Linear Filtering Approach to Computation of the DFT 6.4 Quantization Effects in the Computation ofthe DFT 6.5 Summary and References Problems 7 IMPLEMENTATION OF DISCRETE-TIME SYSTEMS 7.1 Structures for the Realization of Discrete-Time Systems 7.2 Structures for FIR Systems 7.3 Structures for IIR Systems 7.4 State-Space System Analysis and Structures 7.5 Representation of Numbers 7.6 Quantization of Filter Coefficients 7.7 Round-Off Effects in Digital Filters 7.8 Summary and References Problems 8 DESIGN OF DIGITAL FILTERS 8.1 General Considerations 8.2 Design of FIR Filters 8.3 Design of IIR Filters From Analog Filters 8.4 Frequency Transformations 8.5 Design of Digital Filters Based on Least-Squares Method 8.6 Summary and References Problems 9 SAMPLING AND RECONSTRUCTION OF SIGNALS 9.1 Sampling of Bandpass Signals 9.2 Analog-to-Digital ConverSion 9.3 Digital-to-Analog Conversion 9.4 Summary and References Problems 10 MULTIRATE DIGITAL SIGNAL PROCESSING 10.1 Introduction 10.2 Decimation by a Factor D 10.3 Interpolation by a Factor I 10.4 Sampling Rate Conversion by a Rational Factor I/D 10.5 Filter Design and Implementation for Sampling-Rate Conversion 10.6 Multistage Implementation of Sampling-Rate Conversion 10.7 Sampling-Rate Conversion of Bandpass Signals 10.8 Sampling-Rate Conversion by an Arbitrary Factor 10.9 Applications of Multirate Signal Processing 10.10 Summary and References Problems 11 LINEAR PREDICTION AND OPTIMUM LINEAR FILTERS 11.1 Innovations Representation of a Stationary Random Process 11.2 Forward and Backward Linear Prediction 11.3 Solution of the Normal Equations 11.4 Properties of the Linear Prediction-Error Filters 11.5 AR Lattice and ARMA Lattice-Ladder Filters 11.6 Wiener Filters for Filtering and Prediction 11.7 Summary and References Problems 12 POWER SPECTRUM ESTIMATION 12.1 Estimation of Spectra from Finite-Duration Observations of Signals 12.2 Nonparametric Methods for Power Spectrum Estimation 12.3 Parametric Methods for Power Spectrum Estimation 12.4 Minimum Variance Spectral Estimation 12.5 Eigenanalysis Algorithms for Spectrum Estimation 12.6 Summary and References Problems A RANDOM SIGNALS,CORRELATION FUNCTIONS,AND POWER SPECTRA B RANDOM NUMBER GENERATORS C TABLES OF TRANSITION COEFFICIENTS FOR THE DESIGN OF LINEAR-PHASEFIRFILTERS D LIST OF MATLAB FUNCTIONS REFERENCES AND BIBLIOGRAPHYR1 INDEX |
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