为了给读者在理论和实践应用之间进行合理的平衡，本书严谨地介绍了现代数字信号处理的基本概念和技术，并介绍了相关的算法和应用。本书涵盖了线性离散时间系统分析的时域和频域方法，还涉及了诸如采样、数字滤波器设计、滤波器实现、去卷积、插值、状态矢量空间方法、频谱分析等相关主题的内容。本书不仅要求对诸多示例、练习的理解，而且更强调对数字信号算法进行软件实现的实践环节。
本书特点：
·覆盖离散傅立叶变换（DFT）和快速傅立叶变换（FFT）算法，并对其进行了更加合理清晰的重组——介绍DFT，并在阐明傅立叶分析后描述其快速计算
·描述模拟信号模数转换中涉及的运算和技术
·在时域研究线性时不变离散时间系统和离散时间信号的特性
·考虑双边z变换和单边z变换，并描述了求z反变换的方法
·在频域分析信号与系统，给出连续时间信号与离散时间信号的傅立叶级数与傅立叶变换
·实现无限冲激响应（IIR）与有限冲激响应（FIR）系统的结构形式，包括直接型、级联型、并联型、格型和格梯型
·采样频率转换基础与多采样率转换系统
·功率谱估计的详细测试，并讨论了非参数方法、基于模型的方法和基于特征分解的方法，包括

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

书评
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，**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。