数字信号处理：应用MATLAB

　　《数字信号处理：应用MATLAB（第3版 英文影印版）》介绍了MATLAB在数字信号处理中的应用，包括时分信号与系统、时分傅里叶变换、z变换、离散傅里叶变换、离散时间滤波器实现、FIR滤波器设计、HR滤波器设计以及采样率转换等内容。《数字信号处理：应用MATLAB（第3版 英文影印版）》通过使用MATLAB这一“动态实验室”帮助读者提高解决问题的能力和严谨思维的能力。

PREFACE
1 INTRODUCTION
1．1 Overview of Digital Signal Processing
1．2 A Brief Introduction to MATLAB
1．3 Applications of Digital Signal Processing
1．4 Brief Overview of the Book

2 DISCRETE—TIME SIGNALS AND SYSTEMS
2．1 Discrete—time Signals
2．2 Discrete Systems
2．3 Convolution
2．4 Difference Equations
2．5 Problems

3 THE DISCRETE—TIME FOURIER ANALYSIS
3．1 The Discrete—time Fourier Transform （DTFT）
3．2 The Properties of the DTFT
3．3 The Frequency Domain Representation of LTISystems
3．4 Sampling and Reconstruction of Analog Signals
3．5 Problems

4 THE z—TRANSFORM
4．1 The Bilateral z—Transform
4．2 Important Properties of the z—Transform
4．3 Inversion of the z—Transform
4．4 System Representation in the z—Domain
4．5 Solutions of the Difference Equations
4．6 Problems

5 THE DISCRETE FOURIER TRANSFORM
5．1 The Discrete Fourier Series
5．2 Sampling and Reconstruction in the z—Domain
5．3 The Discrete Fourier Transform
5．4 Properties of the Discrete Fourier Transform
5．5 Linear Convolution Using the DFT
5．6 The Fast Fourier Transform
5．7 Problems

6 IMPLEMENTATION OF DISCRETE—TIME FILTERS
6．1 Basic Elements
6．2 IIR Filter Structures
6．3 FIR Filter Structures
6．4 Lattice Filter Structures
6．5 Overview of Finite—Precision Numerical Effects
6．6 Representation of Numbers
6．7 The Process of Quantization and Error Characterizations
6．8 Quantization of Filter Coefficients
6．9 Problems

7 FIR FILTER DESIGN
7．1 Preliminaries 304
7．2 Properties of Linear—phase FIR Filters
7．3 Window Design Techniques
7．4 Frequency Sampling Design Techniques
7．5 Optimal Equiripple Design Technique
7．6 Problems

8 IIR FILTER DESIGN
8．1 Some Preliminaries
8．2 Some Special Filter Types
8．3 Characteristics of Prototype Analog Filters
8．4 Analog—to—Digital Filter Transformations
8．5 Lowpass Filter Design Using MATLAB
8．6 Frequency—band Transformations
8．7 Problems

9 SAMPLING RATE CONVERSION
9．1 Introduction
9．2 Decimation by a Factor D
9．3 Interpolation by a Factor I
9．4 Sampling Rate Conversion by a Rational Factor I／D
9．5 FIR Filter Designs for Sampling Rate Conversion
9．6 FIR Filter Structures for Sampling Rate Conversion
9．7 Problems

10 ROUND—OFF EFFECTS IN DIGITAL FILTERS
10．1 Analysis of A／D Quantization Noise
10．2 Round—off Effects in IIR Digital Filters
10．3 Round—off Effects in FIR Digital Filters
10．4 Problems
BIBLIOGRAPHY

　　From the beginning of the 1980s we have witnessed a revolution in computer technology and an explosion in user-friendly applications. This revolution is still continuing today with low-cost personal computer systems that rival the performance of expensive workstations. This technological prowess should be brought to bear on the educational process and， in particular， on effective teaching that can result in enhanced learning. This companion book on digital signal processing (DSP) makes a small contribution toward reaching that goal.The teaching methods in signal processing have changed over the years from the simple "lecture-only" format to a more integrated "lecture-laboratory" environment in which practical hands-on issues are taught using DSP hardware. However， for effective teaching of DSP the lecture component must also make extensive use of computer-based explanations，examples， and exercises. For the past several years， the MATLAB soft-ware developed by The Math Works， Inc. has established itself as the defacto standard for numerical computation in the signal-processing community and as a platform of choice for algorithm development. There are several reasons for this development， but the most important reason is that MATLAB is available on practically all-computing platforms. In this book we have made an attempt at integrating MATLAB with traditional
　　topics in DSP so that it can be used to explore difficult topics and solve problems to gain insight. Many problems or design algorithms in DSP
　　require considerable computation. It is for these that MATLAB provides a convenient tool so that many scenarios can be tried with ease. Such an approach can enhance the learning process.