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《离散时间信号处理(第3版)(英文版)》：国外电子与通信教材系列

作者简介

作者：（美国）奥本海姆（Alan V.Oppenheim） （美国）谢弗（Ronald W.Schafer）

目录

Introduction
Discrete-Time Signals and Systems
2.0 Introduction
2.1 Discrete-Time Signals
2.2 Discrete-Time Systems
2.2.1 Memoryless Systems
2.2.2 Linear Systems
2.2.3 Time-Invariant Systems
2.2.4 Causality
2.2.5 Stability
2.3 LTI Systems
2.4 Properties of Linear Time-Invariant Systems
2.5 Linear Constant-Coefficient Difference Equations
2.6 Frequency-Domain Representation of Discrete-Time Signals and Systems
2.6.1 Eigenfunctions for Linear Time-Invariant Systems
2.6.2 Suddenly Applied Complex Exponential Inputs
2.7 Representation of Sequences by Fourier Transforms
2.8 Symmetry Properties of the Fourier Transform
2.9 Fourier Transform Theorems
2.9.1 Linearity of the Fourier Transform
2.9.2 Time Shifting and Frequency Shifting Theorem
2.9.3 Time Reversal Theorem
2.9.4 Differentiation in Frequency Theorem
2.9.5 Parseval's Theorem
2.9.6 The Convolution Theorem
2.9.7 The Modulation or Windowing Theorem
2.10 Discrete-Time Random Signals
2.11 Summary
Problems

The z-Transform
3.0 Introduction
3.1 z-Transform
3.2 Properties of the ROC for the z-Transform
3.3 The Inverse z-Transform
3.3.1 Inspection Method
3.3.2 Partial Fraction Expansion
3.3.3 Power Series Expansion
3.4 z-Transform Properties
3.4.1 Linearity
3.4.2 Time Shifting
3.4.3 Multiplication by an Exponential Sequence
3.4.4 Differentiation of X（z）" ~
3.4.5 Conjugation of a Complex Sequence
3.4.6 Time Reversal
3.4.7 Convolution of Sequences
3.4.8 Summary of Some z-Transform Properties
3.5 z-Transforms and LTI Systems
3.6 The Unilateral z-Transform
3.7 Summary
Problems

Sampling of Continuous-Time Signals
4.0 Introduction
4.1 Periodic Sampling
4.2 Frequency-Domain Representation of Sampling .
4.3 Reconstruction of a Bandlimited Signal from Its Samples
4.4 Discrete-Time Processing of Continuous-Time Signals
4.4.1 Discrete-Time LTI Processing of Continuous-Time Signals . .
4.4.2 Impulse Invariance
4.5 Continuous-Time Processing of Discrete-Time Signals
4.6 Changing the Sampling Rate Using Discrete-Time Processing
4.6.1 Sampling Rate Reduction by an Integer Factor
4.6.2 Increasing the Sampling Rate by an Integer Factor
4.6.3 Simple and Practical Interpolation Filters
4.6.4 Changing the Sampling Rate by a Noninteger Factor
4.7 Multirate Signal Processing
4.7.1 Interchange of Filtering with Compressor/Expander
4.7.2 Multistage Decimation and Interpolation
4.7.3 Polyphase Decompositions
4.7.4 Polyphase Implementation of Decimation Filters
4.7.5 Polyphase Implementation of Interpolation Filters
4.7.6 Multirate Filter Banks
4.8 Digital Processing of Analog Signals
4.8.1 Prefiltering to Avoid Aliasing
4.8.2 A/D Conversion
4.8.3 Analysis of Quantization Errors
4.8.4 D/A Conversion
4.9 Oversampling and Noise Shaping in A/D and D/A Conversion
4.9.1 Oversampled A/D Conversion with Direct Quantization
4.9.2 Oversampled A/D Conversion with Noise Shaping
4.9.3 Oversampling and Noise Shaping in D/A Conversion
4.10 Summary
Problems

Transform Analysis of Linear Time-Invariant Systems
5.0 Introduction
5.1 The Frequency Response of LTI Systems
5.1.1 Frequency Response Phase and Group Delay
5.1.2 Illustration of Effects of Group Delay and Attenuation
5.2 System Functions——Linear Constant-Coefficient Difference Equations
5.2.1 Stability and Causality
5.2.2 Inverse Systems
5.2.3 Impulse Response for Rational System Functions
5.3 Frequency Response for Rational System Functions
5.3.1 Frequency Response of lst-Order Systems
5.3.2 Examples with Multiple Poles and Zeros
5.4 Relationship between Magnitude and Phase
5.5 All-Pass Systems
5.6 Minimum-Phase Systems
5.6.1 Minimum-Phase and All-Pass Decomposition
5.6.2 Frequency-Response Compensation Of Non-Minimum-Phase Systems
5.6.3 Properties of Minimum-Phase Systems
5.7 Linear Systems with Generalized Linear Phase
5.7.1 Systems with Linear Phase
5.7.2 Generalized Linear Phase
5.7.3 Causal Generalized Linear-Phase Systems
5.7.4 Relation of FIR Linear-Phase Systems to Minimum-Phase Systems
5.8 Summary
Problems

Structures for Discrete-Time Systems
6.0 Introduction
6.1 Block Diagram Representation of Linear Constant-Coefficient Difference Equations
6.2 Signal Flow Graph Representation
6.3 Basic Structures for IIR Systems
6.3.1 Direct Forms
6.3.2 Cascade Form
6.3.3 Parallel Form
6.3.4 Feedback in IIR Systems
6.4 Transposed Forms
6.5 Basic Network Structures for FIR Systems
6.5.1 Direct Form
6.5.2 Cascade Form
6.5.3 Structures for Linear-Phase FIR Systems
6.6 Lattice Filters
6.6.1 FIR Lattice Filters
6.6.2 All-Pole Lattice Structure
6.6.3 Generalization of Lattice Systems
6.7 Overview of Finite-Precision Numerical Effects
6.7.1 Number Representations
6.7.2 Quantization in Implementing Systems
6.8 The Effects of Coefficient Quantization
6.8.1 Effects of Coefficient Quantization in IIR Systems
6.8.2 Example of Coefficient Quantization in an Elliptic Filter
6.8.3 Poles of Quantized 2hal-Order Sections
6.8.4 Effects of Coefficient Quantization in FIR Systems
6.8.5 Example of Quantization of an Optimum FIR Filter
6.8.6 Maintaining Linear Phase
6.9 Effects of Round-off Noise in Digital Filters
6.9.1 Analysis of the Direct Form IIR Structures
6.9.2 Scaling in Fixed-Point Implementations of IIR Systems
6.9.3 Example of Analysis of a Cascade IIR Structure
6.9.4 Analysis of Direct-Form FIR Systems
6.9.5 Floating-Point Realizations of Discrete-Time Systems
6.10 Zero4nput Limit Cycles in Fixed-Point Realizations of IIR Digital Filters
6.10.1 Limit Cycles Owing to Round-off and Truncation
6.10.2 Limit Cycles Owing to Overflow
6.10.3 Avoiding Limit Cycles
6.11 Summary
Problems

Filter Design Techniques
7.0 Introduction
7.1 Filter Specifications
……
The Discrete Fourier Tranaform
Computation of the Discrete Fourier Transform
Fourier Analysis of Signals Using the Discrete Fourier Transform
Parametric Signal Modeling
Discrete Hilbert Transforms

序言

2001年7月间，电子工业出版社的领导同志邀请各高校十几位通信领域方面的老师，商量引进国外教材问题。与会同志对出版社提出的计划十分赞同，大家认为，这对我国通信事业、特别是对高等院校通信学科的教学工作会很有好处。
教材建设是高校教学建设的主要内容之一。编写、出版一本好的教材，意味着开设了一门好的课程，甚至可能预示着一个崭新学科的诞生。20世纪40年代MIT林肯实验室出版的一套28本雷达丛书，对近代电子学科、特别是对雷达技术的推动作用，就是一个很好的例子。
我国领导部门对教材建设一直非常重视。20世纪80年代，在原教委教材编审委员会的领导下，汇集了高等院校几百位富有教学经验的专家，编写、出版了一大批教材；很多院校还根据学校的特点和需要，陆续编写了大量的讲义和参考书。这些教材对高校的教学工作发挥了极好的作用。近年来，随着教学改革不断深入和科学技术的飞速进步，有的教材内容已比较陈旧、落后，难以适应教学的要求，特别是在电子学和通信技术发展神速、可以讲是日新月异的今天，如何适应这种情况，更是一个必须认真考虑的问题。解决这个问题，除了依靠高校的老师和专家撰写新的符合要求的教科书外，引进和出版一些国外优秀电子与通信教材，尤其是有选择地引进一批英文原版教材，是会有好处的。

文摘

插图：



Another important implication of the FFT was that it was an inherently discrete-time concept. It was directed toward the computation of the Fourier transform of adiscrete-time signal or sequence and involved a set of properties and mathematicsthat was exact in the discrete-time domain it was not simply an approximation toa continuous-time Fourier transform. This had the effect of stimulating a reformulationof many signal processing concepts and algorithms in terms of discrete-time mathemat-ics, and these techniques then formed an exact set of relationships in the discrete-timedomain. Following this shift away from the notion that signal processing on a digitalcomputer was merely an approximation to analog signal processing techniques, thereemerged the current view that discrete-time signal processing is an important field ofinvestigation in its own right.
Another major development in the history of discrete-time signal processing oc-curred in the field of microelectronics. The invention and subsequent proliferation ofthe microprocessor paved the way for low-cost implementations of discrete-time signalprocessing systems. Although the first microprocessors were too slow to implement mostdiscrete-time systems in real time except at very low sampling rates, by the mid-1980s,integrated circuit technology had advanced to a level that permitted the implementationof very fast fixed-point and floating-point microcomputers with architectures speciallydesigned for implementing discrete-time signal processing algorithms. With this tech-nology came, for the first time, the possibility of widespread application of discrete-timesignal processing techniques. The rapid pace of development in microelectronics alsosignificantly impacted the development of signal processing algorithms in other ways.For example, in the early days of real-time digital signal processing devices, memorywas relatively costly and one of the important metrics in developing signal processingalgorithms was the efficient use of memory. Digital memory is now so inexpensive thatmany algorithms purposely incorporate more memory than is absolutely required sothat the power requirements of the processor are reduced. Another area in which tech-nology limitations posed a significant barrier to widespread deployment of DSP was inconversion of signals from analog to discrete-time （digital） form. The first widely avail-able A/D and D/A converters were stand-a
one devices costing thousands of dollars.By combining digital signal processing theory with microelectronic technology, over-sampled A/D and D/A converters costing a few dollars or less have enabled a myriadof real-time applications.

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