Discrete-Time Signal Processing

by Oppenheim, Alan V.; Schafer, Ronald W.

• ISBN13: 9780131988422
• ISBN10: 0131988425
• eBook ISBN(s): 9780133002287
• Additional ISBN(s): 9780137549207
• Edition: 3rd
• Format: Hardcover
• Copyright: 2009-08-18
• Publisher: Pearson
• More Book Details

Summary

THE definitive, authoritative guide to DSP - ideal for those with an introductory-level knowledge of signals and systems - but not necessarily DSP. Written by a prominent, standard-setting team.Provides thorough treatment of the fundamental theorems and properties of discrete-time linear systems, filtering, sampling, and discrete-time Fourier Analysis. Focuses on the general and universal concepts in discrete-time signal processing -- making the content vital and relevant to the new challenges arising in the field -withoutlimiting itself to specific technologies with relatively short life spans. Discusses the wide range of present and future applications of the technology, and features a wealth of examples.For anyone wanting a thorough introduction to Discrete-Time Signal Processing.

Table of Contents

Previous edition TOC

Introduction

Discrete-Time Signals and Systems

Introduction

Discrete-time Signals: Sequences

Discrete-time Systems

Linear Time-Invariant Systems

Properties of Linear Time-Invariant Systems

Linear Constant-Coefficient Difference Equations

Frequency-Domain Representation of Discrete-Time Signals and Systems

Representation of Sequence by Fourier Transforms

Symmetry Properties of the Fourier Transform

Fourier Transform Theorems

Discrete-Time Random Signals

Summary

The z-Transform

Introduction

The z-Transform

Properties of the Region of Convergence for the z-Transform

The Inverse z-Transform

z-Transform Properties

Summary

Sampling of Continuous-Time Signals

Introduction

Periodic Sampling

Frequency-Domain Representation of Sampling

Reconstruction of a Bandlimited Signal from its Samples

Discrete-Time Processing of Continuous-Time Signals

Continuous-Time Processing of Discrete-Time Signals

Changing the Sampling Rate Using Discrete-Time Processing

Practical Considerations

Oversampling and Noise Shaping

Summary

Transform Analysis of Linear Time-Invariant Systems

Introduction

The Frequency Response of LTI Systems

System Functions for Systems Characterized by Linea

Frequency Response for Rational System Functions

Relationship Between Magnitude and Phase

All-Pass Systems

Minimum-Phase Systems

Linear Systems with Generalized Linear Phase

Summary

Structures for Discrete-Time Systems

Introduction

Block Diagram Representation of Linear Constant-Coefficient Difference Equations

Signal Flow Graph Representation of Linear Constant-Coefficient Difference Equations

Basic Structures for IIR Systems

Transposed Forms

Basic Network Structures for FIR Systems

Overview of Finite-Precision Numerical Effects

The Effects of Coefficient Quantization

Effects of Roundoff Noise in Digital Filters

Zero-Input Limit Cycles in Fixed-Point Realizations of IIR Digital Filters

Summary

Filter Design Techniques

Introduction

Design of Discrete-Time IIR Filters from Continuous-Time Filters

Design of FIR Filters by Windowing

Examples of FIR Filter Design by the Kaiser Window Method

Optimum Approximations of FIR Filters

Examples of FIR Equiripple Approximation

Comments on IIR and FIR Digital Filters

Summary

The Discrete Fourier Transform

Introduction

Representation of Periodic Sequences: the Discrete Fourier Series

Summary of Properties of the DFS Representation of Periodic Sequences

The Fourier Transform of Periodic Signals

Sampling the Fourier Transform

Fourier Representation of Finite-Duration Sequences: The Discrete-Fourier Transform

Properties of the Discrete Fourier Transform

Summary of Properties of the Discrete Fourier Transform

Linear Convolution Using the Discrete Fourier Transform

The Discrete Cosine Transform (DCT)

Summary

Computation of the Discrete Fourier Transform

Introduction

Efficient Computation of the Discrete Fourier Transform

The Goertzel Algorithm Decimation-in-Time FFT Algorithms

Decimation-in-Frequency FFT Algorithms

Practical Considerations Implementation of the DFT Using Convolution

Summary

Fourier Analysis of Signals Using the Discrete Fourier Transform

Introduction

Fourier Analysis of Signals Using the DFT

DFT Analysis of Sinusoidal Signals

The Time-Dependent Fourier Transform

Block Convolution Using the Time-Dependent Fourier Transform

Fourier Analysis of Nonstationary Signals

Fourier Analysis of Stationary Random Signals: the Periodogram

Spectrum Analysis of Random Signals Using Estimates of the Autocorrelation Sequence

Summary

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