Introduction to Digital Signal Processing,9780123984203

Introduction to Digital Signal Processing

by
ISBN13: 9780123984203
ISBN10: 0123984203
Format: Hardcover
Pub. Date: 1989-07-01
Publisher(s): Academic Pr
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Summary

An Introduction to Digital Signal Processing is written for those who need to understand and use digital signal processing and yet do not wish to wade through a multi-semester course sequence. Using only calculus-level mathematics, this book progresses rapidly through the fundamentals to advanced topics such as iterative least squares design of IIR filters, inverse filters, power spectral estimation, and multidimensional applications--all in one concise volume. This book emphasizes both the fundamental principles and their modern computer implementation. It presents and demonstrates how simple the actual computer code is for advanced modern algorithms used in DSP. Results of these programs, which the reader can readily duplicate and use on a PC, are presented in many actual computer drawn plots. Key Features * assumes no previous knowledge of signal processing but leads up to very advanced techniques combines exposition of fundamental principles with practical applications * includes problems with each chapter * presents in detail the appropriate computer algorithums for solving problems

Table of Contents

Preface xi
Signals and Systems
Sampling and Aliasing
4(4)
Linear Time-Invariant Systems and the Convolution Operation
8(10)
Constant-Coefficient Difference Equations
18(3)
System Block Diagrams and Flow Graphs
21(3)
Problems
24(3)
Sampled Data and the Z Transform
The Z Transform, Polynomial Multiplication, and Convolution
27(2)
Factoring Z Transforms into Couplets
29(1)
Inverse Operators: Stability, Causality, and Minimum Phase
30(7)
Problems
37(5)
Sinusoidal Response of LSI Systems
Sinusoidal Signals as Eigenfunctions and the Spectrum as Eigenvalues
42(2)
Frequency Response of Some Simple LSI Systems
44(6)
Frequency Response of Digital Differential and Integral Operators
50(3)
The Bilinear Transform and Its Application to Differential Equations
53(7)
Problems
60(5)
Couplets and Elementary Filters
The Single-Zero Couplet
65(4)
The Single-Pole Couplet
69(2)
The Single-Zero, Single-Pole, Allpass Filter
71(3)
Elementary Filters Classified by Their Poles and Zeros
74(2)
Problems
76(3)
The Discrete Fourier Transform
Sampling the System Response in the Frequency Domain
79(3)
Properties of the DFT
82(4)
Special Values of the DFT
86(1)
The Phase-Shift Theorem
87(1)
The Convolution Theorem
88(3)
Cross-Correlation and Autocorrelation
91(2)
Problems
93(5)
The Continuous Fourier Integral Transform
The Fourier Integral Transform Developed from the DFT
98(4)
Properties of the Fourier Integral Transform
102(2)
The Wiener--Khintchine Theorem
104(2)
The Time-Limited Band-Limited Theorem
106(1)
A Repertoire of Transforms and Their Importance
107(17)
Problems
124(4)
Application of the Fourier Transform to Digital Signal Processing
Continuous Time, Discrete Frequency: The Fourier Series
128(3)
The Least-Squares Convergence of the Fourier Series
131(2)
The Sampling Function
133(2)
The Relationship between the FT and the DFT: Resolution and Leakage
135(8)
Interpolation, Decimation, and Multiplexing
143(6)
Digital Control Systems
149(11)
Problems
160(7)
Digital Filter Design
Digital Filter Design---The Problem
167(4)
Designing FIR Filters Using Windows
171(4)
Frequency Sampling and the Parks--McClellan Algorithm
175(7)
Recursive Filters
182(3)
Digitizing Rational Functions of ω
185(5)
DFT Frequency Filtering
190(2)
Problems
192(6)
Inverse Filtering and Deconvolution
Exact Inverses via the DFT
198(5)
Linear Deconvolution---The Problem
203(3)
Winear Least-Squares Filters
206(2)
Application to Inverses
208(3)
Filter Delay Properties
211(2)
Applications to Prediction Filters
213(4)
Matched Filters and Output Energy Filters
217(8)
The Levinson Recursion
225(3)
Appendix: The Least-Squares Property of Wiener Filters
228(2)
Problems
230(6)
Spectral Factorization
The Root Method
236(2)
The Spectrum of a Real Causal Function
238(4)
Kolmogoroff Factorization
242(3)
Least-Squares Zero-Delay Factorization
245(1)
Iterative Least-Squares Factorization
246(4)
Applications to IIR Filter Design
250(3)
Problems
253(8)
Power Spectral Estimation
Signal-Like and Noise-Like Processes---The PSD Problem
261(6)
The MA Model: The Approach of Blackman and Tukey
267(4)
The AR Model: The Approach of Yule--Walker and Burg
271(8)
The Maximum Entropy Principle
279(5)
Other Data Models
284(3)
Problems
287(7)
Multidimensional DSP
Multidimensional Difference Equations
294(16)
Fourier Transform Methods in Multidimensions
310(10)
Two-Dimensional FIR Frequency Filter Design
320(6)
Problems
326(7)
References 333(2)
Index 335

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