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Tables of Contents for Digital Signal Processing
Chapter/Section Title
Page #
Page Count
Preface
xi
 
Introduction
1
5
Discrete-Time Signals and Systems
6
39
Introduction
6
2
Discrete-Time Signals-Sequences
8
3
Linear Shift-Invariant Systems
11
2
Stability and Causality
13
3
Linear Constant-Coefficient Difference Equations
16
2
Frequency-Domain Representation of Discrete-Time Systems and Signals
18
6
Some Symmetry Properties of the Fourier Transform
24
2
Sampling of Continuous-Time Signals
26
4
Two-Dimensional Sequences and Systems
30
15
Summary
34
1
Problems
35
10
The Z-Transform
45
42
Introduction
45
1
z-Transform
45
7
Inverse z-Transform
52
6
z-Transform Theorems and Properties
58
9
System Function
67
6
Two-Dimensional Z-Transform
73
14
Summary
77
1
Problems
78
9
The Discrete Fourier Transform
87
49
Introduction
87
1
Representation of Periodic Sequences-The Discrete Fourier Series
88
3
Properties of the Discrete Fourier Series
91
4
Summary of Properties of the DFS Representation of Periodic Sequences
95
1
Sampling the z-Transform
96
3
Fourier Representation of Finite-Duration Sequences--The Discrete Fourier Transform
99
2
Properties of the Discrete Fourier Transform
101
9
Summary of Properties of the Discrete Fourier Transform
110
1
Linear Convolution Using the Discrete Fourier Transform
110
5
Two-Dimensional Discrete Fourier Transform
115
21
Summary
121
1
Problems
121
15
Flow Graph and Matrix Representation of Digital Filters
136
59
Introduction
136
1
Signal Flow Graph Representation of Digital Networks
137
6
Matrix Representation of Digital Networks
143
5
Basic Network Structures for IIR Systems
148
5
Transposed Forms
153
2
Basic Network Structures for FIR Systems
155
10
Parameter Quantization Effects
165
8
Tellegen's Theorem for Digital Filters and Its Applications
173
22
Summary
181
1
Problems
182
13
Digital Filter Design Techniques
195
89
Introduction
195
2
Design of IIR Digital Filters from Analog Filters
197
14
Design Examples: Analog-Digital Transformation
211
19
Computer-Aided Design of IIR Digital Filters
230
7
Properties of FIR Digital Filters
237
2
Design of FIR Filters Using Windows
239
11
Computer-Aided Design of FIR Filters
250
18
A Comparison of IIR and FIR Digital Filters
268
16
Summary
269
2
Problems
271
13
Computation of the Discrete Fourier Transform
284
53
Introduction
284
3
Goertzel Algorithm
287
4
Decimation-in-Time FFT Algorithms
291
11
Decimation-in-Frequency FFT Algorithms
302
5
FFT Algorithms for N a Composite Number
307
8
General Computational Considerations in FFT Algorithms
315
6
Chirp Z-Transform Algorithm
321
16
Summary
326
2
Problems
328
9
Discrete Hilbert Transforms
337
39
Introduction
337
2
Real- and Imaginary-part Sufficiency for Causal Sequences
339
6
Minimum-Phase Condition
345
8
Hilbert Transform Relations for the DFT
353
5
Hilbert Transform Relations for Complex Sequences
358
18
Summary
365
2
Problems
367
9
Discrete Random Signals
376
28
Introduction
376
1
A Discrte-Time Random Process
377
5
Averages
382
6
Spectrum Representations of Infinite-Energy Signals
388
3
Response of Linear Systems to Random Signals
391
13
Summary
395
1
Problems
395
9
Effects of Finite Register Length in Digital Signal Processing
404
76
Introduction
404
2
Effect on Number Representation on Quantization
406
7
Quantization in Sampling Analog Signals
413
5
Finite-Register-Length Effects in Realizations of IIR Digital Filters
418
20
Finite-Register-Length Effects in Realizations of FIR Digital Filters
438
6
Effects of Finite Register Length in Discrete Fourier Transform Computations
444
36
Summary
462
2
Problems
464
16
Homomorphic Signal Processing
480
52
Introduction
480
1
Generalized Superposition
481
3
Multiplicative Homomorphic System
484
3
Homomorphic Image Processing
487
3
Homomorphic Systems for Convolution
490
10
Properties of the Complex Cepstrum
500
7
Computational Realizations of the Characteristic Syste D
507
4
Applications of Homomorphic Deconvolution
511
21
Summary
527
2
Problems
529
3
Power Spectrum Estimation
532
45
Introduction
532
1
Basic Principles of Estimation Theory
533
6
Estimates of the Autocovariance
539
2
The Periodogram as an Estimate of the Power Spectrum
541
7
Smoothed Spectrum Estimators
548
6
Estimates of the Cross Covariance and Cross Spectrum
554
1
Application of the FFT in Spectrum Estimation
555
7
Example of Spectrum Estimation
562
15
Summary
571
1
Problems
571
6
Index
577