Applied Digital Signal Processing: Theory and Practice

, by Dimitris G. Manolakis , Vinay K. Ingle

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ISBN: 9780521110020 | 0521110025
Cover: Hardcover
Copyright: 11/21/2011

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Master the basic concepts and methodologies of digital signal processing with this systematic introduction, without the need for an extensive mathematical background. The authors lead the reader through the fundamental mathematical principles underlying the operation of key signal processing techniques, providing simple arguments and cases rather than detailed general proofs. Coverage of practical implementation, discussion of the limitations of particular methods and plentiful MATLAB illustrations allow readers to better connect theory and practice. A focus on algorithms that are of theoretical importance or useful in real-world applications ensures that students cover material relevant to engineering practice, and equips students and practitioners alike with the basic principles necessary to apply DSP techniques to a variety of applications. Chapters include worked examples, problems and computer experiments, helping students to absorb the material they have just read. Lecture slides for all figures and solutions to the numerous problems are available to instructors.

Preface	p. xiii
Introduction	p. 1
Signals	p. 2
Systems	p. 9
Analog, digital, and mixed signal processing	p. 13
Applications of digital signal processing	p. 16
Book organization	p. 18
Learning summary	p. 20
Terms and concepts	p. 20
Further reading	p. 21
Review questions	p. 21
Discrete-time signals and systems	p. 23
Discrete-time signals	p. 24
Signal generation and plotting in Matlab	p. 27
Discrete-time systems	p. 31
Convolution description of linear time-invariant systems	p. 37
Properties of linear time-invariant systems	p. 45
Analytical evaluation of convolution	p. 50
Numerical computation of convolution	p. 55
Red-time implementation of FTR filters	p. 57
FTR spatial filters	p. 59
Systems described by linear constant-coefficient difference equations	p. 61
Continuous-time LIT systems	p. 69
Learning summary	p. 75
Terms and concepts	p. 75
Further reading	p. 78
Review questions	p. 78
Problems	p. 79
The z-transform	p. 89
Motivation	p. 90
The z-transform	p. 91
The inverse z-transform	p. 99
Properties of the z-transform	p. 103
System function of LTI systems	p. 106
LTT systems characterized by linear constant-coefficient difference equations	p. 110
Connections between pole-zero locations and time-domain behavior	p. 114
The one-sided z-transform	p. 118
Learning summary	p. 121
Terms and concepts	p. 122
Further reading	p. 123
Review questions	p. 123
Problems	p. 124
Fourier representation of signals	p. 134
Sinusoidal signals and their properties	p. 135
Fourier representation of continuous-time signals	p. 142
Fourier representation of discrete-time signals	p. 157
Summary of Fourier series and Fourier transforms	p. 169
Properties of the discrete-time Fourier transform	p. 171
Learning summary	p. 188
Terms and concepts	p. 189
Further reading	p. 191
Review questions	p. 191
Problems	p. 192
Transform analysis of LTI systems	p. 201
Sinusoidal response of LTI systems	p. 202
Response of LTT systems in the frequency domain	p. 210
Distortion of signals passing through LTI systems	p. 215
Ideal and practical filters	p. 221
Frequency response for rational system functions	p. 224
Dependence of frequency response on poles and zeros	p. 231
Design of simple filters by pole-zero placement	p. 237
Relationship between magnitude and phase responses	p. 247
Allpass systems	p. 249
Invertibility and minimum-phase systems	p. 254
Transform analysis of continuous-time LTI systems	p. 258
Learning summary	p. 274
Terms and concepts	p. 275
Further reading	p. 276
Review questions	p. 277
Problems	p. 278
Sampling of continuous-time signals	p. 292
Ideal periodic sampling of continuous-time signals	p. 293
Reconstruction of a bandlimited signal from its samples	p. 297
The effect of undersampling: abasing	p. 300
Discrete-time processing of continuous-time signals	p. 311
Practical sampling and reconstruction	p. 318
Sampling of bandpass signals	p. 327
Image sampling and reconstruction	p. 333
Learning summary	p. 339
Terms and concepts	p. 340
Further reading	p. 341
Review questions	p. 342
Problems	p. 343
The Discrete Fourier Transform	p. 353
Computational Fourier analysis	p. 354
The Discrete Fourier Transform (DFT)	p. 357
Sampling the Discrete-Time Fourier Transform	p. 363
Properties of the Discrete Fourier Transform	p. 374
Linear convolution using the DFT	p. 392
Fourier analysis of signals using the DFT	p. 396
Learning summary	p. 418
Terms and concepts	p. 419
Further reading	p. 421
Review questions	p. 422
Problems	p. 423
Computation of the Discrete Fourier Transform	p. 434
Direct computation of the Discrete Fourier Transform	p. 435
The FFT idea using a matrix approach	p. 436
Decimation-in-time FFT algorithms	p. 440
Decimation-in-frequency FFT algorithms	p. 450
Generalizations and additional FFT algorithms	p. 454
Practical considerations	p. 456
Computation of DFT for special applications	p. 459
Learning summary	p. 470
Terms and concepts	p. 470
Further reading	p. 472
Review questions	p. 473
Problems	p. 474
Structures for discrete-time systems	p. 485
Block diagrams and signal flow graphs	p. 486
IIR system structures	p. 488
FIR system structures	p. 501
Lattice structures	p. 511
Structure conversion, simulation, and verification	p. 519
Learning summary	p. 522
Terms and concepts	p. 522
Further reading	p. 524
Review questions	p. 525
Problems	p. 526
Design of FIR filters	p. 537
The filter design problem	p. 538
FIR filters with linear phase	p. 544
Design of FIR filters by windowing	p. 556
Design of FTR filters by frequency sampling	p. 573
Chebyshev polynomials and minimax approximation	p. 582
Equiripple optimum Chebyshev FIR filter design	p. 586
Design of some special FTR filters	p. 601
Learning summary	p. 608
Terms and concepts	p. 608
Further reading	p. 610
Review questions	p. 610
Problems	p. 612
Design of IIR filters	p. 624
Introduction to IIR filter design	p. 625
Design of continuous-time lowpass filters	p. 627
Transformation of continuous-time filters to discrete-time LTR filters	p. 653
Design examples for lowpass IIR. filters	p. 668
Frequency transformations of lowpass filters	p. 673
Design examples of IIR filters using Matlab	p. 680
Learning summary	p. 687
Terms and concepts	p. 687
Further reading	p. 689
Review questions	p. 689
Problems	p. 691
Multirate signal processing	p. 705
Sampling rate conversion	p. 706
Implementation of multirate systems	p. 727
Filter design for multirate systems	p. 736'
Two-channel filter banks	p. 746
Multichannel filter banks	p. 759
Learning summary	p. 764
Terms and concepts	p. 764
Further reading	p. 766
Review questions	p. 766
Problems	p. 768
Random signals	p. 777
Probability models and random variables	p. 778
Jointly distributed random variables	p. 786
Covariance, correlation, and linear estimation	p. 792
Random processes	p. 796
Some useful random process models	p. 809
Learning summary	p. 815
Terms and concepts	p. 816
Further reading	p. 818
Review questions	p. 818
Problems	p. 820
Random signal processing	p. 829
Estimation of mean, variance, and covariance	p. 830
Spectral analysis of stationary processes	p. 834
Optimum linear filters	p. 858
Linear prediction and all-pole signal modeling	p. 866
Optimum orthogonal transforms	p. 877
Learning summary	p. 884
Terms and concepts	p. 885
Further reading	p. 886
Review questions	p. 887
Problems	p. 888
Finite wordlength effects	p. 902
Number representation	p. 903
Statistical analysis of quantization error	p. 909
Oversampling A/D and D/A conversion	p. 919
Quantization of filter coefficients	p. 928
Effects of finite wordlength on digital filters	p. 936
Finite wordlength effects in FFT algorithms	p. 950
Learning summary	p. 952
Terms and concepts	p. 953
Further reading	p. 954
Review questions	p. 955
Problems	p. 956
References	p. 968
Index	p. 977
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Applied Digital Signal Processing: Theory and Practice

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