Applied Digital Signal Processing Theory and Practice

ISBN-10: 0521110025

ISBN-13: 9780521110020

Edition: 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.
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Book details

Copyright year: 2011
Publisher: Cambridge University Press
Publication date: 11/21/2011
Binding: Hardcover
Pages: 1008
Size: 7.25" wide x 9.75" long x 1.50" tall
Weight: 4.202
Language: English

Dimitris G. Manolakis is currently a Member of Technical Staff at MIT Lincoln Laboratory in Lexington, Massachusetts. Prior to this he was a Principal Member of Research Staff at Riverside Research Institute. Since receiving his Ph.D. in Electrical Engineering from the University of Athens in 1981, he has taught at various institutions including Northeastern University, Boston College, and Worcester Polytechnic Institute and co-authored two textbooks on signal processing. His research experience and interests include the areas of digital signal processing, adaptive filtering, array processing, pattern recognition, remote sensing and radar systems.

Vinay K. Ingle is an Associate Professor of Electrical and Computer Engineering at Northeastern University. He received his Ph.D. in electrical and computer engineering from Rensselaer Polytechnic Institute in 1981. He has broad research experience and has taught courses on topics including signal and image processing, stochastic processes, and estimation theory. Professor Ingle is coauthor of the books: DSP Laboratory Using the ADSP-2181 Microprocessor (Prentice-Hall, 1991), Discrete Systems Laboratory (Brooks-Cole, 2000), and Statistical and Adaptive Signal proc-essing (Artech House, 2005).

Preface
Introduction
Signals
Systems
Analog, digital, and mixed signal processing
Applications of digital signal processing
Book organization
Learning summary
Terms and concepts
Further reading
Review questions
Discrete-time signals and systems
Discrete-time signals
Signal generation and plotting in Matlab
Discrete-time systems
Convolution description of linear time-invariant systems
Properties of linear time-invariant systems
Analytical evaluation of convolution
Numerical computation of convolution
Red-time implementation of FTR filters
FTR spatial filters
Systems described by linear constant-coefficient difference equations
Continuous-time LIT systems
Learning summary
Terms and concepts
Further reading
Review questions
Problems
The z-transform
Motivation
The z-transform
The inverse z-transform
Properties of the z-transform
System function of LTI systems
LTT systems characterized by linear constant-coefficient difference equations
Connections between pole-zero locations and time-domain behavior
The one-sided z-transform
Learning summary
Terms and concepts
Further reading
Review questions
Problems
Fourier representation of signals
Sinusoidal signals and their properties
Fourier representation of continuous-time signals
Fourier representation of discrete-time signals
Summary of Fourier series and Fourier transforms
Properties of the discrete-time Fourier transform
Learning summary
Terms and concepts
Further reading
Review questions
Problems
Transform analysis of LTI systems
Sinusoidal response of LTI systems
Response of LTT systems in the frequency domain
Distortion of signals passing through LTI systems
Ideal and practical filters
Frequency response for rational system functions
Dependence of frequency response on poles and zeros
Design of simple filters by pole-zero placement
Relationship between magnitude and phase responses
Allpass systems
Invertibility and minimum-phase systems
Transform analysis of continuous-time LTI systems
Learning summary
Terms and concepts
Further reading
Review questions
Problems
Sampling of continuous-time signals
Ideal periodic sampling of continuous-time signals
Reconstruction of a bandlimited signal from its samples
The effect of undersampling: abasing
Discrete-time processing of continuous-time signals
Practical sampling and reconstruction
Sampling of bandpass signals
Image sampling and reconstruction
Learning summary
Terms and concepts
Further reading
Review questions
Problems
The Discrete Fourier Transform
Computational Fourier analysis
The Discrete Fourier Transform (DFT)
Sampling the Discrete-Time Fourier Transform
Properties of the Discrete Fourier Transform
Linear convolution using the DFT
Fourier analysis of signals using the DFT
Learning summary
Terms and concepts
Further reading
Review questions
Problems
Computation of the Discrete Fourier Transform
Direct computation of the Discrete Fourier Transform
The FFT idea using a matrix approach
Decimation-in-time FFT algorithms
Decimation-in-frequency FFT algorithms
Generalizations and additional FFT algorithms
Practical considerations
Computation of DFT for special applications
Learning summary
Terms and concepts
Further reading
Review questions
Problems
Structures for discrete-time systems
Block diagrams and signal flow graphs
IIR system structures
FIR system structures
Lattice structures
Structure conversion, simulation, and verification
Learning summary
Terms and concepts
Further reading
Review questions
Problems
Design of FIR filters
The filter design problem
FIR filters with linear phase
Design of FIR filters by windowing
Design of FTR filters by frequency sampling
Chebyshev polynomials and minimax approximation
Equiripple optimum Chebyshev FIR filter design
Design of some special FTR filters
Learning summary
Terms and concepts
Further reading
Review questions
Problems
Design of IIR filters
Introduction to IIR filter design
Design of continuous-time lowpass filters
Transformation of continuous-time filters to discrete-time LTR filters
Design examples for lowpass IIR. filters
Frequency transformations of lowpass filters
Design examples of IIR filters using Matlab
Learning summary
Terms and concepts
Further reading
Review questions
Problems
Multirate signal processing
Sampling rate conversion
Implementation of multirate systems
Filter design for multirate systems
Two-channel filter banks
Multichannel filter banks
Learning summary
Terms and concepts
Further reading
Review questions
Problems
Random signals
Probability models and random variables
Jointly distributed random variables
Covariance, correlation, and linear estimation
Random processes
Some useful random process models
Learning summary
Terms and concepts
Further reading
Review questions
Problems
Random signal processing
Estimation of mean, variance, and covariance
Spectral analysis of stationary processes
Optimum linear filters
Linear prediction and all-pole signal modeling
Optimum orthogonal transforms
Learning summary
Terms and concepts
Further reading
Review questions
Problems
Finite wordlength effects
Number representation
Statistical analysis of quantization error
Oversampling A/D and D/A conversion
Quantization of filter coefficients
Effects of finite wordlength on digital filters
Finite wordlength effects in FFT algorithms
Learning summary
Terms and concepts
Further reading
Review questions
Problems
References
Index
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