John G. Proakis and Dimitris G. Manolakis
DIGITAL SIGNAL PROCESSING: Principles, Algorithms, and
Applications, 4/e
Hardcover, pp 1084 plus xvi
Pearson Prentice Hall, Pearson Education, Inc.
Upper Saddle River, NJ 07458, 2007
ISBN 0-13-187374-1
About the book
Digital signal processing is today one of the most interesting domain of applied electronics, not only for experts but also for students of the electrical engineering faculties and others who want to understand work of modern electronics gadgets.
This book presents the fundamentals of discrete-time signals, systems, and modern digital processing algorithms and applications for students in electrical engineering, computer engineering, and computer science.
Giving the reader a sound balance of theory and practical application, this book presents the fundamental concepts and techniques of modern digital signal processing with related algorithms and applications. Covering both time-domain and frequency- domain methods for the analysis of linear, discrete-time systems, the book offers cutting-edge coverage on such topics as sampling, digital filter design, filter realizations, deconvolution, interpolation, decimation, state-space methods, spectrum analysis, and more. Rigorous and challenging, it furthers the understanding with numerous examples, exercises, and experiments emphasizing software implementation of digital signal processing algorithms integrated throughout.
Chapter content
In Chapter 1 we describe the operations involved in the analog-to-digilal conversion of analog signals. The process of sampling a sinusoid is described in some detail and the problem of aliasing is explained. Signal quantization and digital-to-analog conversion are also described in general terms, but the analysis is presented in subsequent chapters.
Chapter 2 is devoted entirely to the characterization and analysis of linear time-invariant (shift-invariant) discrete-time systems and discrete-time signals in the time domain. The convolution sum is derived and systems are categorized according to the duration of their impulse response as a finite-duration impulse response (FIR) and as an infinite-duration impulse response (IIR). Linear time-invariant systems characterized by difference equations are presented and the solution of difference equations with initial conditions is obtained. The chapter concludes with a treatment of discrete-time correlation.
The z-transform is introduced in Chapter 3. Both the bilateral and the unilateral z-transforms are presented, and methods for determining the inverse z-transform are described. Use of the z-transform in the analysis of linear lime-invariant systems is illustrated, and important properties of systems, such as causality and stability, are related to z-domain characteristics.
Chapter 4 treats the analysis of signals in the frequency domain. Fourier series and the Fourier transform are presented for both continuous-time and discrete-time signals. Mp>In Chapter 5, linear time-invariant (LT1) discrete systems are characterized in the frequency domain by their frequency response function and their response to periodic and aperiodic signals is determined. A number of important types of discrete-time systems are described, including resonators, notch filters, comb filters, all-pass filters, and oscillators. The design of a number of simple FIR and IIR filters is also considered In addition, the student is introduced to the concepts of minimum-phase, mixed-phase, and maximum-phase systems and to the problem of deconvolution.
Chapter 6 provides a thorough treatment of sampling of continuous-time signals and the reconstruction of the signals from their samples. Our coverage includes the sampling and reconstruction of bandpass signals, the sampling of discrete-time signals, and A/D and D/A conversion. The chapter concludes with the treatment of oversampling A/D and D/A converters.
The DFT, its properties and its applications, are the topics covered in Chapter 7. Two methods are described for using the DFT to perform linear filtering. The use of the DFT to perform frequency analysis of signals is also described. The final topic treated in this chapter is the discrete cosine transform.
Chapter 8 covers the efficient computation of the DFT. Included in this chapter are descriptions of radix-2, radix-4, and split-radix fast Fourier transform (FFT) algorithms, and applications of the FFT algorithms to the computation of convolution and correlation. The Goertzel algorithm and the chirp-z transform are introduced as two methods for computing the DFT using linear filtering.
Chapter 9 treats the realization of IIR and FIR systems. This treatment includes direct-form, cascade, parallel, lattice, and lattice-ladder realizations. The chapter also examines quantization effects in a digital implementation of FIR and IIR systems.
Techniques for design of digital FIR and IIR filters are presented in Chapter 10. The design techniques include both direct methods in discrete time and methods involving the conversion of analog filters into digital filters by various transformations.
Chapter 11 treats sampling-rate conversion and its applications to multirate digital signal processing. In addition to describing decimation and interpolation by integer and rational factors, we describe methods for sampling-rate conversion by an arbitrary factor and implementations by polyphase filter structures. This chapter also treats digital filter banks, two-channel quadrature mirror filters (QMF) and M-channel QMF banks.
Linear prediction and optimum linear (Wiener) filters are treated in Chapter 12. Also included in this chapter are descriptions of the Levinson-Durbin algorithm and Schur algorithm for solving the normal equations, as well as the AR lattice and ARMA lattice-ladder filters.
Chapter 13 treats single-channel adaptive filters based on the LMS algorithm and on recursive least squares (RLS) algorithms. Both direct form FIR and lattice RLS algorithms and filter structures are described.
Power spectrum estimation is the main topic of Chapter 14. Our coverage includes a description of nonparametric and model-based (parametric) methods. Also described arc eigen-decomposition-based methods, including MUSIC and ESPRTT.
Many examples troughput the book and appximately 500 homework problems are included trough the book. Answer to selected problems appears in the bak of the book. Many of the homework problems can be solved numerically on a computer, using a software pakacge suc as a MATLAB©.
Useful book for Students
DIGITAL SIGNAL PROCESSING: Principles, Algorithms, and Applications is s useful book. In general it provides a comprehensive, systematic, and clear coverage of the basic digital signal processing.
The book is a well written source for fundamental concepts and method in the area of digital signal processing, an prepares the reader for further reading in the literature associated with this subject. It is a good source for both undergraduate students in DSP, and wider audience of engineers and researchers who in any way use algorithm for digital signal processing and make some kind of applications.
Therefore, I would certainly fully recommended it to ungraduate and graduate students of electrical engineering and computer science, and researchers looking for very up to date text on digital signal processing. A really good book to start with.
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