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Proakis J. Digital Signal Processing. Solutions 4ed 2007
This book was developed based on our teaching of undergraduate- and graduate-level courses in digital signal processing over the past several years. In this book we present the fundamentals of discrete-time signals, systems, and modern digital processing as well as applications for students in electrical engineering, computer engineering, and computer science. The book is suitable for either a one-semester or a two-semester undergraduate-level course in discrete systems and digital signal processing. It is also intended for use in a one-semester first-year graduate-level course in digital signal processing. It is assumed that the student has had undergraduate courses in advanced calculus (including ordinary differential equations) and linear systems for continuous-time signals, including an introduction to the Laplace transform. Although the Fourier series and Fourier transforms of periodic and aperiodic signals are described in Chapter 4, we expect that many students may have had this material in a prior course. Balanced coverage of both theory and practical applications is provided. A large number of well-designed problems are provided to help the student in mastering the subject matter. A solutions manual is available for download for instructors only. Additionally, Microsoft PowerPoint slides of text figures are available for instructors on the publisher's website. In the fourth edition of the book, we have added a new chapter on adaptive filters and have substantially modified and updated the chapters on multirate digital signal processing and on sampling and reconstruction of signals. We have also added new material on the discrete cosine transform. In Chapter 1 we describe the operations involved in the analog-to-digital 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 (UR). 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 time-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. In Chapter 5, linear time-invariant (LTI) 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 AID 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 ARM A 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 non parametric and model-based (parametric) methods. Also described are eigen-decomposition-based methods, including MUSIC and ESPRIT. A one-semester senior-level course for students who have had prior exposure to discrete systems can use the material in Chapters 1 through 5 for a quick review and then proceed to cover Chapters 6 through 10. In a first-year graduate-level course in digital signal processing, the first six chapters provide the student with a good review of discrete-time systems. The instructor can move quickly through most of this material and then cover Chapters 7 through 11, followed by selected topics from Chapters 12 through 14. Many examples throughout the book and approximately 500 homework problems are included throughout the book. Answers to selected problems appear in the back of the book. Many of the homework problems can be solved numerically on a computer, using a software package such as MATLAB. Available for use as a self-study companion to the textbook is a student manual: Student Manual for Digital Signal Processing with MATLAB. MATLAB is incorporated as the basic software tool for this manual. The instructor may also wish to consider the use of other supplementary books that contain computer-based exercises, such as Computer-Based Exercisesfor Signal Processing Using MATLAB (Prentice Hall, 1994) by C. S. Burrus et al. Introduction. Discrete-Time Signals and Systems. The z-Transform and Its Application to the Analysis of LTI Systems. Frequency Analysis of Signals. Frequency-Domain Analysis of LTI Systems. Sampling and Reconstruction of Signals. The Discrete Fourier Transform: Its Properties and Applications. Efficient Computation of the OFT: Fast Fourier Transform Algorithms. Implementation of Discrete-Time Systems. Design of Digital Filters. Multirate Digital Signal Processing. Linear Prediction and Optimum Linear Filters. Adaptive Filters. Power Spectrum Estimation. A Random Number Generators. B Tables of Transition Coefficients for the Design of Linear-Phase FIR Filters
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Proakis J. Digital Signal Processing 4ed 2006.pdf
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Proakis J. Digital Signal Processing. Solutions 4ed 2007.pdf
