Монография.
Издательство: McGraw Hill Professional, 1999. - 432 стр.
Язык: Английский.
ISBN 10: 0070273898,
ISBN 13: 978-0070273894This book is concerned with the fundamentals of digital signal processing, and there are two ways that the reader may use this book to learn about DSP. First, it may be used as a supplement to any one of a number of excellent DSP textbooks by providing the reader with a rich source of worked problems and examples. Alternatively, it may be used as a self-study guide to DSP, using the method of learning by example. With either approach, this book has been written with the goal of providing the reader with a broad range of problems having different levels of difficulty. In addition to problems that may be considered drill, the reader will find more challenging problems that require some creativity in their solution, as well as problems that explore practical applications such as computing the payments on a home mortgage. When possible, a problem is worked in several different ways, or alternative methods of solution are suggested.
The nine chapters in this book cover what is typically considered to be the core material for an introductory course in DSP. The first chapter introduces the basics of digital signal processing, and lays the foundation for the material in the following chapters. The topics covered in this chapter include the description and characterization of discrete-type signals and systems, convolution, and linear constant coefficient difference equations. The second chapter considers the representation of discrete-time signals in the frequency domain. Specifically, it introduces the discrete-time Fourier transform (DTFT), develops a number of DTFT properties, and explains how the DTFT may be used to solve difference equations and perform convolutions. Chapter 3 covers the important issues associated with sampling continuous-time signals. Of primary importance in this chapter are the sampling theorem, and the notion of aliasing. In Chapter 4, the z-transform is developed, which is the discrete-time equivalent of the Laplace transform for continuous-time signals. Then, Chapter 5 looks at the system function, which is the z-transform of the unit sample response of a linear shift-invariant system, and introduces a number of different types of systems, such as all-pass, linear phase, and minimum phase filters, and feedback systems.
The next two chapters are concerned with the Discrete Fourier Transform (DFT). Chapter 6 introduces the DFT, and develops a number of DFT properties. The key idea in this chapter is that multiplying the DFTs of two sequences corresponds to circular convolution in the time domain. Then, Chapter 7 considers a number of efficient algorithms for computing the DFT of a finite- length sequence. These algorithms are referred to, generically, as fast Fourier transforms (FFTs). Finally, the last two chapters address the design and implementation of discrete-time systems.
Chapter 8 considers different ways to implement linear shift-invariant discrete-time systems, and looks at the sensitivity of these implementations to filter coefficient quantization. In addition, it analyzes the propagation of round-off noise in fixed-point implementations of these systems. Chapter 9 addresses techniques for designing FIR and IIR linear shift-invariant filters. Although the primary focus is on the design of low-pass filters, techniques for designing other frequency selective filters, such as high-pass, band-pass, and band-stop filters are also considered.Signals and Systems
Fourier Analysis
The Z-Transform
Transform Analysis of Systems
The DFT
The Fast Fourier Transform
Implementation of Discrete-Time Systems
Filter Design
Index
