The book can be readily tailored for a variety of courses spanning 30 to 45 lecture hours. Most of the material in the first eight chapters can be covered at a brisk pace in about 45 hours. The book can also be used for a 30-lecture-hour course by covering only analog material (Chapters 1, 2, 4, 6, 7, and possibly selected topics in Chapter 8). Alternately, one can also select Chapters 1 to 5 for courses purely devoted to systems analysis or transform techniques. To treat continuous- and discrete-time systems by using an integrated (or parallel) approach, the appropriate sequence of Chapters is 1, 2, 3, 4, 5, 6, 7, and 8. For a sequential approach, where the continuous-time analysis is followed by discrete-time analysis, the proper chapter sequence is 1, 2, 4, 6, 7, 8, 3, 5, and possibly 9 (depending on the time availability). Logically, the Fourier transform should precede the Laplace transform. I have used such an approach in the companion volume, Signal Processing and Linear Systems (Oxford, 1998). However, a sizable number of instructors feel that it is easier for students to learn Fourier after Laplace. Such an approach has an appeal because of the gradual progression of difficulty, in the sense that the relatively more difficult concepts of Fourier are treated after the simpler area of Laplace.
This book is written to accommodate that viewpoint. For those who wish to see Fourier before Laplace, there is Signal Processing and Linear Systems. This second edition, which closely follows the organization of the first edition, has been refined by incorporating suggestions and changes provided by various reviewers. The added topics include Bode plots, use of digital filters in an impulse-invariance method of designing analog systems, convergence of infinite series, bandpass systems, group and phase delay, and Fourier applications to communication systems. A significant and sizable addition in the area of MATLAB® (a registered trademark of The Math Works, Inc.) has been provided by Dr. Roger Green of North Dakota State University. Dr. Green discusses his contribution at the conclusion of this preface.
MATLAB is a sophisticated language that serves as a powerful tool to better understand a myriad of topics, including control theory, filter design, and, of course, linear systems and signals. MATLAB’s flexible programming structure promotes rapid development and analysis. Outstanding visualization capabilities provide unique insight into system behavior and signal character. By exploring concepts with MATLAB, you will substantially increase your comfort with and understanding of course topics. As with any language, learning MATLAB is incremental and requires practice. This book provides two levels of exposure to MATLAB. First, short computer examples are interspersed throughout the text to reinforce concepts and perform various computations. These examples utilize standard MATLAB functions as well as functions from the control system, signal processing, and symbolic math toolboxes. MATLAB has many more toolboxes available, but these three are commonly available in many engineering departments. A second and deeper level of exposure to MATLAB is achieved by concluding each chapter with a separate MATLAB session. Taken together, these eleven sessions provide a self-contained introduction to the MATLAB environment that allows even novice users to quickly gain MATLAB proficiency and competence. These sessions provide detailed instruction on how to use MATLAB to solve problems in linear systems and signals. Except for the very last chapter, special care has been taken to avoid the use of toolbox functions in the MATLAB sessions. Rather, readers are shown the process of developing their own code. In this way, those readers without toolbox access are not at a disadvantage.