Probabilistic Methods of Signal and System Analysis, Third Edition, provides an introduction to the applications of probability theory to the solution of problems arising in the analysis of signals and systems. Since its original publication in 1971, this text has been a standard for signals and systems courses that emphasize probability.
The new edition incorporates a much greater use of the computer in examples and problems. It increases the number and variety of examples, such as estimating the parameters of random processes and processing them through linear systems. In this edition, the use of the computer is introduced both in text examples and in selected problems. The computer examples are carried out using MATLAB. A number of new sections have been added relating to Benoulli trials, correclation of data sets, smoothing of data, computer computation of correlation functions and spectral densities and system simulation. Virtually all of the examples have been modified or changed, many of the problems have been modified and a number of new problems have been added. A separate Appendix is included that discusses and illustrates the application of computers to signal and system analysis.
It is written as a textbook appropriate for engineering students at the junior or senior level. However, it may also serve graduate students and engineers as a review of topics previously encountered, albeit from scattered sources.
Customer Review: Not Enough Examples
This book does not provide enough examples to thoroughly cover each chapter. The end of chapter exercises are much harder than the examples given in the chapter. This book leaves you wanting more for your money. I advise any one to not buy or use this book. I had to use other books to try and figure out how to solve the problems for homework. I am going to put this book on my bookshelf and let it gather dust, its almost totally useless.
Customer Review: Very litte content
My school uses this book to teach random signals, and I feel that the content is quite lacking. The theory presented is too basic, and the authors don't provide any further explantions. The examples presented are too simple and too few. Additionally, they don't show how harder problems can be solved. The end-of-chapter problems aren't very easy to solve if you're only consulting this book. There are exercises presented for you to try during the chapter in addition to the end-of-chapter problems, but the book doesn't show how to do these problems and only gives you the final answers instead. On top of this, sometimes, the answers for the exercises are switched, leaving you wondering for a few minutes what you might have done wrong.
As a comparision to other books, the chapter about several random variables in this book was approximately 35 pages long, while the book by Papoulis (another book I've consulted) covers this material in 70 pages. I've taken a look at some other books, and one book that comes close to my tastes is Schaum's Outline of Probability, Random Variables, and Random Processes since it provides a whole lot of examples I can work through.
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