Probability, Random Variables, and Stochastic Processes

This is a book which definitely requires diligence and effort to get through. The excercises are also not trivial to say the least. However, if you have the energy and patience to actually slug through this text, in the end you will discover that you have actually learned something. Something which is profound and difficult to understand. This book is definitely not recommended as a casual reference.

This book has a huge pool of examples that enables the reader to understand the concept better. The subject itself is "NOT TRIVIAL", however if it wasn't for this book, it could have been worse. I own this book and I liked it. The examples are fairly easy to understand and relevant to the end of chapter problems. There is also a web site for this book that has a lot of additional resources. So if you are thinking of buying this book, then go for it. (Please Note that I am writing this review for the Fourth Edition Hardcover by Papoulis and Pillai. Previous edition is not that good)

I first encountered the works of Papoulis when just out of graduate school in pure math, and worked for a major defense contractor as an analyst. I found out that almost all the engineers there had this book, and purchased a copy. I had studied stochastic processes at a much more theoretical level than is presented in this book, and that study was significantly more difficult than the material in the text under review, so complainers take note. Why do I think this book an excellent one? Because it is so eminently USEFUL to the working engineer. I believe that has been the intent of the author in all of his works. If you're a working engineer who needs to find answers to tough problems, you can scarcely do better than to consult Papoulis.For example, the material on power spectra is of more than academic interest and is useful in applications; the bivariate Taylor expansion for moments of a function of two distributions has been used again and again in applications in industry; especially in the analysis of the ratio of noisy variables arising from radar measurements. The point is that the text provides the material in a readily accessible way for someone who needs it in the "real world" of engineering analysis.

I first encountered this book in a first, graduate-level, course on probability and random processes. Although I was by far not the best student of the subject, and never went into comm theory professionally, this book kept me afloat. I found it to be one of the most readable books on a difficult subject that I have ever encountered. The author does a fine job of focussing on the important ideas, developing them completely, and presenting them clearly.I'm really surprised by the negative reviews of this book. If these complaints come from undergraduates, I can sympathize a bit. This is definitely a graduate-level book, and I think it is a mistake to use in in an undergrad course. On the other hand, I can't sympathize with such complaints if they from grad students. The complaint seems to be that it doesn't make the subject "easy"; unfortunately, there is nothing "easy" about stochastic processes. Some things in life require effort and commitment.

This is the classical text for understanding and applying stochastics processes. Papoulis gets to the formal point!