Probability, Random Variables and Stochastic Processes [Paperback]

Papoulis (Author)

Book Description

ISBN-10: 0071199810 | ISBN-13: 978-0071199810 | Publication Date: January 1, 2002 | Edition: 4th

The fourth edition of "Probability, Random Variables and Stochastic Processes" has been updated significantly from the previous edition, and it now includes co-author S. Unnikrishna Pillai of Polytechnic University. The book is intended for a senior/graduate level course in probability and is aimed at students in electrical engineering, math, and physics departments. The authors' approach is to develop the subject of probability theory and stochastic processes as a deductive discipline and to illustrate the theory with basic applications of engineering interest. Approximately 1/3 of the text is new material - this material maintains the style and spirit of previous editions. In order to bridge the gap between concepts and applications, a number of additional examples have been added for further clarity, as well as several new topics.

Editorial Reviews

Amazon.com Review

This text is a classic in probability, statistics, and estimation and in the application of these fields to modern engineering problems. Probability, Random Variables, and Stochastic Processes assumes a strong college mathematics background. The first half of the text develops the basic machinery of probability and statistics from first principles while the second half develops applications of the basic theory. Topics in the first section include probability distributions and densities, random variables and vectors, expectations, covariance, correlations, functions of random variables and vectors, and conditional distributions and densities. In this third edition of the text, the second half of the book has been substantially updated and expanded to include new or revised discussions of the following topics: mean square estimation, likelihood tests, maximum entropy methods, Monte Carlo techniques, spectral representations and estimation, sampling theory, bispectra and system identification, cyclostationary processes, deterministic signals in noise, and the Wiener and Kalman filters. Probability, Random Variables, and Stochastic Processes covers a remarkable density of material and the clarity of both presentation and notation make this book invaluable as a text and a reference. --This text refers to an out of print or unavailable edition of this title.

About the Author

S. Unnikrishna Pillai is a Professor of Electrical and Computer Engineering at Polytechnic Institute of NYU in Brooklyn, New York. His research interests include radar signal processing, blind identification, spectrum estimation, data recovery and wavform diversity. Dr. Pillai is the author of Array Signal Processign and co-author of Spectrum Estimation and system Identification, Prof. Papoulis’ Probability, Random Variables and Stochastic processes (Fourth edition), and Space Based Radar – Theory & Applications.

Product Details

• Paperback
• Publisher: Mcgraw Hill Higher Education; 4th edition (January 1, 2002)
• Language: English
• ISBN-10: 0071199810
• ISBN-13: 978-0071199810
• Product Dimensions: 9.4 x 7.6 x 1.4 inches
• Shipping Weight: 3.3 pounds
• Average Customer Review: 2.9 out of 5 stars  See all reviews (35 customer reviews)
• Amazon Best Sellers Rank: #2,451,814 in Books (See Top 100 in Books)

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Customer Reviews

Most Helpful Customer Reviews

25 of 27 people found the following review helpful:

3.0 out of 5 stars Good book with the help of a good instructor, May 14, 2002

By 

JS "jcs19" (Irvine, CA USA) - See all my reviews

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After reading almost all reviews, I actually think I agree with almost all including the ones that say it is not a book for beginners and ones that say that it is a great book written by a very knowledgeable author. As a student who just completed a course in this subject with this book as the text, here is what I would like to say:
1. My instructor re-ordered some of the content of the text for his course. It seemed necessary to understand certain concepts.
2. As one of the previous reviews mentioned, some of the important aspects of probability theory were hidden in problems, these were brought out by the instructor either as homeworks or as part of lecture notes and explained. This also means that it is not enough to just read this text and understand the examples. It is almost as important to go through the problems to get the complete picture
3. All in all I liked the book but I sure would not have liked it as much if I did not have a good instructor to go with it. Definitely not a self-study book.

19 of 21 people found the following review helpful:

4.0 out of 5 stars great book in the classical textbook sense, March 26, 2000

By 

Julius Kusuma (Cambridge, MA, USA) - See all my reviews
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This review is from: Probability, Random Variables and Stochastic Processes (Hardcover)

i would like to again point out that while this book is excellent as a reference, it's not very good to read cover-to-cover. Papoulis is extremely knowledgeable in this area, and this book is, in fact, the FIRST EVER book of stochastic/random variables and processes written for the engineers. unfortunately, despite the excellent material, the presentation and coverage is sometimes hard to follow, and hides the true gem in this book.

15 of 17 people found the following review helpful:

5.0 out of 5 stars Papoulis is Useful, July 2, 2002

By A Customer

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This review is from: Probability, Random Variables and Stochastic Processes (Hardcover)

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.