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Probability, Random Variables and Stochastic Processes 4th Edition

3.3 out of 5 stars 60 customer reviews
ISBN-13: 978-0071226615
ISBN-10: 0071226613
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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.
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Product Details

  • Paperback: 852 pages
  • Publisher: McGraw-Hill Europe; 4th edition (January 1, 2002)
  • Language: English
  • ISBN-10: 0071226613
  • ISBN-13: 978-0071226615
  • Product Dimensions: 7.3 x 1.3 x 9.2 inches
  • Shipping Weight: 3 pounds
  • Average Customer Review: 3.3 out of 5 stars  See all reviews (60 customer reviews)
  • Amazon Best Sellers Rank: #529,803 in Books (See Top 100 in Books)

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Customer Reviews

Top Customer Reviews

Format: Paperback Verified Purchase
When readers and students ask to me for a useable book for nonmathematicians to get into probability (or a probabilistic approach to statistics), before embarking into deeper problems, I suggest this book by the Late A. Papoulis. I even recommend it to mathematicians as their training often tends to make them spend too much time on limit theorems and very little on the actual "plumbing".
The treatment has no measure theory, cuts to the chase, and can be used as a desk reference. If you want measure theory, go spend some time reading Billingsley. A deep understanding of measure theory is not necessary for scientific and engineering applications; it is not necessary for those who do not want to work on theorems and technical proofs.
I've notice a few complaints in the comments section by people who felt frustrated by the treatment: do not pay attention to them. Ignore them. It the subject itself that is difficult, not this book. The book, in fact, is admirable and comprehensive given the current state of the art.
I am using this book as a benchmark while writing my own, but more advanced, textbook (on errors in use of statistical models). Anything derived and presented in Papoulis, I can skip. And when students ask me what they need as pre-requisite to attend my class or read my book, my answer is: Papoulis if you are a scientist, Varadhan if you are more abstract.
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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.
1 Comment 36 of 39 people found this helpful. Was this review helpful to you? Yes No Sending feedback...
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Format: 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.
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By A Customer on July 2, 2002
Format: Hardcover Verified Purchase
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.
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By A Customer on February 2, 2004
Format: Hardcover
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.
1 Comment 15 of 17 people found this helpful. Was this review helpful to you? Yes No Sending feedback...
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Format: Hardcover
In very short words this book is just a very long stream of random processes equations with some explanation in between. At the same time, the cross index at the end is not very complete, this makes looking for an answer difficult (try just to put together the most fundamental properties of a Gaussian Process if you doubt about this).
One good feature of this book (and maybe this is why it's so widely used) is that it covers a very extensive list of topics.
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Format: Hardcover
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.
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