Customer Reviews

Probability and Random Processes with Applications to Signal Processing (3rd Edition)

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I had the misfortune to take an EE grad course in Random Processes using this text (3rd edition.) Let me start with the single good point about the book before thrashing its shortcomings. The book does a good job of covering basic probability theory, which is handy if you've never dealt with set theory, algebras, etc. From that point on, it goes downhill quickly. The introduction to random variables and subsequent random process treatment jumps all over the place, skipping many integral pieces and steps along the way. There is no attempt to build a body of knowledge and then instruct the reader in methodology to solve typical problem sets. To compound this, the book is replete with typographical errors in formulas, proofs, and general verbiage. The problem sets at the end of each chapter are sometimes challenging, but mostly just obtuse and vaguely worded exercises that do not follow any progressive order in the chapter just covered. Some of the problem sets actually require knowledge from subsequent chapters to solve, which makes doing the problems more an exercise in leafing forward and backward in the book rather than a meaningful intuition building and problem solving exercise. I will admit that the Papoulis book is a little dense, but it doesn't skip steps or gloss over any 'obvious' steps in the proofs or example problems. It seems that the Schaum's guide and Papoulis books at least follow a progressive process of building knowledge while this book has roughly the same knowledge, but scattered across many chapters (when it logically should all be treated contiguously.) If you happen to take a class using this book, be forewarned that you really will need several other references (Schaum's guide for certain, Papoulis is dense but complete, that's all I have) to piece together the puzzle on this otherwise very interesting and relevant subject.

I found Probability and Random Processes a difficult subject and it was compounded by the instructor's selection of the stark and woods textbook. While it has some interesting problem sets and the tone of the text is very engaging, Probability and Random Processes, 3rd ed. has several problems. First of all, the book has several typos, including some in derivations which can cause a "what the...?" moment. Second, many sections in the introductory material gloss over derivations, skip steps, or leave proofs of theorems as the classic "exercize for the reader." (!) The biggest problem the text has is that it doesn't adequately explain the intuition for problem solving. For an engineer coming from industry and starting grad school after an extended period away from college, the net result is that the book is not self-contained. I had to buy the Papoulis book and the Schaum's outline to keep my head above water. When the semester was over I ditched the Stark and Woods and kept the Papoulis book.

I am a grad student who has to read this book every week to do the homework :P. Personally I do not reccommend the book for anyone who doesn't have strong random process background. For average student like me, I found myself read it more than 10 times in some of the topics to get the idea of the section (in order to finish end of chapter's questions). Also, I feel like there are some missing link that the author left out (may be because author assume that you know the background quite well) and that sometimes make the flow of the explanation not smooth.(for me)

I had to use this book for a graduate course on Random Processing. The explanations are not very clear. I constantly had to refer to Papoulis's book in order to clarify topics. Some subjects are broken into several parts and each is discussed in a different chapter. this made it very annoying because I to go back and forth between many chapter to get the idea. Overall, i don't recommend it to someone who wants to learn random processes.

This book is ideal as a textbook in a class on random processes, particularly for engineers and those interested in signal processing and telecommunications. I have found the book very easy to follow, quite accessible and complete, and the example problems are very indicative of the approach you need to solve the exercises at the end of each chapter. I would not recommend this book for self-study, however, as I think that self-study of a subject as difficult as random processes would be tough going for anybody. The criticisms that I would make are:
1. The book is poorly edited. There are a moderate number of typos. Some are in places where it is obvious what the author meant, but a few are in critical equations that could mislead the reader.
2. There are no solutions to any of the exercises included in the book. It would really help if there were solutions to either odd or even problems included so that you would know you are on the right path.
Since Amazon does not currently show the table of contents for this book, I do so for the purpose of completeness:
Chapter one is an introduction to probability. This material is covered quickly, so the reader should just use this as a review.
Chapter two introduces random variables. Included topics are the definition of a random variable, the probability density and distribution functions. This material is presented with exceptional clarity.
Functions of Random Variables are introduced in chapter three. This is one of the hardest chapters in the book, although I have not been able to find another book that explains the same material as well. This is mainly concerned with finding the probability density functions of f(x) and f(x,y) given the pdf of the input functions. Convolution and multiple integrals abound in this chapter.
Chapter 4 is Expectation and Introduction to Estimation. This sounds straightforward, but the material on conditional expectation can get complex, although the book covers it well.
Chapter 5 is Random Vectors and Parameter Estimation. This chapter takes concepts from numerical linear algebra and applies it to random processes.
Chapter six is random sequences and introduces linear systems concepts and markov processes.
Chapters seven and eight talk about advanced concepts in random processes.
Chapter nine discusses applications of the previous eight chapters to statistical signal processing.
To get the most out of this book you should already be familiar with probability theory, multiple variable calculus, and linear algebra. If you are not, there is no way you are going to understand this material. A good companion to this book is Schaum's outline of Probability, Random Variables, and Random Processes. It covers most of the same material as this book, except that it does so with more of a mathematician's viewpoint. The Schaum's outline's solved problems also help offset the fact that there are no solutions to exercises in this book. Just remember that there is no textbook on a subject as complex as random processes that is going to negate the need for an instructor of exceptional ability.

This book is well written, and is especially interesting for electrical engineers because it uses examples from their field almost from the start. However, it is rife with typos, which can be frustrating in a math book, where you often assume its true, then try to figure out why. Also, it exhibits the sloppy math style common to engineers, especially when it comes to the distinction between constants and variables. This can lead to alot confusion at first.

I am amazed that this book is used as a primary text at so many universities. While initially I was unsure if this was a poor text, or if I was simply not adequately prepared to take a probability course, I qucikly realized upon viewing other references that this book was useless and that there are so many other books on this subject which address probability in an intuitive manner. I sometimes read this book and wonder who the authors were writing this book for. The examples are completely overbearing in some cases. Take Example 5.5-3, which was a 4 page discourse on Black Lung, which was probably pulled out of a journal paper. While this could be an interesting topic in probability, it is frustrating, confusing and discouraging to someone trying to learn the subject. I will not even go into the books typographical errors, as they have been mentioned in several other reviews. My advice would be to check out other references if you are taking a class using this text. This book is useful only to people who have mastered the subject.

I found this book to be terrible when I was looking for something specific, but good if read from the start to finish of each chapter. My style of studying doesn't mesh well with the book's lack of a useful index and procedural organization within the text. The index is useless because common, major terms refer to pages that almost exclusively off-handedly mention the term with no further explanation. This organization makes it nearly useless as a reference book.

This textbook is for EE grads who are oriented towards signal processing. One of the reasons I like this book is that the authors carefully selected the end of the chapter problems. This book seems to have struck the right balance between theory and application and this is reflected in the problems at the end of the chapter. Another strong emphasis of this book is applications to signal processing and the last chapter is only written for this area. Relative to the book by Papoulis, this book explains the details better for a beginner and also has more application. Relative to the other book by Leon+Garcia, this book emphasizes more signal processing concepts like PSD, KL transforms, trellises, detection&estimation while that of Leon+Garcia has more details on queing theory and networks.
I would wait for a new printing since the first printing of the 3rd edition has some minor errors. A very nice feature of this book is that it starts from the concept of probability space, Algebras and measure in a non-rigorous way to help the student cope with the minor "contradictions" they might perceive when reading a textbook in probability.

If you're THE hotshot math person, go for it. All probability books by Stark and Woods are heavily loaded with useless math, cryptic language and the kind of examples that are first of all huh?? and secondly, half the problem is "left to reader as an exercise". Completely useless books if you're a practicing engineering and are trying to get the hang of things real quick to solve a problem at hand. I suggest you look into "Probability and Random Processes" by Venkatarama Krishnan. Loads of very useful, practical examples, fully explained. Hope this helps. -Tony