Customer Reviews

Probability and Random Processes for Electrical Engineering

5 star:		(6)
4 star:		(8)
3 star:		(5)
2 star:		(4)
1 star:		(9)

 

 

If you are in EE, at first glance this book looks perfect. All of the example are on electrical engineering stuff, you see lots of graphs and the book has many tables on the cover making it nice for reference.

However... when you really get into this book, you will quickly realize it is pretty worthless.

For example chapter 3 is over 100 pages long. It is called random variables. In this single chapter they introduce random variables, functions of random variables, expectation of R.V. and functions of R.V., Markov and Chebyshev inequalities as well as Moment generating functions and Characteristic functions, entropy as well as a few others. I hope you are thinking WHEW!! This should have easily been 2 or 3 chapters.

Now to boot, there are 160 end of chapter problems! In the chapter there are 71 examples, BUT only about 20 of them are actually useful. The other 51 examples are strange things like Ex. What does the greek character rho mean? It means an outcome! That is not an example in my book. Meanwhile the end of chapter problems are like Q. Take the Laplace transform of the characteristic function and show that it is a Cauchy R.V. Right... and that is in the book where. Oh yeah, I get it, I am just suppose to be able to piece that together from this amazing book and its 71 examples, whatever.

Now, there is a solution manual available for this book with worked out problems. Guess how many are done in chapter 3? There are 34 worked out problems, and they are all of the easiest problems. Out of those 34 problems, only one of them uses the characteristic function. Yet, there are about 50 problems at the end of the chapter on characteristic functions.

Overall I am very dissapointed in this book. No worthwhile examples and the explainations are very weak at times. Compared to Papoulis this book is perhaps equal. However when you are comparing stinky socks to rotten eggs...

I am a graduate student using this book in a class. I would really like to warn other people from using it.

The book describes everything with a lot of examples. As a result of this you do not get a basic understanding, but rather some examples that you can adapt and use for a problem that you have to solve.

It is like learning that a wheel is turning because you might turn it with your hand, rather than because you are applying a torque to it. Or that a lamp is turned on because you might hit the switch, rather than because a current flows through it.

For some reason everything has to be described with CDFs instead of PDFs in the book. It seems like PDFs are something that is difficult to imagine for the author.

I once had a teacher in a class, and a book containing a lot of examples like this one. He claimed that he could write everything the book contained on 2 pages - He was right!! I think the same thing could be done with this book.

Do not choose this book. It is highly unrecommended.

I used this book for a graduate class in Probaility and Random Processes and we covered every chapter. I gave the book three stars based on other probability books I have used, but compared to other engineering books I would rate it lower.

I feel main problem with the book is the examples not very helpful in solving the 100+ problems that accompany each chapter. Most of the examples were just useless explanations graphs. The book also seems to gloss over some of the important concepts needed to solve the homework problems. The only homework problems that I found useful were the MATLAB examples. I would recommend doing these problems even if they are not assigned.

The book also does a poor job covering applications, especially in the later chapters on random processes. I would have been interested in more signal processing and communications applications, the main reason I took a course on probability and random processes.

As far a background for a person using this book, I would recommend the person be graduate student with a solid math background.

This book may not be too friendly to those who are unfamiliar with the subject. This is because the subject is unfriendly. Before you complain about this book, take a look at the other books on the subject to realize that the author took a great effort to make it accessible. However, I personally do not like the degree of compromise made in this book. Too many uninsightful examples, and lacking detailed discussions. This cannot be a good reference book. For reference, I like Papoulis, for enjoy reading deep insights, I like Gardner, and I recommend Peebles for people who hated this book. However, Leon-Garcia is easier to read and faster moving than Papoulis and Gardner. It is not easy attempting to combine mathematical rigor (which this book still lacks) and engineering point of view from many application areas in one text book. Three stars because I like other books better, but this should be the lower bound of evaluation given to this book.

This book is just god awful. I think probablity theory is a very fascinating subject, however, I don't think this is a good book to learn it from.

Where do I begin:

-The biggest grip I have with this book is the problem set. The problems in this book are, literally, just plain hard. The author expects you to do problems,using the techniques they used in proving an actual theorem! I'm not talking about using the actual theorem, but the actual steps they used. I'm an undergrad in a graduate course, and most of the graduate students aren't even doing well on the homework assignments. I consider myself a pretty decent student. I was able to learn DSP using the Oppenheim book(with the aid of a teacher's solution manual of course). The problems in this book are harder than the problems in Oppenheim's DSP book(and I have a teachers solution manual for this prob. book). The bottomline is that 80-100 problems per chapter won't do anyone any good if they can't solve those problems.

-The author's notation is extremely weird, confusing, and downright bad.

-I just have the strangest feeling that the author is trying to make the students,whom are using the text, feel like they're stupid.

-This book is nine years old. I think the author should rewrite the text from scratch.

-My instructor is literally terrible, so I'm going through a lot of hell in this course.

-And finally, the author, when explaining the theory, uses alot of tedious reasoning and formulas when doing certain theorems. For example, when he's explaining the concept of a bernoulli distribution, the author uses the indicator function to explain the concept. This is not even needed to explain this concept(I have checked this several books, and this was not done), and it's a bit tedious and pointless to include it in the theory.

-My communication systems teacher told our class last semester, that learning from enigneering books is not a good way to learn material. This is all because the authors like to show off their intellectual skill and nothing more. They usually forget to include problems by the time of publishing, and have to delay the release of the book to include problems. And what do they include, diffcult problems, which are really not needed to learn introductory concepts.

I intend to burn this book once the semester is over; it is utterly worthless. My professor was coerced to use the book and assigns homework from the book, but the exams look nothing at all like the homework or material from the book.

My complaints:
Insuffucient examples to teach a concept. There is an inextricably, monotonous presence of teaching. The examples are nowhere near adequate to be able to do the problems in the back of the chapter. Superficially, the content looks great, but when you try to learn it from the book, the frustration builds until you cry.

The wording of chapter exercises and end of chapter problems is vague and problemmatic. It is difficult to understand what is being taught, if anything is being taught at all. I would like to use this as a reference when I graduate, but realistically, if it's as useful as cow dung now, then why would I keep it?

So, get it all over with now, the crying, the late nights pulling hair out, seeking antidepressants for the incessant crying and depression due to frustration. Be realistic in the beginning. Unless you have an excellent professor, you will probably not make a good grade based on homework and/or exams from this book. Better yet, don't buy the book - you might get a better grade on the exams if you are exposed to the unnecessary stress.

[This is just an opinion - don't sue me. If, by some strange reason, you're a math major, then you might have a partial background to cope with the book's inadequacies and take a different view.]

I am a senior in Computer Science and this book was used as a text book for our Probability class. Our class was very unhappy with it. The author is a very intelligent person, but our class had a hard time keeping up with him. Many of the complex problems refer to equations, tables, and more importantly previous problems that had been touched briefly on 20 or more pages previously. All of the tables were given only once and in a few cases, Chapter 5 problems have you flipping back to Chapter 3 just to read a table. This meant we were constantly flipping pages back and forth to try and read the material.

There were also errors in the book that I couldn't believe hadn't been caught by now. Many of the errors are difficult to catch as a student because they fall in equation definitions that are only given once. One error had a double integral misdefined.

The author also assumes that the students can identify Taylor series expansions, geometric, and e^x by solving discrete summations, which to be honest I would have appreciated the author going thru at least one example, or giving the student some tips on identifying these.

The notation in this book is also confusing. Many of the problems deal with finding the double integral of a function that invloves 'x' and 'y' yet the author uses X and Y to denote a random variable from the respective functions, therefore the book is riddled with equations that sometimes have x, X, and x' all meaning completely different things. This was extremely confusing once we started doing joint probabilites that involved y,Y,y',x,X,x'. Also the author introduces <x> to define the mean, but he doesn't explain this is a defintion but instead introduces it in chapter one problem 7 and asks the student to prove the discrete summation, which I won't try and convey here.

In my opinion this book is too difficult for undergraduate classes, but perhaps it would suit graduate level students, if the errors were corrected, the notation was cleaned up, and a few more examples were given.

Probability and Random Processes for Electrical Engineering is not a very well-written book. The book seems to be gaining more favor with EE and computer science programs, not because of the quality of the book, but rather the need to standardize on texts, regardless of the quality.

The book itself is extremely sketchy and lacks mathematical rigor, perhaps because it is supposed to be meant for engineers and not for math majors, but even so it does not explain its subject very well, even though preface states that it is accessible. For example, the concept of counting theory is extremely important in probabiity, but the author devotes a total of six pages to the subject and even notes that counting theory can be skipped without loss of continuity. I don't think so! Also the author's definitions of discrete and continous sample spaces are not quite correct.

There are not enough examples outlined in the book and many of the homework problems have little relevance to the examples presented. A good instructor could make something out of this book, but be sure to get a Schaum's outline for more problems and another text to complement this one.

I used this book in a sophomore-level probability course for electrical engineers and I found the book a bit confusing at the time. The notation is somewhat awkward and examples are interleaved throughout general concepts, making it difficult to discern key ideas.

During my doctoral studies, I gained a different perspective. I consistently found the book to be a valuable starting point for many concepts and I now find the examples a quick way to brush up on elementary principles.

However, Leon-Garcia doesn't give a thorough approach to probability theory (there are essentially no theorems) and avoids set theory almost entirely. To really put my teeth into something, I would have to track down a more advanced text for any particular concept I was interested in. Basically, Leon-Garcia tries to seperate "Probability and Random Processes" from rigorous mathematics.... something similar to eating fat-free cheesecake.

This book is a confusing muddle and for students who have no prior knowledge of the subject, it could not be a worse textbook. It seems as if more graduate programs in electrical and computer engineering are using this text, not because it teaches the subject well, but "to keep up with the Joneses," so to speak. There are too few examples to illustrate problems, and many of the homework exercises are not well explained and have no relevance to the text. The text itself is too bare bones. The introduction uses the words easily accessible or similar terms to describe the book, but that is not true. In the hands of a good lecturer/professor, it may be worthwhile but if you are taking a class with a bad lecturer who is using this text,then you are in deep trouble! Caveat emptor!