The theory of probability is a powerful tool that helps electrical and computer engineers to explain, model, analyze, and design the technology they develop. The text begins at the advanced undergraduate level, assuming only a modest knowledge of probability, and progresses through more complex topics mastered at graduate level. The first five chapters cover the basics of probability and both discrete and continuous random variables. The later chapters have a more specialized coverage, including random vectors, Gaussian random vectors, random processes, Markov Chains, and convergence. Describing tools and results that are used extensively in the field, this is more than a textbook; it is also a reference for researchers working in communications, signal processing, and computer network traffic analysis. With over 300 worked examples, some 800 homework problems, and sections for exam preparation, this is an essential companion for advanced undergraduate and graduate students. Further resources for this title, including solutions (for Instructors only), are available online at www.cambridge.org/9780521864701.
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'… stands alone as a textbook that encourages readers to work through and obtain working knowledge of probability and random processes.' IEEE Software
Book Description
The theory of probability has important applications for computer and electrical engineers as a tool to explain, model, analyse and design the technology they develop. Gubner presents the fundamentals of probability, then progresses to more complicated topics. Suitable for advanced undergraduates, graduates and as a reference for researchers.
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Probability theory provides powerful tools to explain, model, analyze, and design technology developed by electrical and computer engineers. Read the first page
Front Cover | Copyright | Table of Contents | Excerpt | Index
Probability theory provides powerful tools to explain, model, analyze, and design technology developed by electrical and computer engineers. Read the first page
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Front Cover | Copyright | Table of Contents | Excerpt | Index
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Most Helpful Customer Reviews
2 of 3 people found the following review helpful
By Ramses
Format:Hardcover|Amazon Verified Purchase
I have just bought this book a couple of weeks ago, it is a new title from Cambridge. Why another book about this topic ? there are hundreds. I have asked this to myself but after reading parts and skimming the rest I can give 5 stars. I do like the approach taken by the author, who has a friendly style, made a wise choice of topics, and follows a logical progression with liberal sprinkling of examples (including numerical) through the text. Only useful mathematics are introduced and the text is self-contained at the upper-undergraduate level in applied mathematics. This will be a very good book for me to keep for reference in my library.
0 of 1 people found the following review helpful
By Martin Juul
Format:Hardcover|Amazon Verified Purchase
This book seems to be an endless resource. Now several years after I bought it I still return, for reference, re-reading, and for new things I skipped the first time. Every basic topic in probability theory is found here, and there are strikingly few errors. The reader is assumed to know linear algebra, infinite series, and calculus of several variables. The book is typographically perfect.
Gubners theory centric approach is frustrating at times. As an example the Poisson variable is defined at page 69, with no mention of it's origin in the exponential distribution. On page 81 it's expectation is calculated, and on page 111 in the section about probability generating functions, it's variance is found. This is Gubners way! The first time you read the book, it's the perfect choice. When used as a reference, it's less so.
To be honest, despite it's shortcomings, I love this book!
Gubners theory centric approach is frustrating at times. As an example the Poisson variable is defined at page 69, with no mention of it's origin in the exponential distribution. On page 81 it's expectation is calculated, and on page 111 in the section about probability generating functions, it's variance is found. This is Gubners way! The first time you read the book, it's the perfect choice. When used as a reference, it's less so.
To be honest, despite it's shortcomings, I love this book!
Most Helpful Customer Reviews on Amazon.com (beta)
Amazon.com:
4.1 out of 5 stars
7 reviews
8 of 8 people found the following review helpful
4.0 out of 5 stars
an excellent book to begin probability
1 Nov 2007
By Arvind Jayaraman
- Published on Amazon.com
Format:Hardcover
This is an excellent book on probability. What I liked about it is the fact that it is sprinkled with numeours examples. The language the author has used is also easy to understand but at the same time, formal. It really strikes the balance.
However, I think there should be more explanation of combinatorics in ch2. But if a person has had some prior knowledge of probability, they should refer to some other book for that portion.
However, I think there should be more explanation of combinatorics in ch2. But if a person has had some prior knowledge of probability, they should refer to some other book for that portion.
10 of 11 people found the following review helpful
5.0 out of 5 stars
well suited for a university course
3 Sep 2006
By W Boudville
- Published on Amazon.com
Format:Hardcover
Gubner provides an excellent text for undergrads or grads wanting a solid background in applying the ideas of probability and random processes. The emphasis is on applications in electrical engineering. The book presupposes a solid background in calculus and some circuit theory. Ideally, the student might be a third year undergrad or higher.
The main ideas in probability are developed. Getting to the Central Limit Theorem and the Gaussian (bell) curve. The probability distributions most useful to you might be the continuous ones.
Then, the text develops the ideas of random processes. When these can be assumed to be stationary, then it makes tractable vast areas of applications, as in the communications theory of the signal to noise ratio of a channel.
The book shines as a text for a university course because of the wealth of examples and problem sets. The difficult of the latter varies considerably, which is also another advantage to a lecturer facing students with a range of abilities.
The main ideas in probability are developed. Getting to the Central Limit Theorem and the Gaussian (bell) curve. The probability distributions most useful to you might be the continuous ones.
Then, the text develops the ideas of random processes. When these can be assumed to be stationary, then it makes tractable vast areas of applications, as in the communications theory of the signal to noise ratio of a channel.
The book shines as a text for a university course because of the wealth of examples and problem sets. The difficult of the latter varies considerably, which is also another advantage to a lecturer facing students with a range of abilities.
4.0 out of 5 stars
An easy to use book
4 Oct 2011
By S. Jacobs
- Published on Amazon.com
Format:Hardcover|Amazon Verified Purchase
This book is very effective in bringing out important concepts and applying the methods it teaches. The presentation of material is concise and intuitive, and the examples help flesh out the concepts.
The exercises are helpful, with many "show this is true" type of problems that are still simple enough to be doable, but still stretching your understanding of the concepts. The exam preparation sections at the end of each chapter are incredibly helpful.
The exercises are helpful, with many "show this is true" type of problems that are still simple enough to be doable, but still stretching your understanding of the concepts. The exam preparation sections at the end of each chapter are incredibly helpful.
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4.1 out of 5 stars
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