Probability and Random Processes an Introduction for Applied Scientists and Engineers
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Book Overview
A post-calculus approach to this important mathematical discipline. A cursory survey of engineering reveals the widespread application of probability theory. Such diverse fields as systems analysis,... This description may be from another edition of this product.
Format:Hardcover
Language:English
ISBN:0070154406
ISBN13:9780070154407
Release Date:January 1970
Publisher:McGraw-Hill College
Length:608 Pages
Weight:1.96 lbs.
Dimensions:9.5" x 1.3" x 6.5"
Customer Reviews
2 ratings
A book for engineers working in applications
Published by Thriftbooks.com User , 16 years ago
I found/find this book wonderful. I was introduced to this book about 25 years ago by Prof Simon Haykin at McMaster University as a graduate student. For a person who had not taken a formal course on Probability and Random Processes, I found this book very useful. The book explains concepts using the simplest of examples but does not miss out on the mathematical rigour. Although I was introduced to this book 25 years ago, I still continue to use it, have recommended that my students also use it. I would recommend this book for any graduate student working in Communications/Speech Technology/Machine Learning/Computer Vision. I wish a paperback student edition becomes available so that more students can OWN it.
Excellent and relevant coverage of material
Published by Thriftbooks.com User , 26 years ago
Davenport's "Probability and Random Processes" is an excellent, readable text on this subject for engineers/scientists/etc with an intermediate to advanced level of mathematics background. The important chapters are: 3) Probability, 4) Random variables, 5) random vectors, 6) functions of rv's, 7) statistical averages, 8) estimation, sampling, and prediction, 9) random processes (a wide variety), 10) linear transforms, 11) spectral analysis, 12) sums of independent rv's, 13) the poisson process, 14) the gaussian process. Clearly this book covers a wide breadth which is the attraction for me. His approach is rigorous yet approachable through many interesting examples. Many examples deal with digital communcation of binary data. What this book is not is a highfalutin, axiomatic, terse text for those with PhD's in mathematics. McGraw-Hill recently republished this classic 1970 volume in its "classic textbook reissue" series. The author, Davenport, was in fact of Prof. at MIT. I highly recommend this text for those who want a rigorous understanding of random processes.
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