
Probability, Random Variables, and Stochastic Processes
McGraw Hill Higher Education (Publisher)
4th Edition
Published on 25. October 2001
Book
Hardback
864 pages
978-0-07-366011-0 (ISBN)
Description
The fourth edition of "Probability, Random Variables and Stochastic Processes" has been updated significantly from the previous edition, and it now includes co-author S. Unnikrishna Pillai of Polytechnic University. The book is intended for a senior/graduate level course in probability and is aimed at students in electrical engineering, math, and physics departments. The authors' approach is to develop the subject of probability theory and stochastic processes as a deductive discipline and to illustrate the theory with basic applications of engineering interest. Approximately 1/3 of the text is new material - this material maintains the style and spirit of previous editions. In order to bridge the gap between concepts and applications, a number of additional examples have been added for further clarity, as well as several new topics.
More details
Edition
4th Revised edition
Language
English
Place of publication
London
United States
Publishing group
McGraw-Hill Education - Europe
Target group
College/higher education
Edition type
Revised edition
Illustrations
Illustrations
Dimensions
Height: 241 mm
Width: 190 mm
Thickness: 37 mm
Weight
1426 gr
ISBN-13
978-0-07-366011-0 (9780073660110)
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Schweitzer Classification
Persons
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.
Content
Part 1 Probability and Random Variables 1 The Meaning of Probability 2 The Axioms of Probability 3 Repeated Trials 4 The Concept of a Random Variable 5 Functions of One Random Variable 6 Two Random Variables 7 Sequences of Random Variables 8 Statistics Part 2 Stochastic Processes 9 General Concepts 10 Random Walk and Other Applications 11 Spectral Representation 12 Spectral Estimation 13 Mean Square Estimation 14 Entropy 15 Markov Chains 16 Markov Processes and Queueing Theory