
Probability, Random Variables and Stochastic Processes with Errata Sheet (Int'l Ed)
McGraw-Hill Professional (Publisher)
4th Edition
Published on 16. January 2002
Book
978-0-07-122661-5 (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 edition
Language
English
Place of publication
United States
Publishing group
McGraw-Hill Education - Europe
Target group
College/higher education
Dimensions
Height: 0 mm
Width: 0 mm
Thickness: 0 mm
ISBN-13
978-0-07-122661-5 (9780071226615)
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 Variables1 The Meaning of Probability2 The Axioms of Probability3 Repeated Trials4 The Concept of a Random Variable5 Functions of One Random Variable6 Two Random Variables7 Sequences of Random Variables8 StatisticsPart 2 Stochastic Processes9 General Concepts10 Random Walk and Other Applications11 Spectral Representation12 Spectral Estimation13 Mean Square Estimation14 Entropy15 Markov Chains16 Markov Processes and Queueing Theory