Probability, Random Variables, and Stochastic Processes

Papoulis Athanasios

ISBN 10: 0070484481 / ISBN 13: 9780070484481

Published by McGraw-Hill, 1965

About this Item

This item is fairly worn, but continues to work perfectly. Signs of wear can include aesthetic issues such as scratches, dents, worn corners, bends, tears, small stains, and partial water damage. All pages and the cover are intact, but the dust cover may be missing, if applicable. Pages may include excessive notes and highlighting, but the text is not obscured or unreadable. Satisfaction Guaranteed. Seller Inventory # 4BQGBJ00BGZ5_ns

Bibliographic Details

Title: Probability, Random Variables, and ...

Publisher: McGraw-Hill

Publication Date: 1965

Binding: hardcover

Condition: Fair

About this title

Synopsis:

Book Overview The authors' approach to the revised fourth edition of the popular text Probability, Random Variables and Stochastic Processes is to develop the subject of probability theory and stochastic processes systematically as a deductive discipline with many illustrative examples of engineering interest. The text is intended for senior/graduate level courses in probability and stochastic processes, and is aimed at students in electrical and computer engineering, mathematics, and physics. With its excellent topical coverage, the book can be used for two or three different courses. This significantly updated fourth edition now includes a coauthor, Prof. S. Unnikrishna Pillai, also from Polytechnic.

Review:

This text is a classic in probability, statistics, and estimation and in the application of these fields to modern engineering problems. Probability, Random Variables, and Stochastic Processes assumes a strong college mathematics background. The first half of the text develops the basic machinery of probability and statistics from first principles while the second half develops applications of the basic theory. Topics in the first section include probability distributions and densities, random variables and vectors, expectations, covariance, correlations, functions of random variables and vectors, and conditional distributions and densities. In this third edition of the text, the second half of the book has been substantially updated and expanded to include new or revised discussions of the following topics: mean square estimation, likelihood tests, maximum entropy methods, Monte Carlo techniques, spectral representations and estimation, sampling theory, bispectra and system identification, cyclostationary processes, deterministic signals in noise, and the Wiener and Kalman filters. Probability, Random Variables, and Stochastic Processes covers a remarkable density of material and the clarity of both presentation and notation make this book invaluable as a text and a reference.