Approximation and Weak Convergence Methods for Random Processes with Applications to Stochastic Systems Theory (Signal Processing, Optimization, and Control)

(4)
Approximation and Weak Convergence Methods for Random Processes with Applications to Stochastic Systems Theory (Signal Processing, Optimization, and Control) image
ISBN-10:

0262110903

ISBN-13:

9780262110907

Released: Apr 26, 1984
Publisher: Mit Pr
Format: Hardcover, 361 pages
Related ISBN: 9780262512183

Description:

Control and communications engineers, physicists, and probability theorists, among others, will find this book unique. It contains a detailed development of approximation and limit theorems and methods for random processes and applies them to numerous problems of practical importance. In particular, it develops usable and broad conditions and techniques for showing that a sequence of processes converges to a Markov diffusion or jump process. This is useful when the natural physical model is quite complex, in which case a simpler approximation (a diffusion process, for example) is usually made. The book simplifies and extends some important older methods and develops some powerful new ones applicable to a wide variety of limit and approximation problems. The theory of weak convergence of probability measures is introduced along with general and usable methods (for example, perturbed test function, martingale, and direct averaging) for proving tightness and weak convergence. Kushner's study begins with a systematic development of the method. It then treats dynamical system models that have state-dependent noise or nonsmooth dynamics. Perturbed Liapunov function methods are developed for stability studies of non-Markovian problems and for the study of asymptotic distributions of non-Markovian systems. Three chapters are devoted to applications in control and communication theory (for example, phase-locked loops and adoptive filters). Small-noise problems and an introduction to the theory of large deviations and applications conclude the book. This book is the sixth in The MIT Press Series in Signal Processing, Optimization, and Control, edited by Alan S. Willsky.

Best prices to buy, sell, or rent ISBN 9780262110907




Frequently Asked Questions about Approximation and Weak Convergence Methods for Random Processes with Applications to Stochastic Systems Theory (Signal Processing, Optimization, and Control)

You can buy the Approximation and Weak Convergence Methods for Random Processes with Applications to Stochastic Systems Theory (Signal Processing, Optimization, and Control) book at one of 20+ online bookstores with BookScouter, the website that helps find the best deal across the web. Currently, the best offer comes from and is $ for the .

The price for the book starts from $103.99 on Amazon and is available from 2 sellers at the moment.

At BookScouter, the prices for the book start at $48.88. Feel free to explore the offers for the book in used or new condition from various booksellers, aggregated on our website.

If you’re interested in selling back the Approximation and Weak Convergence Methods for Random Processes with Applications to Stochastic Systems Theory (Signal Processing, Optimization, and Control) book, you can always look up BookScouter for the best deal. BookScouter checks 30+ buyback vendors with a single search and gives you actual information on buyback pricing instantly.

As for the Approximation and Weak Convergence Methods for Random Processes with Applications to Stochastic Systems Theory (Signal Processing, Optimization, and Control) book, the best buyback offer comes from and is $ for the book in good condition.

The Approximation and Weak Convergence Methods for Random Processes with Applications to Stochastic Systems Theory (Signal Processing, Optimization, and Control) book is in very low demand now as the rank for the book is 7,327,278 at the moment. A rank of 1,000,000 means the last copy sold approximately a month ago.

Not enough insights yet.