Theory of Probability and Random Processes by Leonid KoralovTheory of Probability and Random Processes by Leonid Koralov

Theory of Probability and Random Processes

byLeonid Koralov, Yakov G. Sinai

Paperback | October 23, 2007

Pricing and Purchase Info

$81.74

Earn 409 plum® points

Prices and offers may vary in store

Quantity:

In stock online

Ships free on orders over $25

Not available in stores

about

A one-year course in probability theory and the theory of random processes, taught at Princeton University to undergraduate and graduate students, forms the core of the content of this book

It is structured in two parts: the first part providing a detailed discussion of Lebesgue integration, Markov chains, random walks, laws of large numbers, limit theorems, and their relation to Renormalization Group theory. The second part includes the theory of stationary random processes, martingales, generalized random processes, Brownian motion, stochastic integrals, and stochastic differential equations. One section is devoted to the theory of Gibbs random fields.

This material is essential to many undergraduate and graduate courses. The book can also serve as a reference for scientists using modern probability theory in their research.

YAKOV SINAI has been a professor at Princeton University since 1993. He was educated at Moscow State University, and was a professor there till 1993.Since 1971 he has also held the position of senior researcher at the Landau Institute of Theoretical Physics. He is known for fundamental work on dynamical systems, probability theory, mat...
Loading
Title:Theory of Probability and Random ProcessesFormat:PaperbackDimensions:358 pagesPublished:October 23, 2007Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:3540254846

ISBN - 13:9783540254843

Reviews

Table of Contents

Probability Theory.- Random Variables and Their Distributions.- Sequences of Independent Trials.- Lebesgue Integral and Mathematical Expectation.- Conditional Probabilities and Independence.- Markov Chains with a Finite Number of States.- Random Walks on the Lattice ?d.- Laws of Large Numbers.- Weak Convergence of Measures.- Characteristic Functions.- Limit Theorems.- Several Interesting Problems.- Random Processes.- Basic Concepts.- Conditional Expectations and Martingales.- Markov Processes with a Finite State Space.- Wide-Sense Stationary Random Processes.- Strictly Stationary Random Processes.- Generalized Random Processes.- Brownian Motion.- Markov Processes and Markov Families.- Stochastic Integral and the Ito Formula.- Stochastic Differential Equations.- Gibbs Random Fields.

Editorial Reviews

From the reviews of the second edition:"The book is based on a series of lectures taught by the authors at Princeton University and the University of Maryland. The material of the book can be used to support a two-semester course in probability and stochastic processes or, alternatively, two independent one-semester courses in probability and stochastic processes, respectively. . will be found useful by advanced undergraduate and graduate students and by professionals who wish to learn the basic concepts of modern probability theory and stochastic processes." (Vladimir P. Kurenok, Mathematical Reviews, Issue 2008 k)"The text is well written and the concepts and results motivated and explained. Most of the chapters include a section with exercises of varying difficulty. The material of the book has been used by the authors to teach one-year lecture courses at Princeton University and the University of Maryland to advanced undergraduate and graduate students. Summarising, the book is enjoyable and provides a concise well-motivated presentation of the material covered, suitable for lecture courses at an advanced level." (Evelyn Buckwar, Zentralblatt MATH, Vol. 1181, 2010)