Stochastic Analysis and Diffusion Processes

Szerző: Gopinath Kallianpur

Nyelv:

Kötés: Puha kötésű

Kiadó: Oxford University Press

Elérhetőség: Kiadói készleten rendelésre

Küldés 17-26 napon belül

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Stochastic Analysis and Diffusion Processes presents a simple, mathematical introduction to Stochast...

Információk a könyvről

Szerző

Gopinath Kallianpur

Nyelv

Angol

Kötés

Könyv - Puha kötésű

Kiadva

2014

oldal

368

EAN

9780199657070

ISBN

0199657076

Enbook ID

02097189

Kiadó

Oxford University Press

Súly

560

Méretek

156 x 234 x 24

Teljes leírás

Stochastic Analysis and Diffusion Processes presents a simple, mathematical introduction to Stochastic Calculus and its applications. The book builds the basic theory and offers a careful account of important research directions in Stochastic Analysis. The breadth and power of Stochastic Analysis, and probabilistic behavior of diffusion processes are told without compromising on the mathematical details. Starting with the construction of stochastic processes, the book introduces Brownian motion and martingales. The book proceeds to construct stochastic integrals, establish the Ito formula, and discuss its applications. Next, attention is focused on stochastic differential equations (SDEs) which arise in modeling physical phenomena, perturbed by random forces. Diffusion processes are solutions of SDEs and form the main theme of this book. The Stroock-Varadhan martingale problem, the connection between diffusion processes and partial differential equations, Gaussian solutions of SDEs, and Markov processes with jumps are presented in successive chapters. The book culminates with a careful treatment of important research topics such as invariant measures, ergodic behavior, and large deviation principle for diffusions. Examples are given throughout the book to illustrate concepts and results. In addition, exercises are given at the end of each chapter that will help the reader to understand the concepts better. The book is written for graduate students, young researchers and applied scientists who are interested in stochastic processes and their applications. The reader is assumed to be familiar with probability theory at graduate level. The book can be used as a text for a graduate course on Stochastic Analysis.

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