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008 191202s2014 enk g b 001 0 eng d
010 $a 2013943837
015 $aGBB398937$2bnb
020 $a9780199657070 (pbk.) :$cNT$1748
040 $aTWTNM$beng$dTWTNM
050 00$aQA274$b.K338 2014
082 04$a519.233$222
100 1 $aKallianpur, G.,$eauthor.
245 10$aStochastic analysis and diffusion processes /$cGopinath Kallianpur and P. Sundar.
250 $aFirst edition.
260 $aOxford, United Kingdom :$bOxford University Press,$c2014.
300 $axi, 352 p. ;$c24 cm.
490 1 $aOxford graduate texts in mathematics ;$v24.
504 $aIncludes bibliographical references (pages 347-350) and index.
505 0 $aIntroduction to stochastic processes -- Brownian motion -- Elements of Martingale theory -- Analytic tools for Brownian motion -- Stochastic integration -- Stochastic differential equations -- The Martingale problem -- Probability theory and partial differential equations -- Gaussian solutions -- Jump Markov processes -- Invariant measures and ergodicity -- Large deviations for diffusions.
520 $a"Stochastic Analysis and Diffusion Processes presents a simple, mathematical introduction to Stochastic Calculus and its applications. The book builds the basic theory and offers a careful account of important research directions in Stochastic Analysis. The breadth and power of Stochastic Analysis, and probabilistic behavior of diffusion processes are told without compromising on the mathematical details. Starting with the construction of stochastic processes, the book introduces Brownian motion and martingales. The book proceeds to construct stochastic integrals, establish the It formula, and discuss its applications. Next, attention is focused on stochastic differential equations (SDEs) which arise in modeling physical phenomena, perturbed by random forces. Diffusion processes are solutions of SDEs and form the main theme of this book. The Stroock-Varadhan martingale problem, the connection between diffusion processes and partial differential equations, Gaussian solutions of SDEs, and Markov processes with jumps are presented in successive chapters. The book culminates with a careful treatment of important research topics such as invariant measures, ergodic behavior, and large deviation principle for diffusions. Examples are given throughout the book to illustrate concepts and results. In addition, exercises are given at the end of each chapter that will help the reader to understand the concepts better. The book is written for graduate students, young researchers and applied scientists who are interested in stochastic processes and their applications. The reader is assumed to be familiar with probability theory at graduate level. The book can be used as a text for a graduate course on Stochastic Analysis." --$cProvided by publisher.
650 0$aDiffusion processes.
650 0$aStochastic analysis.
700 1 $aSundar, P.$q(Padmanabhan),$eauthor.
830 0$aOxford graduate texts in mathematics ;$v24.