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Stochastic Analysis and Diffusion Processes | Zookal Textbooks | Zookal Textbooks
  • Author(s) Gopinath Kallianpur / P Sundar
  • Edition
  • Published31st October 2013
  • PublisherOxford University Press UK
  • ISBN9780199657070
  • University course codes
Mathematical models in physics, engineering, biology, finance theory, and other fields are inherently stochastic rather than deterministic. Stochastic analysis provides the mathematics needed to understand any evolving phenomenon in the face of uncertainties. Stochastic Analysis and Diffusion Processes presents a simple, coherent introduction to stochastic calculus.This book starts right from the concept of random processes and
Brownian motion and builds the theory and research directions in a self-contained manner. The book grew out of the authors' lecture notes developed for teaching stochastic analysis over a number of
years.Examples are given throughout the book to illustrate concepts and results. In addition, exercises are given at the end of each chapter. 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.

Stochastic Analysis and Diffusion Processes

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  • Author(s) Gopinath Kallianpur / P Sundar
  • Edition
  • Published31st October 2013
  • PublisherOxford University Press UK
  • ISBN9780199657070
  • University course codes
Mathematical models in physics, engineering, biology, finance theory, and other fields are inherently stochastic rather than deterministic. Stochastic analysis provides the mathematics needed to understand any evolving phenomenon in the face of uncertainties. Stochastic Analysis and Diffusion Processes presents a simple, coherent introduction to stochastic calculus.This book starts right from the concept of random processes and
Brownian motion and builds the theory and research directions in a self-contained manner. The book grew out of the authors' lecture notes developed for teaching stochastic analysis over a number of
years.Examples are given throughout the book to illustrate concepts and results. In addition, exercises are given at the end of each chapter. 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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