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An Introduction To Stochastic Dynamics (cambridge Texts In Applied Mathematics) [Paperback]

Item : An Introduction To Stochastic Dynamics (cambridge Texts In Applied Mathematics) [Paperback]
Price : $71.99 (see below)
Category : Books
Author Author : Jinqiao Duan
ISBN-10 ISBN-10 : 1107428203
ISBN-13 ISBN-13 : 9781107428201
Publisher Publisher : Cambridge University Press
Pages Pages : 320
Binding Binding : Paperback
Item ID : 100002236

An accessible introduction for applied mathematicians to concepts and techniques for describing, quantifying, and understanding dynamics under uncertainty.This book serves as a concise introductory text on stochastic dynamics for applied mathematicians. Rich with examples, illustrations, and exercises with their solutions, this book provides an accessible introduction to concepts and techniques for describing, quantifying, and understanding dynamics under uncertainty, from analytical, deterministic, structural and numerical perspectives.This book serves as a concise introductory text on stochastic dynamics for applied mathematicians. Rich with examples, illustrations, and exercises with their solutions, this book provides an accessible introduction to concepts and techniques for describing, quantifying, and understanding dynamics under uncertainty, from analytical, deterministic, structural and numerical perspectives.The mathematical theory of stochastic dynamics has become an important tool in the modeling of uncertainty in many complex biological, physical, and chemical systems and in engineering applications  for example, gene regulation systems, neuronal networks, geophysical flows, climate dynamics, chemical reaction systems, nanocomposites, and communication systems. It is now understood that these systems are often subject to random influences, which can significantly impact their evolution. This book serves as a concise introductory text on stochastic dynamics for applied mathematicians and scientists. Starting from the knowledge base typical for beginning graduate students in applied mathematics, it introduces the basic tools from probability and analysis and then develops for stochastic systems the properties traditionally calculated for deterministic systems. The book's final chapter opens the door to modeling in non-Gaussian situations, typical of many real-world applications. Rich with examples, illustrations, and exercises with solutions, this book islÓ3

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