Random Ordinary Differential Equations and Their Numerical Solution (Probability Theory and Stochastic Modelling #85) (Paperback)

Random Ordinary Differential Equations and Their Numerical Solution (Probability Theory and Stochastic Modelling #85) By Xiaoying Han, Peter E. Kloeden Cover Image
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Description


Makes recent results on the derivation of higher order numerical schemes for random ordinary differential equations (RODEs) available to a broader readership

Develops numerical methods for random ODEs (RODEs)

Highlights important applications, with a focus on dynamical behavior and the biological sciences

About the Author


Professor Peter E. Kloeden has wide interests in the applications of mathematical analysis, numerical analysis, stochastic analysis and dynamical systems. He is the coauthor of several influential books on nonautonomous dynamical systems, metric spaces of fuzzy sets, and in particular "Numerical Solutions of Stochastic Differential equations" (with E. Platen) published by Springer in 1992. Professor Kloeden is a Fellow of the Australian Mathematical Society and the Society of Industrial and Applied Mathematics. He was awarded the W.T. & Idalia Reid Prize from Society of Applied and Industrial Mathematics in 2006. His current interests focus on nonautonomous and random dynamical systems and their applications in the biological sciences. Professor Xiaoying Han's main research interests are in random and nonautonomous dynamical systems and their applications. In addition to mathematical analysis of dynamical systems, she is also interested in modeling and simulation of applied dynamical systems in biology, chemical engineering, ecology, material sciences, etc. She is the coauthor of the books "Applied Nonautonomous and Random Dynamical Systems" (with T. Caraballo) and "Attractors under Discretisation" (with P. E. Kloeden), published in the SpringerBrief series.
Product Details
ISBN: 9789811348433
ISBN-10: 981134843X
Publisher: Springer
Publication Date: December 11th, 2018
Pages: 250
Language: English
Series: Probability Theory and Stochastic Modelling