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Stochastic Dynamics, Filtering and Optimization
This book introduces essential concepts in stochastic processes that interface seamlessly with applications of interest in science and engineering.
Debasish Roy (Author), G. Visweswara Rao (Author)
9781107182646, Cambridge University Press
Hardback, published 4 May 2017
742 pages
24.9 x 19 x 3.9 cm, 1.32 kg
Targeted at graduate students, researchers and practitioners in the field of science and engineering, this book gives a self-contained introduction to a measure-theoretic framework in laying out the definitions and basic concepts of random variables and stochastic diffusion processes. It then continues to weave into a framework of several practical tools and applications involving stochastic dynamical systems. These include tools for the numerical integration of such dynamical systems, nonlinear stochastic filtering and generalized Bayesian update theories for solving inverse problems and a new stochastic search technique for treating a broad class of non-convex optimization problems. MATLAB® codes for all the applications are uploaded on the companion website.
List of figures
List of tables
Preface
Dedication
Acronyms
1. Probability theory and random variables
2. Random variables: conditioning, convergence and simulation
3. An introduction to stochastic processes
4. Stochastic calculus and diffusion processes
5. Numerical solutions to stochastic differential equations
6. Non-Linear Stochastic Filtering and Recursive Monte Carlo Estimation
7. Nonlinear filters with gain-type additive updates
8. Improved numerical solutions to SDEs by change of measure
9. Evolutionary global optimization via change of measures: A Martingale Route
10. COMBEO – a new global optimization scheme by change of measures
Appendices
Bibliography
References.
Subject Areas: Mechanical engineering [TGB], Stochastics [PBWL], Optimization [PBU], Probability & statistics [PBT]