Stochastic Dynamics,Filtering and Optimization/ Debasish Roy and G.Visweswara Rao

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Material type: Text

TextPublication details: Cambridge : Cambridge University Press, 2017.Description: xxxvii,709pISBN:

9781107182646

Subject(s):

DDC classification:

519.23 ROY/S

Summary: 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.

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Holdings
Item type	Current library	Home library	Call number	Status	Date due	Barcode
Book	Study Centre Alappuzha, University of Kerala Processing Center	Study Centre Alappuzha, University of Kerala	519.23 ROY/S (Browse shelf(Opens below))	Not For Loan		USCA5503

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Previous	519.2 LAR/I Introduction to probability theory and statistical inference/	519.2 REV/L Limit Theorems of Probability Theory/	519.202854 FRE/C A course in computational probability and statistics/	519.23 ROY/S Stochastic Dynamics,Filtering and Optimization/	519.233 LOS/F Finite Markov Processes and Their Applications/	519.233 REV/M Markov chains/	519.4 CHA/C Computational methods for data analysis/	Next

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.

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