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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Debasish Roy is currently working as Professor in the Computational Mechanics Laboratory at the Indian Institute of Science, Bangalore. He obtained his Ph.D. from the Indian Institute of Science, followed by post-doctoral research at the University of Innsbruck, Austria. Besides being a fellow of the Indian National Academy of Engineering, he has also held an Honorary Professorship in the School of Engineering, University of Aberdeen, and a distinguished visiting fellowship of the Royal Academy of Engineering, London. His areas of research include computational mechanics of non-classical continua, stochastic dynamical systems and optimization/inverse problems. He has published over 120 papers in journals of international repute, delivered keynote/invited lectures at many international conferences and served on editorial boards.
G. Visweswara Rao was Technical Advisor in ACS Design Consulting Private Limited, Bangalore. He received his Ph.D. from the Indian Institute of Science, Bangalore, in 1989. He has published several research papers in the areas of structural dynamics specific to earthquake engineering, nonlinear and random vibration, and structural control, and co-authored Elements of Structural Dynamics: A New Perspective (2012) with D. Roy. His areas of research include non-linear and stochastic structural dynamics.
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Librería: Powell's Bookstores Chicago, ABAA, Chicago, IL, Estados Unidos de America
Hardcover. Condición: Good Plus. Estado de la sobrecubierta: None. 1. Paper-covered boards, no jacket (as issued). Boards lightly creased. Bottom corner of rear board bumped and frayed along hinge; binding remains sound. Else fine. A nice study copy with crisp, clean internals. 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. Nº de ref. del artículo: 2033729
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Librería: Powell's Bookstores Chicago, ABAA, Chicago, IL, Estados Unidos de America
Hardcover. Condición: New. 1. Paper-covered boards. In shrinkwrap. 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. Nº de ref. del artículo: 2041405
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