Stochastic Systems: Estimation, Identification, and Adaptive Control (Paperback)

P. R. Kumar, Pravin Varaiya

Edité par Society for Industrial Applied Mathematics,U.S., 2016
ISBN 10: 1611974259 / ISBN 13: 9781611974256
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Language: English . Brand New Book. Since its origins in the 1940s, the subject of decision making under uncertainty has grown into a diversified area with applications in several branches of engineering and in areas of the social sciences concerned with policy analysis and prescription. With the increase in computational capacity and the ability to collect and process huge quantities of data, an explosion of work in the area has been engendered. This book provides succinct and rigorous treatment of the foundations of stochastic control; a unified approach to filtering, estimation, prediction, and stochastic and adaptive control; and the conceptual framework necessary to understand current trends in stochastic control, data mining, learning, and robotics. It is ideal for students previously acquainted with probability theory and stochastic processes, who wish to learn more on decision making with uncertainty, and can be used as a course textbook for advanced undergraduate or first year graduate students. N° de réf. du libraire

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Synopsis : Since its origins in the 1940s, the subject of decision making under uncertainty has grown into a diversified area with application in several branches of engineering and in those areas of the social sciences concerned with policy analysis and prescription. These approaches required a computing capacity too expensive for the time, until the ability to collect and process huge quantities of data engendered an explosion of work in the area.

This book provides succinct and rigorous treatment of the foundations of stochastic control; a unified approach to filtering, estimation, prediction, and stochastic and adaptive control; and the conceptual framework necessary to understand current trends in stochastic control, data mining, machine learning, and robotics.

Audience: This book is recommended for those who have been introduced to probability theory and stochastic processes and want to learn more about decision making under uncertainty. It can be used as a one- or two-semester course textbook for advanced undergrad or first-year graduate students.

Contents: Chapter 1: Introduction; Chapter 2: State space models; Chapter 3: Properties of linear stochastic systems; Chapter 4: Controlled Markov chain model; Chapter 5: Input output models; Chapter 6: Dynamic programming; Chapter 7: Linear systems: estimation and control; Chapter 8: Infinite horizon dynamic programming; Chapter 9: Introduction to system identification; Chapter 10: Linear system identification; Chapter 11: Bayesian adaptive control; Chapter 12: Non-Bayesian adaptive control; Chapter 13: Self-tuning regulators for linear systems

Book Description: A succinct and rigorous treatment of the foundations of stochastic control, ideal for advanced students already acquainted with stochastic processes. This book presents a unified approach to filtering, estimation, prediction, and stochastic and adaptive control, while also providing the conceptual framework necessary to understand current trends.

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Titre : Stochastic Systems: Estimation, ...
Éditeur : Society for Industrial Applied Mathematics,U.S.
Date d'édition : 2016
Reliure : Paperback
Etat du livre : New

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Description du livre Society for Industrial Applied Mathematics,U.S., United States, 2016. Paperback. État : New. Language: English . Brand New Book. Since its origins in the 1940s, the subject of decision making under uncertainty has grown into a diversified area with application in several branches of engineering and in those areas of the social sciences concerned with policy analysis and prescription. These approaches required a computing capacity too expensive for the time, until the ability to collect and process huge quantities of data engendered an explosion of work in the area. This book provides:* Succinct and rigorous treatment of the foundations of stochastic control.* A unified approach to filtering, estimation, prediction, and stochastic and adaptive cools* The conceptual framework necessary to understand current trends in stochastic control, data mining, machine learning, and robotics. N° de réf. du libraire AAN9781611974256

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P. R. Kumar, Pravin Varaiya
Edité par Society for Industrial Applied Mathematics,U.S., United States (2016)
ISBN 10 : 1611974259 ISBN 13 : 9781611974256
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Description du livre Society for Industrial Applied Mathematics,U.S., United States, 2016. Paperback. État : New. Language: English . Brand New Book. Since its origins in the 1940s, the subject of decision making under uncertainty has grown into a diversified area with application in several branches of engineering and in those areas of the social sciences concerned with policy analysis and prescription. These approaches required a computing capacity too expensive for the time, until the ability to collect and process huge quantities of data engendered an explosion of work in the area. This book provides:* Succinct and rigorous treatment of the foundations of stochastic control.* A unified approach to filtering, estimation, prediction, and stochastic and adaptive cools* The conceptual framework necessary to understand current trends in stochastic control, data mining, machine learning, and robotics. N° de réf. du libraire AAN9781611974256

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Kumar, P. R.; Varaiya, Pravin
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