Recursive Estimation And Control For Stochastic Systems
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Recursive Estimation And Control For Stochastic Systems
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Author : Hanfu Chen
language : en
Publisher: John Wiley & Sons
Release Date : 1985
Recursive Estimation And Control For Stochastic Systems written by Hanfu Chen and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985 with Mathematics categories.
This self-contained reference for statisticians and engineers in system and control theory, analyzes the effect of convergent recursive estimation algorithms and stochastic approximation on the dependent noise case and the classic independent case. It discusses control and adaptive control problems related to recursive estimation, and introduces the combined probabilistic and differential equation method of data analysis.
Stochastic Approximation And Recursive Estimation
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Author : M. B. Nevel'son
language : en
Publisher: American Mathematical Soc.
Release Date : 1976-10-01
Stochastic Approximation And Recursive Estimation written by M. B. Nevel'son and has been published by American Mathematical Soc. this book supported file pdf, txt, epub, kindle and other format this book has been release on 1976-10-01 with Mathematics categories.
This book is devoted to sequential methods of solving a class of problems to which belongs, for example, the problem of finding a maximum point of a function if each measured value of this function contains a random error. Some basic procedures of stochastic approximation are investigated from a single point of view, namely the theory of Markov processes and martingales. Examples are considered of applications of the theorems to some problems of estimation theory, educational theory and control theory, and also to some problems of information transmission in the presence of inverse feedback.
Recursive Identification And Parameter Estimation
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Author : Han-Fu Chen
language : en
Publisher: CRC Press
Release Date : 2014-06-23
Recursive Identification And Parameter Estimation written by Han-Fu Chen and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-23 with Mathematics categories.
Recursive Identification and Parameter Estimation describes a recursive approach to solving system identification and parameter estimation problems arising from diverse areas. Supplying rigorous theoretical analysis, it presents the material and proposed algorithms in a manner that makes it easy to understand—providing readers with the modeling and identification skills required for successful theoretical research and effective application. The book begins by introducing the basic concepts of probability theory, including martingales, martingale difference sequences, Markov chains, mixing processes, and stationary processes. Next, it discusses the root-seeking problem for functions, starting with the classic RM algorithm, but with attention mainly paid to the stochastic approximation algorithms with expanding truncations (SAAWET) which serves as the basic tool for recursively solving the problems addressed in the book. The book not only identifies the results of system identification and parameter estimation, but also demonstrates how to apply the proposed approaches for addressing problems in a range of areas, including: Identification of ARMAX systems without imposing restrictive conditions Identification of typical nonlinear systems Optimal adaptive tracking Consensus of multi-agents systems Principal component analysis Distributed randomized PageRank computation This book recursively identifies autoregressive and moving average with exogenous input (ARMAX) and discusses the identification of non-linear systems. It concludes by addressing the problems arising from different areas that are solved by SAAWET. Demonstrating how to apply the proposed approaches to solve problems across a range of areas, the book is suitable for students, researchers, and engineers working in systems and control, signal processing, communication, and mathematical statistics.
Stochastic Systems
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Author : P. R. Kumar
language : en
Publisher: SIAM
Release Date : 2015-12-15
Stochastic Systems written by P. R. Kumar and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-15 with Mathematics categories.
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.?
Stochastic Approximation And Recursive Estimation
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Author : Mikhail Borisovich Nevelʹson
language : en
Publisher:
Release Date : 1976
Stochastic Approximation And Recursive Estimation written by Mikhail Borisovich Nevelʹson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1976 with Estimation theory categories.
Stochastic Processes Estimation And Control
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Author : Jason L. Speyer
language : en
Publisher: SIAM
Release Date : 2008-11-06
Stochastic Processes Estimation And Control written by Jason L. Speyer and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-11-06 with Mathematics categories.
The authors provide a comprehensive treatment of stochastic systems from the foundations of probability to stochastic optimal control. The book covers discrete- and continuous-time stochastic dynamic systems leading to the derivation of the Kalman filter, its properties, and its relation to the frequency domain Wiener filter aswell as the dynamic programming derivation of the linear quadratic Gaussian (LQG) and the linear exponential Gaussian (LEG) controllers and their relation to HÝsubscript 2¨ and HÝsubscript Ýinfinity¨¨ controllers and system robustness. This book is suitable for first-year graduate students in electrical, mechanical, chemical, and aerospace engineering specializing in systems and control. Students in computer science, economics, and possibly business will also find it useful.
Stochastic Approximation And Recursive Estimation
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Author : Michail Borisovič Nevel'son
language : en
Publisher:
Release Date : 1973
Stochastic Approximation And Recursive Estimation written by Michail Borisovič Nevel'son and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1973 with Estimation theory categories.
Recursive Estimation And Time Series Analysis
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Author : Peter C. Young
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-08-04
Recursive Estimation And Time Series Analysis written by Peter C. Young and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-08-04 with Technology & Engineering categories.
This is a revised version of the 1984 book of the same name but considerably modified and enlarged to accommodate the developments in recursive estimation and time series analysis that have occurred over the last quarter century. Also over this time, the CAPTAIN Toolbox for recursive estimation and time series analysis has been developed at Lancaster, for use in the MatlabTM software environment (see Appendix G). Consequently, the present version of the book is able to exploit the many computational routines that are contained in this widely available Toolbox, as well as some of the other routines in MatlabTM and its other toolboxes. The book is an introductory one on the topic of recursive estimation and it demonstrates how this approach to estimation, in its various forms, can be an impressive aid to the modelling of stochastic, dynamic systems. It is intended for undergraduate or Masters students who wish to obtain a grounding in this subject; or for practitioners in industry who may have heard of topics dealt with in this book and, while they want to know more about them, may have been deterred by the rather esoteric nature of some books in this challenging area of study.
Recursive Estimation And Control For Stochastic Systems
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Author : Hanfu Chen
language : en
Publisher: John Wiley & Sons
Release Date : 1985
Recursive Estimation And Control For Stochastic Systems written by Hanfu Chen and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985 with Mathematics categories.
This self-contained reference for statisticians and engineers in system and control theory, analyzes the effect of convergent recursive estimation algorithms and stochastic approximation on the dependent noise case and the classic independent case. It discusses control and adaptive control problems related to recursive estimation, and introduces the combined probabilistic and differential equation method of data analysis.
Bounded Dynamic Stochastic Systems
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Author : Hong Wang
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Bounded Dynamic Stochastic Systems written by Hong Wang and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Technology & Engineering categories.
Over the past decades, although stochastic system control has been studied intensively within the field of control engineering, all the modelling and control strategies developed so far have concentrated on the performance of one or two output properties of the system. such as minimum variance control and mean value control. The general assumption used in the formulation of modelling and control strategies is that the distribution of the random signals involved is Gaussian. In this book, a set of new approaches for the control of the output probability density function of stochastic dynamic systems (those subjected to any bounded random inputs), has been developed. In this context, the purpose of control system design becomes the selection of a control signal that makes the shape of the system outputs p.d.f. as close as possible to a given distribution. The book contains material on the subjects of: - Control of single-input single-output and multiple-input multiple-output stochastic systems; - Stable adaptive control of stochastic distributions; - Model reference adaptive control; - Control of nonlinear dynamic stochastic systems; - Condition monitoring of bounded stochastic distributions; - Control algorithm design; - Singular stochastic systems. A new representation of dynamic stochastic systems is produced by using B-spline functions to descripe the output p.d.f. Advances in Industrial Control aims to report and encourage the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.