Stochastic models, estimation and control by Peter S. Maybeck

Cover of: Stochastic models, estimation and control | Peter S. Maybeck

Published by Academic Press in New York .

Written in English

Read online

Subjects:

  • System analysis.,
  • Control theory.,
  • Estimation theory.

Edition Notes

Includes bibliographies and index.

Book details

StatementPeter S. Maybeck.
SeriesMathematics in science and engineering ;, v. 141
Classifications
LC ClassificationsQA402 .M37
The Physical Object
Pagination3 v. :
ID Numbers
Open LibraryOL4721691M
ISBN 100124807011
LC Control Number78008836

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Stochastic models, estimation, and control by Peter S. Maybeck,Academic Press edition, in EnglishCited by: Stochastic Processes, Estimation, and Control is divided into three related sections. First, the authors present the concepts of probability theory, random variables, and stochastic processes, which lead to the topics of expectation, conditional expectation, and discrete-time estimation and the Kalman filter.

This importance class of stochastic estimation problems has ramifications for the estimation and control theory presented in the remainder of this book. Minimum Variance Estimation. The thought may have crossed your mind that conditional expectation is an odd subject for a book.

Discrete-time Stochastic Systems gives a comprehensive introduction to the estimation and control of dynamic stochastic systems and provides complete derivations of key results such as the basic relations for Wiener filtering.

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Estimation, Simulation, and Control (Spall, J.C.; ) [book review] Abstract: This comprehensive book offers main pages divided into 17 chapters. In addition, five very useful and clearly written appendices are provided, covering multivariate analysis, basic tests in statistics, probability theory and convergence, random number generators Cited by: Additional Physical Format: Online version: Maybeck, Peter S.

Stochastic models, estimation and control. New York: Academic Press, (OCoLC) ×Close. The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data.

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Stochastic models, estimation, and control / [Peter S Maybeck]. Stochastic Models, Estimation, and Control: Volume 3: Maybeck, Peter S.: Books - or: Peter S. Maybeck.

The major themes of this course are estimation and control of dynamic systems. Preliminary topics begin with reviews of probability and random variables.

Next, classical and state-space descriptions of random processes and their propagation through linear systems are introduced, followed by frequency domain design of filters and compensators. From there, the Kalman. Peter S. Maybeck is the author of Stochastic Models, Estimation And Control ( avg rating, 2 ratings, 1 review, published ), Stochastic Models, Es 2/5.

As more applications are found, interest in Hidden Markov Models continues to grow. Following comments and feedback from colleagues, students and other working with Hidden Markov Models the corrected 3rd printing of this volume contains clarifications, improvements and some new material, including.Lin J and Michailidis G () Regularized estimation and testing for high-dimensional multi-block vector-autoregressive models, The Journal of Machine Learning Research,(), Online publication date: 1-Janadshelp[at] The ADS is operated by the Smithsonian Astrophysical Observatory under NASA Cooperative Agreement NNX16AC86AAuthor: P.

S. Maybeck, E. J. Balder.

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