Adaptive Filtering Prediction and Control
(eBook)

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Published
Dover Publications, 2014.
Status
Available Online

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Format
eBook
Language
English
ISBN
9780486137728

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Citations

APA Citation, 7th Edition (style guide)

Graham C. Goodwin., Graham C. Goodwin|AUTHOR., & Kwai Sang Sin|AUTHOR. (2014). Adaptive Filtering Prediction and Control . Dover Publications.

Chicago / Turabian - Author Date Citation, 17th Edition (style guide)

Graham C. Goodwin, Graham C. Goodwin|AUTHOR and Kwai Sang Sin|AUTHOR. 2014. Adaptive Filtering Prediction and Control. Dover Publications.

Chicago / Turabian - Humanities (Notes and Bibliography) Citation, 17th Edition (style guide)

Graham C. Goodwin, Graham C. Goodwin|AUTHOR and Kwai Sang Sin|AUTHOR. Adaptive Filtering Prediction and Control Dover Publications, 2014.

MLA Citation, 9th Edition (style guide)

Graham C. Goodwin, Graham C. Goodwin|AUTHOR, and Kwai Sang Sin|AUTHOR. Adaptive Filtering Prediction and Control Dover Publications, 2014.

Note! Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy. Citation formats are based on standards as of August 2021.

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Grouped Work IDfc985846-d664-b945-6972-44109c17ea01-eng
Full titleadaptive filtering prediction and control
Authorgoodwin graham c
Grouping Categorybook
Last Update2023-10-09 19:08:45PM
Last Indexed2024-04-24 06:02:56AM

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First LoadedJun 21, 2022
Last UsedJun 21, 2022

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    [synopsis] => This unified survey of the theory of adaptive filtering, prediction, and control focuses on linear discrete-time systems and explores the natural extensions to nonlinear systems. In keeping with the importance of computers to practical applications, the authors emphasize discrete-time systems. Their approach summarizes the theoretical and practical aspects of a large class of adaptive algorithms. Ideal for advanced undergraduate and graduate classes, this treatment consists of two parts. The first section concerns deterministic systems, covering models, parameter estimation, and adaptive prediction and control. The second part examines stochastic systems, exploring optimal filtering and prediction, parameter estimation, adaptive filtering and prediction, and adaptive control. Extensive appendices offer a summary of relevant background material, making this volume largely self-contained. Readers will find that these theories, formulas, and applications are related to a variety of fields, including biotechnology, aerospace engineering, computer sciences, and electrical engineering.
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