Event-Based State Estimation

A Stochastic Perspective

By: Dawei Shi, Tongwen Chen, Ling Shi

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Paperback | 23 August 2016

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Paperback
224 Pages

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23.5 x 15.5 x 1.19

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This book explores event-based estimation problems. It shows how several stochastic approaches are developed to maintain estimation performance when sensors perform their updates at slower rates only when needed.

The self-contained presentation makes this book suitable for readers with no more than a basic knowledge of probability analysis, matrix algebra and linear systems. The introduction and literature review provide information, while the main content deals with estimation problems from four distinct angles in a stochastic setting, using numerous illustrative examples and comparisons. The text elucidates both theoretical developments and their applications, and is rounded out by a review of open problems.

This book is a valuable resource for researchers and students who wish to expand their knowledge and work in the area of event-triggered systems. At the same time, engineers and practitioners in industrial process control will benefit from the event-triggering technique that reduces communication costs and improves energy efficiency in wireless automation applications.

Industry Reviews

"This book addresses essentially the engineers (or researchers and students interested in the area of event-trigged systems). The subject turns around event-based estimation problems in a stochastic setting. This document is self-contained and it is readable with just a basic knowledge of probability theory, Kalman filtering theory, and linear algebra. ... This book is clear and well written. The results presented are proven, and each chapter contains notes and references." (B©n©dicte Puig, zbMATH 1331.62010, 2016)

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