Event-Based State Estimation - A Stochastic Perspective (Paperback, Softcover reprint of the original 1st ed. 2016)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Studies in Systems, Decision and Control, 41
Release date:	August 2016
First published:	2016
Authors:	Dawei Shi • Ling/Shi • Tongwen Chen
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	208
Edition:	Softcover reprint of the original 1st ed. 2016
ISBN-13:	978-3-319-36911-2
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Reference & Interdisciplinary > Communication studies > Information theory > Cybernetics & systems theory Books > Professional & Technical > Energy technology & engineering > Electrical engineering > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > General Promotions
LSN:	3-319-36911-3
Barcode:	9783319369112

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