000			03310nam a22005415i 4500
001			978-3-319-26606-0
003			DE-He213
005			20200421111844.0
007			cr nn 008mamaa
008			151119s2016 gw | s |||| 0|eng d
020			_a9783319266060 _9978-3-319-26606-0
024	7		_a10.1007/978-3-319-26606-0 _2doi
050		4	_aTJ212-225
072		7	_aTJFM _2bicssc
072		7	_aTEC004000 _2bisacsh
082	0	4	_a629.8 _223
100	1		_aShi, Dawei. _eauthor.
245	1	0	_aEvent-Based State Estimation _h[electronic resource] : _bA Stochastic Perspective / _cby Dawei Shi, Ling Shi, Tongwen Chen.
264		1	_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2016.
300			_aXIII, 208 p. 37 illus., 32 illus. in color. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aStudies in Systems, Decision and Control, _x2198-4182 ; _v41
505	0		_aIntroduction -- Linear Gaussian Systems and Event-Based State Estimation -- Event-Triggered Sampling -- Approximate Optimal Filtering Approaches -- Constrained Optimization Approach -- Set-Valued Filtering Approach -- Probabilistic Approach -- Communications Rate Analysis -- Open Problems -- Appendices: Brief Review of Probability Theory; Linear Estimation Theory.
520			_aThis 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. .
650		0	_aEngineering.
650		0	_aSystem theory.
650		0	_aProbabilities.
650		0	_aControl engineering.
650		0	_aPower electronics.
650	1	4	_aEngineering.
650	2	4	_aControl.
650	2	4	_aProbability Theory and Stochastic Processes.
650	2	4	_aPower Electronics, Electrical Machines and Networks.
650	2	4	_aSystems Theory, Control.
700	1		_aShi, Ling. _eauthor.
700	1		_aChen, Tongwen. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783319266046
830		0	_aStudies in Systems, Decision and Control, _x2198-4182 ; _v41
856	4	0	_uhttp://dx.doi.org/10.1007/978-3-319-26606-0
912			_aZDB-2-ENG
942			_cEBK
999			_c55739 _d55739