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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 _aGPFC
_2bicssc
072 7 _aTEC004000
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082 0 4 _a003
_223
100 1 _aShi, Dawei.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_958157
245 1 0 _aEvent-Based State Estimation
_h[electronic resource] :
_bA Stochastic Perspective /
_cby Dawei Shi, Ling Shi, Tongwen Chen.
250 _a1st ed. 2016.
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,
_x2198-4190 ;
_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 _aControl engineering.
_931970
650 0 _aProbabilities.
_94604
650 0 _aElectric power production.
_927574
650 0 _aSystem theory.
_93409
650 0 _aControl theory.
_93950
650 1 4 _aControl and Systems Theory.
_931972
650 2 4 _aProbability Theory.
_917950
650 2 4 _aElectrical Power Engineering.
_931821
650 2 4 _aSystems Theory, Control .
_931597
700 1 _aShi, Ling.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_958158
700 1 _aChen, Tongwen.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_958159
710 2 _aSpringerLink (Online service)
_958160
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319266046
776 0 8 _iPrinted edition:
_z9783319266053
776 0 8 _iPrinted edition:
_z9783319369112
830 0 _aStudies in Systems, Decision and Control,
_x2198-4190 ;
_v41
_958161
856 4 0 _uhttps://doi.org/10.1007/978-3-319-26606-0
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c80087
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