MARC Record from marc_columbia

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001 15099711
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008 140607t20142014flua ob 001 0 eng d
035 $a(OCoLC)ocn881162708
035 $a(NNC)15099711
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019 $a881365370$a887193152$a1065868608$a1281715967
020 $a9781466568860$q(electronic bk.)
020 $a1466568860$q(electronic bk.)
020 $a1306866804$q(electronic bk.)
020 $a9781306866804$q(electronic bk.)
020 $a1466568844$q(Hardback ;$qacid-free paper)
020 $a9781466568846$q(Hardback ;$qacid-free paper)
020 $z9781466568846
020 $z9781138034280
024 7 $a10.1201/b17078$2doi
035 $a(OCoLC)881162708$z(OCoLC)881365370$z(OCoLC)887193152$z(OCoLC)1065868608$z(OCoLC)1281715967
037 $a617931$bMIL
050 4 $aTA168
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082 04 $a620.001171$223
084 $aMAT003000$aMAT029010$aTEC007000$2bisacsh
049 $aZCUA
100 1 $aChen, Hanfu,$eauthor.
245 10 $aRecursive identification and parameter estimation /$cHan-Fu Chen, Wenxiao Zhao.
264 1 $aBoca Raton, FL :$bCRC Press/Taylor and Francis Group,$c[2014]
264 4 $c©2014
300 $a1 online resource (xiii, 426 pages) :$billustrations
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
347 $adata file
588 0 $aPrint version record.
504 $aIncludes bibliographical references and index.
505 0 $aDependent Random Vectors -- Recursive Parameter Estimation -- Recursive Identification for ARMAX Systems -- Recursive Identification for Nonlinear Systems -- Other Problems Reducible to Parameter Estimation -- Appendix A: Proof of Some Theorems in Chapter 1 -- Appendix B: Nonnegative Matrices.
520 $aRecursive Identification and Parameter Estimation describes a recursive approach to solving system identification and parameter estimation problems arising from diverse areas. Supplying rigorous theoretical analysis, it presents the material and proposed algorithms in a manner that makes it easy to understand?providing readers with the modeling and identification skills required for successful theoretical research and effective application. The book begins by introducing the basic concepts of probability theory, including martingales, martingale difference sequences, Markov chains, mixing processes, and stationary processes. Next, it discusses the root-seeking problem for functions, starting with the classic RM algorithm, but with attention mainly paid to the stochastic approximation algorithms with expanding truncations (SAAWET) which serves as the basic tool for recursively solving the problems addressed in the book. The book not only identifies the results of system identification and parameter estimation, but also demonstrates how to apply the proposed approaches for addressing problems in a range of areas, including: Identification of ARMAX systems without imposing restrictive conditions Identification of typical nonlinear systems Optimal adaptive tracking Consensus of multi-agents systems Principal component analysis Distributed randomized PageRank computation This book recursively identifies autoregressive and moving average with exogenous input (ARMAX) and discusses the identification of non-linear systems. It concludes by addressing the problems arising from different areas that are solved by SAAWET. Demonstrating how to apply the proposed approaches to solve problems across a range of areas, the book is suitable for students, researchers, and engineers working in systems and control, signal processing, communication, and mathematical statistics.
650 0 $aSystems engineering$xMathematics.
650 0 $aParameter estimation.
650 0 $aRecursive functions.
650 6 $aIngénierie des systèmes$xMathématiques.
650 6 $aEstimation d'un paramètre.
650 6 $aFonctions récursives.
650 7 $aTECHNOLOGY & ENGINEERING$xEngineering (General)$2bisacsh
650 7 $aTECHNOLOGY & ENGINEERING$xReference.$2bisacsh
650 7 $aParameter estimation.$2fast$0(OCoLC)fst01052990
650 7 $aRecursive functions.$2fast$0(OCoLC)fst01091984
700 1 $aZhao, Wenxiao,$eauthor.
776 08 $iPrint version:$aChen, Hanfu.$tRecursive identification and parameter estimation.$dBoca Raton : CRC Press, Taylor & Francis Group, [2014]$z9781466568846$w(DLC) 2014013190$w(OCoLC)796752384
856 40 $uhttp://www.columbia.edu/cgi-bin/cul/resolve?clio15099711$zTaylor & Francis eBooks
852 8 $blweb$hEBOOKS