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020 _a9784431557388
_9978-4-431-55738-8
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050 4 _aTA1637-1638
050 4 _aTK7882.S65
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082 0 4 _a621.382
_223
100 1 _aOzeki, Kazuhiko.
_eauthor.
245 1 0 _aTheory of Affine Projection Algorithms for Adaptive Filtering
_h[recurso electrónico] /
_cby Kazuhiko Ozeki.
264 1 _aTokyo :
_bSpringer Japan :
_bImprint: Springer,
_c2016.
300 _aXII, 223 p. 32 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aMathematics for Industry,
_x2198-350X ;
_v22
505 0 _aIntroduction -- Classical Adaptation Algorithms -- Affine Projection Algorithm -- Family of Affine Projection Algorithms -- Convergence Behavior of APA -- Reduction of Computational Complexity -- Kernel Affine Projection Algorithm -- Variable Parameter APAs -- Appendix; Matrices.
520 _aThis book focuses on theoretical aspects of the affine projection algorithm (APA) for adaptive filtering. The APA is a natural generalization of the classical, normalized least-mean-squares (NLMS) algorithm. The book first explains how the APA evolved from the NLMS algorithm, where an affine projection view is emphasized. By looking at those adaptation algorithms from such a geometrical point of view, we can find many of the important properties of the APA, e.g., the improvement of the convergence rate over the NLMS algorithm especially for correlated input signals. After the birth of the APA in the mid-1980s, similar algorithms were put forward by other researchers independently from different perspectives. This book shows that they are variants of the APA, forming a family of APAs. Then it surveys research on the convergence behavior of the APA, where statistical analyses play important roles. It also reviews developments of techniques to reduce the computational complexity of the APA, which are important for real-time processing. It covers a recent study on the kernel APA, which extends the APA so that it is applicable to identification of not only linear systems but also nonlinear systems. The last chapter gives an overview of current topics on variable parameter APAs. The book is self-contained, and is suitable for graduate students and researchers who are interested in advanced theory of adaptive filtering.
650 0 _aEngineering.
650 0 _aMathematical models.
650 0 _aProjective geometry.
650 0 _aApplied mathematics.
650 0 _aEngineering mathematics.
650 1 4 _aEngineering.
650 2 4 _aSignal, Image and Speech Processing.
650 2 4 _aMathematical Modeling and Industrial Mathematics.
650 2 4 _aAppl.Mathematics/Computational Methods of Engineering.
650 2 4 _aProjective Geometry.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9784431557371
830 0 _aMathematics for Industry,
_x2198-350X ;
_v22
856 4 0 _zLibro electrónico
_uhttp://148.231.10.114:2048/login?url=http://dx.doi.org/10.1007/978-4-431-55738-8
912 _aZDB-2-ENG
942 _cLIBRO_ELEC
999 _c225573
_d225573