000			03467nam a22005415i 4500
001			978-1-4614-4106-9
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005			20140220082814.0
007			cr nn 008mamaa
008			120814s2013 xxu| s |||| 0|eng d
020			_a9781461441069 _9978-1-4614-4106-9
024	7		_a10.1007/978-1-4614-4106-9 _2doi
050		4	_aTK5102.9
050		4	_aTA1637-1638
050		4	_aTK7882.S65
072		7	_aTTBM _2bicssc
072		7	_aUYS _2bicssc
072		7	_aTEC008000 _2bisacsh
072		7	_aCOM073000 _2bisacsh
082	0	4	_a621.382 _223
100	1		_aDiniz, Paulo S. R. _eauthor.
245	1	0	_aAdaptive Filtering _h[electronic resource] : _bAlgorithms and Practical Implementation / _cby Paulo S. R. Diniz.
250			_a4th ed. 2013.
264		1	_aBoston, MA : _bSpringer US : _bImprint: Springer, _c2013.
300			_aXXI, 652 p. 199 illus. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aIntroduction to Adaptive Filtering -- Fundamentals of Adaptive Filtering -- The Least-Mean-Square (LMS) Algorithm -- LMS-Based Algorithms -- Conventional RLS Adaptive Filter -- Data-Selective Adaptive Filtering -- Adaptive Lattice-Based RLS Algorithms -- Fast Transversal RLS Algorithms -- QR-Decomposition-Based RLS Filters -- Adaptive IIR Filters -- Nonlinear Adaptive Filtering -- Subband Adaptive Filters -- Blind Adaptive Filtering.
520			_aIn the fourth edition of Adaptive Filtering: Algorithms and Practical Implementation, author Paulo S.R. Diniz presents the basic concepts of adaptive signal processing and adaptive filtering in a concise and straightforward manner. The main classes of adaptive filtering algorithms are presented in a unified framework, using clear notations that facilitate actual implementation. The main algorithms are described in tables, which are detailed enough to allow the reader to verify the covered concepts. Many examples address problems drawn from actual applications. New material to this edition includes: Analytical and simulation examples in Chapters 4, 5, 6 and 10 Appendix E, which summarizes the analysis of set-membership algorithm Updated problems and references Providing a concise background on adaptive filtering, this book covers the family of LMS, affine projection, RLS and data-selective set-membership algorithms as well as nonlinear, sub-band, blind, IIR adaptive filtering, and more. Several problems are included at the end of chapters, and some of these problems address applications. A user-friendly MATLAB package is provided where the reader can easily solve new problems and test algorithms in a quick manner. Additionally, the book provides easy access to working algorithms for practicing engineers.
650		0	_aEngineering.
650		0	_aComputer engineering.
650		0	_aTelecommunication.
650		0	_aSystems engineering.
650	1	4	_aEngineering.
650	2	4	_aSignal, Image and Speech Processing.
650	2	4	_aCircuits and Systems.
650	2	4	_aCommunications Engineering, Networks.
650	2	4	_aElectrical Engineering.
650	2	4	_aControl.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9781461441052
856	4	0	_uhttp://dx.doi.org/10.1007/978-1-4614-4106-9
912			_aZDB-2-ENG
999			_c95064 _d95064