000			03484nam a22004815i 4500
001			978-0-387-68630-1
003			DE-He213
005			20250710084007.0
007			cr nn 008mamaa
008			100301s2007 xxu| s |||| 0|eng d
020			_a9780387686301 _a99780387686301
024	7		_a10.1007/978-0-387-68630-1 _2doi
082	0	4	_a621.382 _223
100	1		_aOgunfunmi, Tokunbo. _eauthor.
245	1	0	_aAdaptive Nonlinear System Identification _h[recurso electrónico] : _bThe Volterra and Wiener Model Approaches / _cby Tokunbo Ogunfunmi.
264		1	_aBoston, MA : _bSpringer US, _c2007.
300			_bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aSignals And Communication Technology, _x1860-4862
505	0		_ato Nonlinear Systems -- Polynomial Models of Nonlinear Systems -- Volterra and Wiener Nonlinear Models -- Nonlinear System Identification Methods -- to Adaptive Signal Processing -- Nonlinear Adaptive System Identification Based on Volterra Models -- Nonlinear Adaptive System Identification Based on Wiener Models (Part 1) -- Nonlinear Adaptive System Identification Based on Wiener Models (Part 2) -- Nonlinear Adaptive System Identification Based on Wiener Models (Part 3) -- Nonlinear Adaptive System Identification Based on Wiener Models (Part 4) -- Conclusions, Recent Results, and New Directions.
520			_aAdaptive Nonlinear System Identification: The Volterra and Wiener Model Approaches introduces engineers and researchers to the field of nonlinear adaptive system identification. The book includes recent research results in the area of adaptive nonlinear system identification and presents simple, concise, easy-to-understand methods for identifying nonlinear systems. These methods use adaptive filter algorithms that are well known for linear systems identification. They are applicable for nonlinear systems that can be efficiently modeled by polynomials. After a brief introduction to nonlinear systems and to adaptive system identification, the author presents the discrete Volterra model approach. This is followed by an explanation of the Wiener model approach. Adaptive algorithms using both models are developed. The performance of the two methods are then compared to determine which model performs better for system identification applications. Adaptive Nonlinear System Identification: The Volterra and Wiener Model Approaches is useful to graduates students, engineers and researchers in the areas of nonlinear systems, control, biomedical systems and in adaptive signal processing.
650		0	_aENGINEERING.
650		0	_aCOMPUTER VISION.
650		0	_aTELECOMMUNICATION.
650		0	_aSYSTEMS ENGINEERING.
650	1	4	_aENGINEERING.
650	2	4	_aSIGNAL, IMAGE AND SPEECH PROCESSING.
650	2	4	_aCONTROL, ROBOTICS, MECHATRONICS.
650	2	4	_aIMAGE PROCESSING AND COMPUTER VISION.
650	2	4	_aCIRCUITS AND SYSTEMS.
650	2	4	_aCOMMUNICATIONS ENGINEERING, NETWORKS.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387263281
830		0	_aSignals And Communication Technology, _x1860-4862
856	4	0	_uhttp://dx.doi.org/10.1007/978-0-387-68630-1 _zVer el texto completo en las instalaciones del CICY
912			_aZDB-2-ENG
942			_2ddc _cER
999			_c58003 _d58003