000			02148nam a2200325 a 4500
005			20250930131710.0
008			110321s2010 nju b 001 0 eng
020			_a9780471322702 _cRM275.25
039		9	_a201106161645 _bzaina _c201106161536 _dzaina _c201106011157 _drasyilla _y03-21-2011 _zrasyilla
090			_aQA76.87.C577 3
090			_aQA76.87 _b.C577
100	1		_aCirrincione, Giansalvo, _d1959-
245	1	0	_aNeural-based orthogonal data fitting : _bthe EXIN neural networks / _cGiansalvo Cirrincione, Maurizio Cirrincione.
260			_aHoboken, NJ : _bWiley, _c2010.
300			_axviii, 243 p. : _bill. ; _c24 cm.
490	0		_aWiley series in Adaptive & learning systems for signal processing, communications and control
504			_aIncludes bibliographical references and index.
520			_a'Written by three leaders in the field of neural based algorithms, Neural Based Orthogonal Data Fitting proposes several neural networks, all endowed with a complete theory which not only explains their behavior, but also compares them with the existing neural and traditional algorithms. The algorithms are studied from different points of view, including: as a differential geometry problem, as a dynamic problem, as a stochastic problem, and as a numerical problem. All algorithms have also been analyzed on real time problems (large dimensional data matrices) and have shown accurate solutions. Where most books on the subject are dedicated to PCA (principal component analysis) and consider MCA (minor component analysis) as simply a consequence, this is the fist book to start from the MCA problem and arrive at important conclusions about the PCA problem.'-- _cProvided by publisher.
650		0	_aNeural networks (Computer science) _960531
650		0	_aNumerical analysis.
650		0	_aOrthogonalization methods.
700	1		_aCirrincione, Maurizio, _d1961-
907			_a.b14975956 _b2021-05-28 _c2019-11-12
942			_c01 _n0 _kQA76.87.C577 3
914			_avtls003459667
990			_azsz
991			_aFakulti Kejuruteraan dan Alam Bina
998			_at _b2011-08-03 _cm _da _feng _gnju _y0 _z.b14975956
999			_c482408 _d482408