MARC View

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003			KUKTEM
005			20251117150339.0
008			110411t2010 njuaf f b 001 0 eng d
020			_a9780471322702 (hardback)
020			_a0471322709 (hardback)
039		9	_a201109261603 _bfauzi _c201109261603 _dfauzi _c201107140034 _dVLOAD _y201104111026 _zsafura
040			_aUMP
090			_aQA76.87 .C57 2010
100	1		_aCirrincione, Giansalvo
245	1	0	_aNeural based orthogonal data fitting : _bthe EXIN neural networks / _cGiansalvo Cirrincione, Maurizio Cirrincione
260			_aHoboken, NJ : _bJohn Wiley & Sons, _cc2010
300			_axviii, 243 p., [12] p. of plates : _bill. (some col.) ; _c25 cm.
490	1		_aAdaptive and learning systems for signal processing, communication, and control
504			_aIncludes bibliographical references (p. 227-237) and index
520			_aWritten 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)
650		0	_aNumerical analysis
650		0	_aOrthogonalization methods
700	1		_aCirrincione, Maurizio
830		0	_aAdaptive and learning systems for signal processing, communication, and control
999			_aVIRTUA40 _c56514 _d56520
999			_aVTLSSORT00800200020104000900100024502600300049005040520065006501650270008300*9991