000			01475cam a2200337 a 4500
001			u3030
003			SA-PMU
005			20210418124605.0
008			070608s2007 si a b 001 0 eng c
010			_a 2008270006
040			_aYDXCP _beng _cYDX _dBAKER _dBTCTA _dNBU _dYDXCP _dCUS _dIAY _dUMC _dDLC _dIG# _dU6C _dOKU _dDEBBG _dOCL
020			_a9812706240
020			_a9789812706249
035			_a(OCoLC)141384911
042			_apcc
050	0	0	_aQA76.87 _bG77 2007
082	0	0	_a006.3/2 _222
100	1		_aGraupe, Daniel.
245	1	0	_aPrinciples of artificial neural networks / _cDaniel Graupe.
250			_a2nd ed.
260			_aSingapore ; _aHackensack, N.J. : _bWorld Scientific, _cc2007.
300			_axv, 303 p. : _bill. ; _c26 cm.
490	1		_aAdvanced series on circuits and systems ; _vvol. 6
504			_aIncludes bibliographical references (p. 291-297) and indexes.
505	0		_aFundamentals of biological neural networks -- Basic principles of ANNs and their early structures -- The perceptron -- The madaline -- Back propagation -- Hopefield networks -- Counter propagation -- Adaptive resonance theory -- The cognitron and the neocognitron -- Statistical training -- Recurrent (time cycling) back propagation networks -- Large scale memory storage and retrieval (LAMSTAR) network.
650		0	_aNeural networks (Computer science)
830		0	_aAdvanced series on circuits and systems ; _vv. 6.
942			_cBOOK
994			_aZ0 _bSUPMU
596			_a1
999			_c8660 _d8660