000			01473nam a2200301 i 4500
008			130529s2009 njua b 00110 eng d
020			_a9780131293762
020			_a0131293761
040			_aBAUN _beng _cBAUN _erda
049			_aBAUN_MERKEZ
050	0	4	_aQA76.87 _bH39 2009
100	1		_aHaykin, Simon S., _d1931-
245	1	0	_aNeural networks and learning machines / _cSimon Haykin.
250			_a3. baskı
264		1	_aUpper Saddle River, N.J. : _bPearson, _c[2009]
264		4	_c©2009
300			_a934 pages : _billustrations ; _c23 cm.
336			_2rdacontent _atext _btxt
337			_2rdamedia _aunmediated _bn
338			_2rdacarrier _avolume _bnc
504			_aIncludes bibliographical references and index.
505	0	0	_t-- Rosenblatt's perceptron _t-- Model building through regression _t-- The least-mean-square algorithm _t-- Multilayer perceptrons _t-- Kernel methods and radial-basis function networks _t-- Support vector machines _t-- Regularization theory _t-- Principal-components analysis _t-- Self-organizing maps _t-- Information-theoretic learning models _t-- Stochastic methods rooted in statistical mechanics _t-- Dynamic programming _t-- Neurodynamics _t-- Bayseian filtering for state estimation of dynamic systems _t-- Dynamically driven recurrent networks.
650		0	_aNeural networks (Computer science)
650		0	_aNeural networks (Computer science) _vProblems, exercises, etc.
900			_a34801
900			_bsatın
942			_2lcc _cKT
999			_c31955 _d31955