000			02715nmm a2200373 a 4500
001			00002982
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007			cr |uu|||uu|||
008			181210s1997 si a ob 001 0 eng d
040			_aWSPC _beng _cWSPC
020			_a9789812385383 _q(ebook)
020			_z9789810225162 _q(hbk.)
020			_z9789810241254 _q(pbk.)
050	0	4	_aQA76.87 _b.G77 1997
072		7	_aTEC _x009030 _2bisacsh
072		7	_aCOM _x014000 _2bisacsh
072		7	_aCOM _x004000 _2bisacsh
082	0	4	_a006.3/2 _223
100	1		_aGraupe, Daniel. _93609
245	1	0	_aPrinciples of artificial neural networks _h[electronic resource] / _cDaniel Graupe.
260			_aSingapore : _bWorld Scientific Publishing Co. Pte Ltd., _c©1997.
300			_a1 online resource (252 p.) : _bill.
490	0		_aAdvanced series in circuits and systems ; _vv. 3
538			_aMode of access: World Wide Web.
538			_aSystem requirements: Adobe Acrobat Reader.
588			_aTitle from web page (viewed December 10, 2018).
504			_aIncludes bibliographical references and indexes.
520			_a"This textbook is intended for a first-year graduate course on Artificial Neural Networks. It assumes no prior background in the subject and is directed to MS students in electrical engineering, computer science and related fields, with background in at least one programming language or in a programming tool such as Matlab, and who have taken the basic undergraduate classes in systems or in signal processing. The uniqueness of the book is in the breadth of its coverage over the range of all major artificial neural network approaches and in extensive hands-on case-studies on each and every neural network considered. These detailed case studies include complete program print-outs and results and deal with a range of problems, to illustrate the reader's ability to solve problems ranging from speech recognition, character recognition to control and signal processing problems, all on the basis of following the present text. Another unique aspect of the text is its coverage of important new topics of recurrent (time-cycling) networks and of large memory storage and retrieval problems. The text also attempts to show the reader how he can modify or combine one or more of the neural networks covered, to tailor them to a given problem which does not appear to fit any of the more standard designs, as is very often the case."-- _cPublisher's website.
650		0	_aNeural networks (Computer science) _93414
650		0	_aElectronic books. _920721
856	4	0	_uhttps://www.worldscientific.com/worldscibooks/10.1142/2982#t=toc _zAccess to full text is restricted to subscribers.
942			_cEBK
999			_c72560 _d72560