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Principles of Artificial Neural Networks : WS

	Author(s):	Daniel Graupe
	Collection:	Advanced Series in Circuits and Systems, Vol 3
	Publisher:	World Scientific Publishing Company
	Year:	1997
	Language:	English
	Pages:	252 pages
	Size:	1.83 MB
	Extension:	DJVU

[tab] [content title="Description"]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. [/content] [content title="Content"] [/content] [content title="About the author"]Daniel Graupe (M'71–SM'83–F'85) received the B.S.M.E., B.S.E.E., and Dipl. Eng. in electrical engineering degrees from the Technion, Israel Institute of Technology, and the Ph.D. degree in electrical engineering from the University of Liverpool, Liverpool. U.K.,He is currently a Professor of electrical engineering and computer science, Professor of bioengineering, and Adjunct Professor of physical medical and rehabilitation at the University of Illinois at Chicago. [/content] [/tab]

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