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Principles of artificial neural networks

	Author(s):	Daniel Graupe
	Collection:	Advanced series on circuits and systems 6
	Publisher:	World Scientific
	Year:	2007
	Language:	English
	Pages:	320 pages
	Size:	3.47 MB
	Extension:	PDF

[tab] [content title="Description"]The book should serve as a text for a university graduate course or for an advanced undergraduate course on neural networks in engineering and computer science departments. It should also serve as a self-study course for engineers and computer scientists in the industry. Covering major neural network approaches and architectures with the theories, this text presents detailed case studies for each of the approaches, accompanied with complete computer codes and the corresponding computed results. The case studies are designed to allow easy comparison of network performance to illustrate strengths and weaknesses of the different networks. [/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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