Overview
- Editors:
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José G. Delgado-Frias
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State University of New York at Binghamton, Binghamton, USA
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William R. Moore
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Oxford University, Oxford, UK
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Table of contents (30 chapters)
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Neural Networks on Multiprocessor Systems and Applications
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- Wayne Luk, Adrian Lawrence, Vincent Lok, Ian Page, Richard Stamper
Pages 197-206
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- G. Palm, A. Ultsch, K. Goser, U. Rückert
Pages 207-216
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- M. A. Styblinski, Jill R. Minick
Pages 217-229
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VLSI Machines for Artificial Intelligence
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- S. H. Lavington, C. J. Wang, N. Kasabov, S. Lin
Pages 231-242
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- Denis B. Howe, Krste Asanović
Pages 243-252
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- Mario Cannataro, Giandomenico Spezzano, Domenico Talia
Pages 253-263
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- Darren Rodohan, Raymond Glover
Pages 265-273
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- Alessandro De Gloria, Paolo Faraboschi, Mauro Olivieri
Pages 275-284
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- Pier Luigi Civera, Guido Masera, Massimo Ruo Roch
Pages 285-295
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- Danilo Demarchi, Gianluca Piccinini, Maurizio Zamboni
Pages 297-306
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- Takashi Yokota, Kazuo Seo
Pages 307-315
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Back Matter
Pages 317-320
About this book
Neural network and artificial intelligence algorithrns and computing have increased not only in complexity but also in the number of applications. This in turn has posed a tremendous need for a larger computational power that conventional scalar processors may not be able to deliver efficiently. These processors are oriented towards numeric and data manipulations. Due to the neurocomputing requirements (such as non-programming and learning) and the artificial intelligence requirements (such as symbolic manipulation and knowledge representation) a different set of constraints and demands are imposed on the computer architectures/organizations for these applications. Research and development of new computer architectures and VLSI circuits for neural networks and artificial intelligence have been increased in order to meet the new performance requirements. This book presents novel approaches and trends on VLSI implementations of machines for these applications. Papers have been drawn from a number of research communities; the subjects span analog and digital VLSI design, computer design, computer architectures, neurocomputing and artificial intelligence techniques. This book has been organized into four subject areas that cover the two major categories of this book; the areas are: analog circuits for neural networks, digital implementations of neural networks, neural networks on multiprocessor systems and applications, and VLSI machines for artificial intelligence. The topics that are covered in each area are briefly introduced below.
Editors and Affiliations
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State University of New York at Binghamton, Binghamton, USA
José G. Delgado-Frias
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Oxford University, Oxford, UK
William R. Moore