Abstract
Connectionist (or neural) networks consist of large numbers of relatively simple computational units. The units communicate nonsymbolically over links. The computation performed is embodied in the pattern of connectivity. Connectionist researchers hope to explain or reproduce human performance on pattern matching and other tasks which have proved resistant to traditional programming techniques. Roughly, they work on designing artificial brains. Because of the large numbers of units needed — the human brain has more than 10**10 neurons — networks useful for large, complex tasks will require hardware realizations. Work on VLSI networks is ongoing [1].
This work was done while the author was at Ricoh Corporation, San Jose, California.
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© 1990 Plenum Press, New York
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Fanty, M. (1990). An Extendible Connectionist Simulator. In: Tewksbury, S.K. (eds) Frontiers of Computing Systems Research. Frontiers of Computing Systems Research, vol 1. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-0633-7_9
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DOI: https://doi.org/10.1007/978-1-4613-0633-7_9
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