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Proceedings Paper

Neural networks implementation on a parallel machine
Author(s): Chung Ching Wang; Behrooz A. Shirazi
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Paper Abstract

As more supporting theory and applications for neural nets are being developed the hardware implementation of neural nets becomes more important. However most of the existing hardware implementations of neural nets suffer from various weaknesses. Such problems range from inadequate support for parallelism to high communication overhead. In this paper we propose the design of a dataflow-based multiprocessor system for efficiently implementmg asynchronous highly parallel neural nets. L

Paper Details

Date Published: 1 March 1991
PDF: 6 pages
Proc. SPIE 1396, Applications of Optical Engineering: Proceedings of OE/Midwest '90, (1 March 1991); doi: 10.1117/12.25811
Show Author Affiliations
Chung Ching Wang, Southern Methodist Univ. (United States)
Behrooz A. Shirazi, Univ. of Texas/Arlington (United States)

Published in SPIE Proceedings Vol. 1396:
Applications of Optical Engineering: Proceedings of OE/Midwest '90
Rudolph P. Guzik; Hans E. Eppinger; Richard E. Gillespie; Mary Kathryn Dubiel; James E. Pearson, Editor(s)

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