3 May 1988 Hardware Implementation Of An Artificial Neural Network
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Proceedings Volume 0882, Neural Network Models for Optical Computing; (1988); doi: 10.1117/12.944095
Event: 1988 Los Angeles Symposium: O-E/LASE '88, 1988, Los Angeles, CA, United States
Abstract
A hardware implementation of a lightly connected artificial neural network known as the Hogg-Huberman model (1) (2) is described. The hardware is built around NCR's Geometric Arithmetic Parallel Processor (GAPP) chip. A large perfor-mance gain is shown between this implementation and a simulation done in FORTRAN on a VAX 11/780. Even though the direct processor to processor communications are limited to nearest neighbors, models which require other connections can be implemented with this hardware.
© (1988) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ross A McClain, Charles H Rogers, William J.B Oldham, "Hardware Implementation Of An Artificial Neural Network", Proc. SPIE 0882, Neural Network Models for Optical Computing, (3 May 1988); doi: 10.1117/12.944095; https://doi.org/10.1117/12.944095
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KEYWORDS
Neural networks

Image processing

Array processing

Artificial neural networks

Detection and tracking algorithms

Binary data

Optical computing

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