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Proceedings Paper

Nearest-Neighbor Non-Iterative Error Correcting Optical Associative Memory Processor
Author(s): Bruce L. Montgomery; B. V.K. Vijaya Kumar
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Paper Abstract

The Hopfield neural network model has recently been proposed as a method for optically determining the nearest-neighbor of a binary bipolar test vector from a set of binary bipolar reference vectors. We illustrate several drawbacks of this approach and introduce a new technique called direct storage nearest-neighbor (DSNN) algorithm to accomplish the same task. We provide a comparison of the two approaches and demonstrate the superiority of the proposed DSNN algorithm.

Paper Details

Date Published: 15 October 1986
PDF: 8 pages
Proc. SPIE 0638, Hybrid Image Processing, (15 October 1986); doi: 10.1117/12.964267
Show Author Affiliations
Bruce L. Montgomery, Carnegie-Mellon University (United States)
B. V.K. Vijaya Kumar, Carnegie-Mellon University (United States)


Published in SPIE Proceedings Vol. 0638:
Hybrid Image Processing
David P. Casasent; Andrew G. Tescher, Editor(s)

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