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Proceedings Paper

An Efficient Algorithm For Predicting The Response Of A Laterally Inhibited Neural Network
Author(s): B. V.K. Vijaya Kumar; Michael Lemmon
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Paper Abstract

Neural networks are usually described mathematically using sets of coupled non-linear differential equations. Thus, we can determine the response of the network to any input stimulus by numerically integrating the corresponding differential equations (which can be computationally intensive). In this paper, a new algorithm is presented for determining the input-output behavior of laterally inhibited neural networks. This algorithm is based on an analytical understanding and thus does not involve any numerical integrations. Initial results indicate that this new algorithm provides a speed up of up to three orders of magnitude. We also propose a VLSI Systolic Array implementation of this algorithm.

Paper Details

Date Published: 6 December 1989
PDF: 8 pages
Proc. SPIE 1154, Real-Time Signal Processing XII, (6 December 1989); doi: 10.1117/12.962372
Show Author Affiliations
B. V.K. Vijaya Kumar, Carnegie Mellon University (United States)
Michael Lemmon, Carnegie Mellon University (United States)

Published in SPIE Proceedings Vol. 1154:
Real-Time Signal Processing XII
J. P. Letellier, Editor(s)

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