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Proceedings Paper

Imposing a temporal structure in neural networks
Author(s): Lalit Gupta; Mohammed R. Sayeh; Anand M. Upadhye
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Paper Abstract

Although neural networks are very effective pattern classifiers a major limitation is that they are not suitable for classifying patterns with Inherent time-variations. This paper describes an approach to incorporate a temporal structure in a neural network system which wifi accomodate the time variations in local feature sets encountered in problems such as partial shape classification. 1.

Paper Details

Date Published: 1 March 1991
PDF: 4 pages
Proc. SPIE 1396, Applications of Optical Engineering: Proceedings of OE/Midwest '90, (1 March 1991); doi: 10.1117/12.25820
Show Author Affiliations
Lalit Gupta, Southern Illinois Univ./Carbondale (United States)
Mohammed R. Sayeh, Southern Illinois Univ./Carbondale (United States)
Anand M. Upadhye, Southern Illinois Univ./Carbondale (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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