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Proceedings Paper

Theoretical and experimental analysis of the first layer in neural networks for 3D pattern recognition
Author(s): Jesus Figueroa-Nazuno; A. Vazquez-Nava; E. Vargas Medina
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Paper Abstract

The behavior of the first layer of a weightless artificial neural network is analyzed in this paper. The way in which the neural network receives external information changes according to different probability distribution functions that control data sampling from many different patterns. This paper describes the architecture of this system, and shows the effect of the different probability distribution functions over 3-dimensional pattern recognition.

Paper Details

Date Published: 1 July 1992
PDF: 11 pages
Proc. SPIE 1710, Science of Artificial Neural Networks, (1 July 1992); doi: 10.1117/12.140106
Show Author Affiliations
Jesus Figueroa-Nazuno, U.N.A.M. (Mexico)
A. Vazquez-Nava, U.N.A.M. (Mexico)
E. Vargas Medina, U.N.A.M. (Mexico)

Published in SPIE Proceedings Vol. 1710:
Science of Artificial Neural Networks
Dennis W. Ruck, Editor(s)

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