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Proceedings Paper

Evolving neural network architecture
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Paper Abstract

This work investigates the application of a stochastic search technique, evolutionary programming, for developing self-organizing neural networks. The chosen stochastic search method is capable of simultaneously evolving both network architecture and weights. The number of synapses and neurons are incorporated into an objective function so that network parameter optimization is done with respect to computational costs as well as mean pattern error. Experiments are conducted using feedforward networks for simple binary mapping problems.

Paper Details

Date Published: 16 December 1992
PDF: 12 pages
Proc. SPIE 1766, Neural and Stochastic Methods in Image and Signal Processing, (16 December 1992); doi: 10.1117/12.130875
Show Author Affiliations
John R. McDonnell, Naval Command Control and Ocean Surveillance Ctr. (United States)
Donald E. Waagen, Naval Command Control and Ocean Surveillance Ctr. (United States)


Published in SPIE Proceedings Vol. 1766:
Neural and Stochastic Methods in Image and Signal Processing
Su-Shing Chen, Editor(s)

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