Evolving neural network architecture

John R. McDonnell; Donald E. Waagen

doi:10.1117/12.130875

16 December 1992 Evolving neural network architecture

John R. McDonnell, Donald E. Waagen

Proceedings Volume 1766, Neural and Stochastic Methods in Image and Signal Processing; (1992) https://doi.org/10.1117/12.130875
Event: San Diego '92, 1992, San Diego, CA, United States

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.

Citation Download Citation

John R. McDonnell and Donald E. Waagen "Evolving neural network architecture", Proc. SPIE 1766, Neural and Stochastic Methods in Image and Signal Processing, (16 December 1992); https://doi.org/10.1117/12.130875

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