Accession Number:

ADA273134

Title:

Evolving Neural Network Connectivity

Descriptive Note:

Professional paper

Corporate Author:

NAVAL COMMAND CONTROL AND OCEAN SURVEILLANCE CENTER RDT AND E DIV SAN DIEGO CA

Personal Author(s):

Report Date:

1993-10-01

Pagination or Media Count:

8.0

Abstract:

This work investigates the application of evolutionary programming, a stochastic search technique, for determining connectivity in feedforward neural networks. The method is capable of simultaneously evolving both the connection scheme and the network weights. The number of connections are incorporated into an objective function so that network parameter optimization is done with respect to network complexity as well as mean pattern error. Experimental results are shown for simple binary mapping problems. Neutral networks, Evolutionary programming, Signal detection.

Subject Categories:

  • Operations Research
  • Computer Systems
  • Cybernetics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE