Fuzzy control of backpropagation

2 January 2003

conference paper
Published by Institute of Electrical and Electronics Engineers (IEEE)

p. 967-972
https://doi.org/10.1109/fuzzy.1992.258787

Abstract

The authors propose a fuzzy logic controlled implementation of the backpropagation training algorithm for layered perceptrons. The heuristics for adjusting the value of the learning rate eta are incorporated into a simple fuzzy control system. This provides automatic tuning of the learning rate parameter depending on the shape of the error surface. The application of this straightforward procedure was shown to be able to dramatically improve training time in some problems.<>

Keywords

FUZZY CONTROL
FUZZY LOGIC
AUTOMATIC CONTROL
BACKPROPAGATION ALGORITHMS
TIME OF ARRIVAL ESTIMATION
SHAPE

This publication has 1 reference indexed in Scilit:

Increased rates of convergence through learning rate adaptation
Neural Networks, 1988

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