Convergence of back-propagation in neural networks using a log-likelihood cost function

8 November 1990

journal article
Published by Institution of Engineering and Technology (IET) in Electronics Letters

Vol. 26 (23) , 1964-1965
https://doi.org/10.1049/el:19901270

Abstract

A variation of the back-propagation algorithm is described, using a log-likelihood cost function. Appropriate choices of learning parameters are discussed. An example is given where the range of initial weights leading to proper convergence is increased, and the number of iterations required is significantly reduced.

Keywords

INITIAL WEIGHTS
ITERATIONS REDUCTION
LOG-LIKELIHOOD COST FUNCTION
CONVERGENCE OF BACK-PROPAGATION
BACK-PROPAGATION ALGORITHM
NEURAL NETWORKS

This publication has 0 references indexed in Scilit: