ScienceAsia 24 (1998): 011-020 |doi: 10.2306/scienceasia1513-1874.1998.24.011
FAULT IMMUNIZATION MODEL FOR ARTIFICIAL NEURAL NETWORKS
ABSTRACT: By injecting some chemical substances to a cell, it is able to enhance the ability of the cell to fight against the intruder. This immunization concept in biological cells has been applied to enhance the fault tolerance capability in a perceptron-like neuron. In this paper, we consider only the case where each neuron separates its input vectors into two classes. We mathematically model the cell immunization in terms of weight vector relocation and propose a polynomial time weight relocating algorithm. This algorithm can be generalized to the case where each neuron separating the input vectors into more than two classes.
Department of Mathematics and Computer Science, Chulalongkorn University, Bangkok 10330, Thailand.
Received August 9, 1997