Associative Memory Design Based on Region Attracivity Neural Networks and Reinforcement Learning

This paper introduces a novel associative memory design method based on neural networks which are region attractivity. For the given memory patterns, we can take any value for networks connection weights and then compute network external inputs based on reinforcement learning algoritms. One numerical experiment is given for validify our method.