Effect of Positive Weight Diagonal Elements on MVN Neural Networks in Associative Memory Design

Abstract

Previously, a lot of applications on recurrent neural networks with multi-valued neuron (MVNRNNs) in asynchronous update mode, used zero diagonal elements as network stability condition. However, according to our recent finding, only positive diagonal elements can guarantee the whole network to be complete convergent. How to adopt positive diagonal element to amend former research results is still unknown. This paper tries to investigate this question by using MVNRNNs with different positive diagonal elements in associative memory (AM) design. Simulation results illustrate that choosing appropriate positive diagonal elements can promote AM's performance compared with AM employing zero diagonal elements.