Stability Criterion of Discrete Hopfield Neural Networks with Weighted Function Matrix and one-Delay

Abstract

In this paper, discrete Hopfield neural networks with weight function matrix(WFM) and delay(DHNNWFMD) are presented. And we obtain an important result that if the WFM is a symmetric function matrix(SFM) and delayed function matrix(DFM) is a diagonally dominant function matrix(DDFM), DHNNWFMD will converge to a state in serial mode and if the WFM is a SFM and non-negative definite function matrix(NFM) and DFM is a DDFM, DHNNWFMD will converge to a state in parallel mode. It provides some theory basis for the application of DHNNWFMD.