Asymptotic stability of bidirectional associative memory neural networks with time-varying delays via delta operator approach

This paper is interested in the problem of asymptotic stability analysis of Bidirectional Associative Memory (BAM) neural networks with time-varying delays via delta operator approach. The delays are assumed to exist in the nonlinear synaptic connection between different neural fields. Based on the Lyapunov–Krasovskii functional in delta domain, a new delay-dependent criterion for analyzing the asymptotic stability of BAM neural networks is obtained. Some previous results of continuous and discrete BAM systems are unified into the delta operator system framework due to the favorable numerical properties and the quasi-continuous performance of delta operator approach at high sampling rates. Since the sampling period is an explicit parameter in the results, it can be regulated to analyze the stability of systems. Numerical examples are presented to demonstrate the effectiveness of the developed theoretical results.