Global stability analysis for delayed complex-valued BAM neural networks

Abstract

This paper investigates the stability criteria for complex-valued bidirectional associative memory (BAM) with time delay. Firstly, based on the Lyapunov function method and mathematical analysis technique, sufficient conditions for the existence of unique equilibrium, and global asymptotic stability of the equilibrium are derived by separating complex-valued neural networks into real and imaginary parts. Secondly, we propose the delay-dependent stability criteria for the complex-valued BAM neural networks. Finally, numerical examples are given to show the effectiveness and merits of the present results.