Global stability of periodic solution for bidirectional associative memory neural networks with varying-time delay

This paper investigates the global stability of periodic solution for bidirectional associative memory neural networks by using linear matrix inequality, and presents new sufficient conditions on the existence, uniqueness, global exponential stability and asymptotic stability of periodic solution for bidirectional associative memory neural networks with varying-time delays. In addition, exponential convergence rate is estimated by the equation in the paper. Furthermore, the results in this paper are generalized and the ones reported in the existing literatures are improved. Numerical simulations are given to verify the effectiveness of our main results.