An analysis of global exponential stability of bidirectional associative memory neural networks with constant time delays

This paper presents a new sufficient condition for the existence, uniqueness and global exponential stability of the equilibrium point for bidirectional associative memory (BAM) neural networks with constant delays. The results are also compared with the previous results in the literature, implying that the results obtained in this paper provide one more set of criteria for determining the global exponential stability of BAM neural networks with constant delays.