A new sufficient condition for global robust stability of bidirectional associative memory neural networks with multiple time delays

This paper presents an easily verifiable delay independent sufficient condition for the global robust asymptotic stability of the equilibrium point for bidirectional associative memory (BAM) neural networks with time delays by employing a class of Lyapunov functionals. The obtained results are applicable to all bounded continuous non-monotonic neuron activation functions. Some numerical examples are given to compare our results with the previous robust stability results derived in the literature.