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Abstract-It is shown that if the neuronal gains are small compared with the synaptic connection weights, then a bidirectional associative memory network with axonal signal transmission delays converges to the equilibria associated with exogenous inputs to the network; both discrete and continuously distributed delays are considered; the asymptotic stability is global in the state space of neuronal activations and also is independent of the delays.

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A well known bidirectional associative memory (BAM) model is generalized with the introduction of discrete time delays in the leakage (or forgetting) terms. By using a model transformation, the system is converted to one of a neutral delay system. Two sets of delay dependent sufficient conditions are derived for the existence of a unique equilibrium as well as its asymptotic and exponential stability. The methods of degenerate Lyapunov-Kravsovskii functionals and inequalities together with some properties of M-matrices are used in the derivation of sufficient conditions. In the absence of leakage delays, the sufficient conditions lead to some known sufficient conditions.