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This paper presents a sufficient condition for the global asymptotic stability of the equilibrium point for bidirectional associative memory (BAM) neural networks with variable coefficients. The results impose constraint conditions on the network parameters of neural system independently of variable coefficients, and they are applicable to all bounded continuous non-monotonic neuron activation functions.
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