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This note presents a generalized sufficient condition which guarantees stability of analog neural networks with time delays. The condition is derived using a Lyapunov functional and the stability criterion is stated as: the equilibrium of analog neural networks with delays is globally asymptotically stable if the product of the norm of connection matrix and the maximum neuronal gain is less than one.
Cao et al. (Mon,) studied this question.
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