Global output convergence for delayed recurrent neural networks under impulsive effects
نویسنده
چکیده
In this paper, we investigate convergence of state output for a class of delayed recurrent neural networks with impulsive effects. Based on properties of time-varying inputs and monotonicity of activation function, we establish some sufficient conditions to guarantee output convergence of the networks in which state variable subjected to impulsive displacements at fixed moments of time.
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تاریخ انتشار 2013