Passivity analysis of memristor-based recurrent neural networks with time-varying delays
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This paper investigates the delay-dependent exponential passivity problem of the memristor-based recurrent neural networks (RNNs). Based on the knowledge of memristor and recurrent neural network, the model of the memristor-based RNNs is established. Taking into account of the information of the neuron activation functions and the involved time-varying delays, several improved results with less computational burden and conservatism have been obtained in the sense of Filippov solutions. A numerical example is presented to show the effectiveness of the obtained results. © 2013 The Franklin Institute.
author list (cited authors)
Wen, S., Zeng, Z., Huang, T., & Chen, Y.