|Title||Passivity analysis of memristor-based recurrent neural networks with time-varying delays|
|Publication Type||Journal Article|
|Year of Publication||2013|
|Authors||S Wen, Z Zeng, T Huang, and Y Chen|
|Journal||Journal of the Franklin Institute|
|Pagination||2354 - 2370|
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.
|Short Title||Journal of the Franklin Institute|