title: Passivity analysis for memristor-based recurrent neural networks with discrete and distributed delays.
abstract: In this paper, based on the knowledge of memristor and recurrent neural networks (RNNs), the model of the memristor-based RNNs with discrete and distributed delays is established. By constructing proper Lyapunov functionals and using inequality technique, several sufficient conditions are given to ensure the passivity of the memristor-based RNNs with discrete and distributed delays in the sense of Filippov solutions. The passivity conditions here are presented in terms of linear matrix inequalities, which can be easily solved by using Matlab Tools. In addition, the results of this paper complement and extend the earlier publications. Finally, numerical simulations are employed to illustrate the effectiveness of the obtained results.
authors.affiliation: College of Mathematics and Statistics, South-Central University for Nationalities, Wuhan 430074, China. zgdhbnu@163.com
authors.lastname: Guodong Zhang
authors.lastname: Yi Shen
authors.lastname: Quan Yin
authors.lastname: Junwei Sun
mesh_terms: D000465:Algorithms; D008962:Models, Theoretical; D016571:Neural Networks, Computer