Passivity Analysis of Stochastic Memristor-Based Complex-Valued Recurrent Neural Networks with Mixed Time-Varying Delays

被引：0
|
作者：
Jian Guo
Zhendong Meng
Zhengrong Xiang
机构：
[1] Nanjing University of Science and Technology,School of Automation
来源：
Neural Processing Letters | 2018年 / 47卷
关键词：
Passivity; Memristor; Neural networks; Switched systems; Time-varying delays;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper, the passivity analysis of stochastic memristor-based complex-valued recurrent neural networks (SMCVRNNs) with discrete and distributed time-varying delays is conducted. We adopt a switched system to describe the SMCVRNN with mixed time-varying delays. Appropriate Lyapunov–Krasovski functionals are constructed to analyze the passivity of SMCVRNNs under consideration. Two sufficient conditions are presented in terms of linear matrix inequalities which assure that the SMCVRNNs are stochastically passive. The effectiveness of the obtained results is demonstrated by two examples.
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页码：1097 / 1113
页数：16
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