Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6865733 | Neurocomputing | 2015 | 25 Pages |
Abstract
In this paper, the passivity problem of memristor-based recurrent neural networks (MRNNs) with mixed time-varying delays is investigated. We adopt a switched system to describe the memristor-based recurrent neural network with mixed time-varying delays. By constructing appropriate Lyapunov-Krasovskii functionals, two sufficient conditions for passivity and exponential passivity of MRNNs are established in terms of linear matrix inequalities (LMIs), respectively. An example is given to demonstrate the effectiveness of the obtained results.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Zhendong Meng, Zhengrong Xiang,