Abstract
This article considers the robust passivity analysis for a class of discrete-time recurrent neural networks (DRNNs) with mixed time-delays and uncertain parameters. The mixed time-delays that consist of both the discrete time-varying and distributed time-delays in a given range are presented, and the uncertain parameters are norm-bounded. The activation functions are assumed to be globally Lipschitz continuous. Based on new bounding technique and appropriate type of Lyapunov functional, a sufficient condition is investigated to guarantee the existence of the desired robust passivity condition for the DRNNs, which can be derived in terms of a family of linear matrix inequality (LMI). Some free-weighting matrices are introduced to reduce the conservatism of the criterion by using the bounding technique. A numerical example is given to illustrate the effectiveness and applicability.
Original language | English |
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Pages (from-to) | 216-232 |
Number of pages | 17 |
Journal | International Journal of Electronics |
Volume | 102 |
Issue number | 2 |
DOIs | |
Publication status | Published - 2015 Feb 1 |
All Science Journal Classification (ASJC) codes
- Electrical and Electronic Engineering