Abstract
A global stability analysis of a particular class of recurrent neural networks with time-varying delay is performed. Both Lipschitz continuous and monotone non-decreasing activation functions are considered. Globally asymptotically delay-dependent stability criteria are derived in the form of linear matrix inequalities through the use of Leibniz-Newton formula and relaxation matrices. Finally, two numerical examples are given to illustrate the effectiveness of the given criterion.
Original language | English |
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Pages (from-to) | 736-742 |
Number of pages | 7 |
Journal | IET Control Theory and Applications |
Volume | 2 |
Issue number | 8 |
DOIs | |
Publication status | Published - 2008 Jul 24 |
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Human-Computer Interaction
- Computer Science Applications
- Control and Optimization
- Electrical and Electronic Engineering