Abstract
By using the fact that the neuron activation functions are sector bounded and nondecreasing, this brief presents a new method, named the delay-slope-dependent method, for stability analysis of a class of recurrent neural networks with time-varying delays. This method includes more information on the slope of neuron activation functions and fewer matrix variables in the constructed Lyapunov-Krasovskii functional. Then some improved delay-dependent stability criteria with less computational burden and conservatism are obtained. Numerical examples are given to illustrate the effectiveness and the benefits of the proposed method.
| Original language | English |
|---|---|
| Article number | 1 |
| Pages (from-to) | 2138-2143 |
| Number of pages | 6 |
| Journal | IEEE transactions on neural networks |
| Volume | 22 |
| Issue number | 12 |
| DOIs | |
| Publication status | Published - 2011 |
Keywords
- Lyapunov functions
- neural networks (computer science)