Abstract
This brief paper presents an M-matrix-based algebraic criterion for the global exponential stability of a class of recurrent neural networks with decreasing time-varying delays. The criterion improves some previous criteria based on M-matrix and is easy to be verified with the connection weights of the recurrent neural networks with decreasing time-varying delays. In addition, the rate of exponential convergence can be estimated via a simple computation based on the criterion herein. © 2008 IEEE.
| Original language | English |
|---|---|
| Pages (from-to) | 528-531 |
| Number of pages | 4 |
| Journal | IEEE Transactions on Neural Networks |
| Volume | 19 |
| Issue number | 3 |
| Online published | 31 Mar 2008 |
| DOIs | |
| Publication status | Published - Mar 2008 |
| Externally published | Yes |
Research Keywords
- Global exponential stability
- M-matrix
- Recurrent neural networks
- Time-varying delays
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