Global point dissipativity of neural networks with mixed time-varying delays
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
| Original language | English |
|---|---|
| Article number | 13105 |
| Journal / Publication | Chaos |
| Volume | 16 |
| Issue number | 1 |
| Publication status | Published - 2006 |
Link(s)
Abstract
By employing the Lyapunov method and some inequality techniques, the global point dissipativity is studied for neural networks with both discrete time-varying delays and distributed time-varying delays. Simple sufficient conditions are given for checking the global point dissipativity of neural networks with mixed time-varying delays. The proposed linear matrix inequality approach is computationally efficient as it can be solved numerically using standard commercial software. Illustrated examples are given to show the usefulness of the results in comparison with some existing results. © 2006 American Institute of Physics.
Citation Format(s)
Global point dissipativity of neural networks with mixed time-varying delays. / Cao, Jinde; Yuan, Kun; Ho, Daniel W.C. et al.
In: Chaos, Vol. 16, No. 1, 13105, 2006.
In: Chaos, Vol. 16, No. 1, 13105, 2006.
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
