Globally exponential synchronization in an array of asymmetric coupled neural networks
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
| Original language | English |
|---|---|
| Pages (from-to) | 444-451 |
| Journal / Publication | Physics Letters, Section A: General, Atomic and Solid State Physics |
| Volume | 369 |
| Issue number | 5-6 |
| Publication status | Published - 1 Oct 2007 |
Link(s)
Abstract
In this Letter, we study the globally exponential synchronization in an array of linearly coupled neural networks with delayed coupling. The coupling configuration matrix is assumed to be asymmetric, which is more coincident with the real-world network. The difficulty arising from the asymmetry of the coupling matrix has been overcame in this work. Some synchronization criteria are given in terms of strict linear matrix inequalities (LMIs), which can be efficiently solved by using interior point algorithm. Some previous synchronization results are generalized. Numerical simulation is also given to verify our theoretical analysis. © 2007 Elsevier B.V. All rights reserved.
Research Area(s)
- Asymmetric coupling, Complex network, Delay, Neural network, Synchronization
Citation Format(s)
Globally exponential synchronization in an array of asymmetric coupled neural networks. / Lu, Jianquan; Ho, Daniel W.C.; Liu, Ming.
In: Physics Letters, Section A: General, Atomic and Solid State Physics, Vol. 369, No. 5-6, 01.10.2007, p. 444-451.
In: Physics Letters, Section A: General, Atomic and Solid State Physics, Vol. 369, No. 5-6, 01.10.2007, p. 444-451.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
