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| DOI： |
| Received:June 06, 2005Revised:March 03, 2006 |
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| Global exponential stability analysis of cellular neural networks with multiple time delays |
| Zhanshan WANG;Huaguang ZHANG |
| (School of Information Science and Engineering,
Northeastern University, Shenyang Liaoning 110004, China;Department of Information Engineering, Shenyang Ligong
University, Shenyang Liaoning 110168, China) |
| Abstract: |
| Global exponential stability problems are investigated for cellular
neural networks (CNN) with multiple time-varying delays. Several new
criteria in linear matrix inequality form or in algebraic form are
presented to ascertain the uniqueness and global exponential
stability of the equilibrium point for CNN with multiple
time-varying delays and with constant time delays. The proposed
method has the advantage of considering the difference of neuronal
excitatory and inhibitory effects, which is also computationally
efficient as it can be solved numerically using the recently
developed interior-point algorithm or be checked using simple
algebraic calculation. In addition, the proposed results generalize
and improve upon some previous works. Two numerical examples are
used to show the effectiveness of the obtained results. |
| Key words: Cellular neural networks Multiple time-varying delays Exponential |
