Global exponential stability of fuzzy cellular neural networks with delays and reaction–diffusion terms

Jian Wang and Jun Guo Lu

Chaos, Solitons & Fractals, 2008, vol. 38, issue 3, 878-885

Abstract: In this paper, we study the global exponential stability of fuzzy cellular neural networks with delays and reaction–diffusion terms. By constructing a suitable Lyapunov functional and utilizing some inequality techniques, we obtain a sufficient condition for the uniqueness and global exponential stability of the equilibrium solution for a class of fuzzy cellular neural networks with delays and reaction–diffusion terms. The result imposes constraint conditions on the network parameters independently of the delay parameter. The result is also easy to check and plays an important role in the design and application of globally exponentially stable fuzzy neural circuits.

Date: 2008
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:38:y:2008:i:3:p:878-885

DOI: 10.1016/j.chaos.2007.01.032

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