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Global exponential stability of fuzzy cellular neural networks with delays and reaction-diffusion terms. (English) Zbl 1146.35315

Summary: 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.

MSC:

35B35 Stability in context of PDEs
35K57 Reaction-diffusion equations
35K50 Systems of parabolic equations, boundary value problems (MSC2000)
35R10 Partial functional-differential equations
92B20 Neural networks for/in biological studies, artificial life and related topics
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