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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:
35B35Stability of solutions of PDE
35K57Reaction-diffusion equations
35K50Systems of parabolic equations, boundary value problems (MSC2000)
35R10Partial functional-differential equations
92B20General theory of neural networks (mathematical biology)
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