Stability in cellular neural networks with a piecewise constant argument. (English) Zbl 1191.68484
Summary: By using the concept of differential equations with piecewise constant arguments of generalized type, a model of cellular neural networks is developed. The Lyapunov-Razumikhin technique is applied to find sufficient conditions for the uniform asymptotic stability of equilibria. Global exponential stability is investigated by means of Lyapunov functions. An example with numerical simulations is worked out to illustrate the results.
MSC:
| 68T05 | Learning and adaptive systems in artificial intelligence |
Keywords:
cellular neural networks; differential equations with a piecewise constant argument of generalized type; Lyapunov-Razumikhin technique; method of Lyapunov functions; linear matrix inequalityReferences:
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