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Adaptive robust convergence of neural networks with time-varying delays. (English) Zbl 1154.93420

Summary: This paper is concerned with the adaptive robust convergence for a class of neural networks with time-varying delays. By employing the Lyapunov method and a novel lemma, some delay-independent conditions are derived to guarantee the state variables of the discussed time-varying robust system to converge, globally, uniformly, exponentially to a ball in the state space with a pre-specified convergence rate. Here, the existence and uniqueness of the equilibrium point needs not to be considered. Finally, an illustrated example is given to show the effectiveness and usefulness of the results.

MSC:

93D20 Asymptotic stability in control theory
92B20 Neural networks for/in biological studies, artificial life and related topics
93D21 Adaptive or robust stabilization
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References:

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