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State estimation for complex-valued memristive neural networks with time-varying delays. (English) Zbl 1445.92007

Summary: This paper focuses on the state estimation problem for complex-valued memristive neural networks with time-varying delays. By utilizing Lyapunov stability theory and some matrix inequality techniques, based on a novel Lyapunov functional, a sufficient delay-dependent condition which guarantees that the error-state system is global asymptotically stable is firstly derived for the addressed system, and a suitable state estimator is also designed. Finally, an example is given to illustrate the present method.

MSC:

92B20 Neural networks for/in biological studies, artificial life and related topics
93E15 Stochastic stability in control theory
34K60 Qualitative investigation and simulation of models involving functional-differential equations
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