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Stabilization of delayed chaotic neural networks by periodically intermittent control. (English) Zbl 1170.93370
Summary: This paper studies the exponential stabilization of Delayed Chaotic Neural Networks (DCNNs) using what is called periodically intermittent control. An exponential stability criterion for the controlled neural networks, together with its simplified version, is established by using the Lyapunov function and Halanay inequality. The feasible region of control parameters is estimated in a rigorous way. Theoretical results and numerical simulations show that the continuous-time DCNN can be stabilized by intermittent feedback control with nonzero duration.

93D21Adaptive or robust stabilization
93C15Control systems governed by ODE
92B20General theory of neural networks (mathematical biology)
Full Text: DOI
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