Exponential Stability of Switched Time-varying Delayed Neural Networks with All Modes Being Unstable

This paper aims to design an appropriate switching law to stabilize the switched neural networks with time-varying delays when all subsystems are unstable. By using the discretized Lyapunov function approach and the extended comparison principle for impulsive systems, the stability of switched delayed neural networks composed full of unstable subsystems is analyzed and a computable sufficient condition is derived in the framework of dwell time. The effectiveness of the proposed results is illustrated by a numerical example.

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