Synchronization for switched neural networks via variable sampled-data control method

This paper investigates the sampled-data synchronization of switched neural networks with time-varying discrete and distributed delays. Considering that the system switching may happen during a sampling interval, the asynchronous phenomenon is taken into account for the sampled-data control process. By utilizing multiple Lyapunov functions and average dwell time property, sufficient conditions are derived to guarantee the exponential stability of the error between the master and slave neural networks. Based on this, sampled-data controller is further designed so that the master and the slave systems are synchronized with a prescribed performance index. Finally, a numerical example is provided to illustrate the validness and effectiveness of the proposed results.