Exponential lag synchronization for delayed memristive recurrent neural networks

In this paper, by using the parallel-memristors connection corresponding to the capacitors and memristors synaptic connection in usual recurrent neural networks, general delayed memristive recurrent neural networks are proposed. Basing on nonsmooth analysis and control theory, several sufficient conditions concerning global exponential lag synchronization are obtained for the proposed system. In addition, the obtained results complement and extend earlier publications on memristive or conventional neural network dynamical systems with continuous or discontinuous right-hand side. Finally, numerical simulations illustrate the effectiveness of our results.

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