Global Exponential Stability and Synchronization of Memristive Neural Networks Including both Time-Varying and Continuously Distributed Delays
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2017 IEEE. This article investigates the stability and synchronization problems for a kind of general memristive neural networks (MNNs) including both time-varying and continuously distributed delays. With the help of homeomorphism theory, delay differential-integral inequality and appropriate Lyapunov-Kravsovskii functional approach, several new sufficient criteria concerning global exponential stability and synchronization for MNNs are obtained under the sense of Filippov solution. The obtained criteria make some extensions and improvements of the existing results and are easier to be validated in the numerical simulation.
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2017 International Workshop on Complex Systems and Networks (IWCSN)