The Dissipativity And Finite-time Synchronization Analysis Of Memristive Neural Network Systems

In this paper,the dissipayivity and finite-time synchronization of memristive neural network systems are studied by using linear matrix inequalities(LMIs),differential inclusion,some integral inequality techniques and drive-response concept.The first part,the dissipativity of a neutral-type memristive neural networks(MNNs)with leakage delays,additive time delays and distributed delays.By applying a suitable Lyapunov-Krasovskii functional(LKF),some integral inequality techniques,LMIs and free-weighting matrix method,some new sufficient conditions are derived to ensure the dissipativity of the aforementioned MNNs.Furthermore,the global exponential attractive sets and positive invariant sets are also derived.Finally,a numerical simulation is given to illustrate the effectiveness of our results.The second part,the finite-time synchronization of a kind of memristive neural network systems by using different controllers is investigated.First,a mathematical model of inertial MNNs with time-varying delays is given,then the original system is transformed into a first-order differential equation by selecting a suitable variable substitution.Second,by two different controllers,it can be guaranteed to achieve that finite-time and global fixed-time synchronization between response system and drive system based on finite time stability and fixed time theory.Finally,two numerical simulations are given to illustrate the effectiveness of the main results.