The Optimization of Synchronization Control Parameters for Fractional-Order Delayed Memristive Neural Networks Using SIWPSO

The paper mainly deals with the optimization of synchronization for fractional-order memristive neural networks (FOMNNs) with a time delay. Based on synchronization conditions, an optimization model for control parameters is designed and computed. It’s significative to design an appropriate controller which can synchronize the drive FOMNNs and response FOMNNs. Based on the proposed controller, some synchronization conditions of FOMNNS can be obtained with the help of the linear matrix inequality, along with fractional-order Lyapunov methods and matrix analysis. The optimal model of control parameters includes a target function and some constraints. The target function is the minimal sum of control energy and integral square error index. The constraint conditions choose the sufficient conditions for synchronization of FOMNNs. The optimization model is difficult to compute but can be solved by means of the stochastic inertia weight particle swarm optimization algorithm. A simulation is provided to verify the validity of the proposed theoretical results.