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

  • Qi Chang
  • Aihua Hu
  • Yongqing YangEmail author
  • Li Li
Article
  • 10 Downloads

Abstract

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.

Keywords

Fractional-order Memristive neural networks Optimal control SIWPSO algorithm 

Notes

Compliance with Ethical Standards

Conflict of interest

The authors declare that there is no conflict of interest in preparing this article.

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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Science, Wuxi Engineering Research Center for BiocomputingJiangnan UniversityWuxiPeople’s Republic of China
  2. 2.School of IoT EngineeringJiangnan UniversityWuxiPeople’s Republic of China

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