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Complete synchronization of delayed discrete-time fractional-order competitive neural networks

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  • Chen, Wei-Wei
  • Li, Hong-Li

Abstract

In this paper, we explore complete synchronization for the delayed discrete-time fractional-order competitive neural networks (DDFCNNs). Firstly, several definitions with respect to Caputo fractional-order difference are given. Next, a novel method for proving Caputo fractional difference inequality of 2k-norm function is given, then by making use of the inequality we prove and Hanalay inequality, some sufficient criteria on complete synchronization of DDFCNNs are obtained under the linear feedback controller. In the end, some numerical simulations are given to verify effectiveness of the theoretical consequences.

Suggested Citation

  • Chen, Wei-Wei & Li, Hong-Li, 2024. "Complete synchronization of delayed discrete-time fractional-order competitive neural networks," Applied Mathematics and Computation, Elsevier, vol. 479(C).
    • Handle: RePEc:eee:apmaco:v:479:y:2024:i:c:s0096300324003333
    DOI: 10.1016/j.amc.2024.128872
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    References listed on IDEAS

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    1. Zhang, Xiao-Li & Li, Hong-Li & Kao, Yonggui & Zhang, Long & Jiang, Haijun, 2022. "Global Mittag-Leffler synchronization of discrete-time fractional-order neural networks with time delays," Applied Mathematics and Computation, Elsevier, vol. 433(C).
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