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<p>This paper investigates the fixed-time bipartite synchronization of coupled competitive neural networks incorporating impulsive effects. Firstly, by employing the comparison principle, a new lemma that addresses the fixed-time stability of impulsive systems subjected to destabilizing impulses is derived. Secondly, in contrast to traditional controllers that utilize two power exponential terms, a novel and simplified controller is proposed. Subsequently, based on the established fixed-time stability, some sufficient conditions for achieving fixed-time bipartite synchronization of aforementioned networks are presented under both stabilizing and destabilizing impulsive influences. Finally, theoretical results are verified by numerical examples.</p>

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Novel fixed-time control for bipartite synchronization of impulsive competitive neural networks

  • 期刊论文

  • 发表日期：

    2026年4月22日

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  • Shimiao Tang,
  • Jun-Guo Lu,
  • Jiarong Li,
  • Juan Yu,
  • Jinling Wang,
  • Cheng Hu

摘要

This paper investigates the fixed-time bipartite synchronization of coupled competitive neural networks incorporating impulsive effects. Firstly, by employing the comparison principle, a new lemma that addresses the fixed-time stability of impulsive systems subjected to destabilizing impulses is derived. Secondly, in contrast to traditional controllers that utilize two power exponential terms, a novel and simplified controller is proposed. Subsequently, based on the established fixed-time stability, some sufficient conditions for achieving fixed-time bipartite synchronization of aforementioned networks are presented under both stabilizing and destabilizing impulsive influences. Finally, theoretical results are verified by numerical examples.