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<p>In this paper, the synchronization issue of memristive neural networks (MNNs) with uncertain parameters and multiple time-delays is investigated under an adaptive time-controllable control strategy. Based on the designed control strategy and identification rules of uncertain parameter, some criteria for synchronization of MNNs are given. To identify the uncertain switching parameters, a time-controllable adaptive identifier is proposed. Under the construction of the adaptive time-controllable identifier, uncertain parameters are identified within controllable time. Furthermore, a secure communication scheme based on the time-controllable synchronization is put forward. The obtained results indicate that the given scheme is suitable for the MNNs with parameters being not fully obtained. Effectiveness of the theoretical results are verified by two sets of numerical simulations.</p>

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Synchronization for security communication of multi-delay MNNs under uncertain parameters identification: an adaptive time-controllable approach

  • 期刊论文

  • 发表日期：

    2025年3月23日

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  • Lili Zhou,
  • Kaiyue Liu,
  • Fei Tan,
  • Huiying Zhang,
  • Chunlai Li

摘要

In this paper, the synchronization issue of memristive neural networks (MNNs) with uncertain parameters and multiple time-delays is investigated under an adaptive time-controllable control strategy. Based on the designed control strategy and identification rules of uncertain parameter, some criteria for synchronization of MNNs are given. To identify the uncertain switching parameters, a time-controllable adaptive identifier is proposed. Under the construction of the adaptive time-controllable identifier, uncertain parameters are identified within controllable time. Furthermore, a secure communication scheme based on the time-controllable synchronization is put forward. The obtained results indicate that the given scheme is suitable for the MNNs with parameters being not fully obtained. Effectiveness of the theoretical results are verified by two sets of numerical simulations.