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<p>Research has been conducted on the global exponential synchronization (GES) of proportional delay BAM neural networks (PDBAMNNs) with uncertain parameters. A solution estimation method is employed to derive sufficient algebraic conditions for GES under norm-bounded parameter uncertainties. The effectiveness is validated numerically, and an application to a chaos-based image encryption scheme is presented.</p>

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Global exponential synchronization of BAM neural networks with proportional delays and uncertain parameters for image encryption

  • 期刊论文

  • 发表日期：

    2026年6月16日

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  • Wenyue Zheng,
  • Liqun Zhou

摘要

Research has been conducted on the global exponential synchronization (GES) of proportional delay BAM neural networks (PDBAMNNs) with uncertain parameters. A solution estimation method is employed to derive sufficient algebraic conditions for GES under norm-bounded parameter uncertainties. The effectiveness is validated numerically, and an application to a chaos-based image encryption scheme is presented.