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Global Asymptotic Stability of Periodic Solutions for Neutral-Type Delayed BAM Neural Networks by Combining an Abstract Theorem of k-Set Contractive Operator with LMI Method

机译:用LMI方法将k集体收缩算子的抽象定理组合通过与LMI法相结合中立型延迟BAM神经网络的全局渐近稳定性

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The paper considers the existence and global asymptotic stability of periodic solutions for a class of neutral-type BAM neural networks with time delays. By combining an abstract theorem of k-set contractive operator with LMI method as well as inequality techniques, a sufficient condition to guarantee the existence of periodic solutions for the above neutral-type BAM neural networks with time delays is established. Then by combining LMI method with inequality techniques, a sufficient condition of the global asymptotic stability of periodic solutions for the above neutral-type BAM neural networks is obtained. Our method and results on periodic solutions for the above neural networks are new and complementary to the existing papers.
机译:本文考虑了一类中性型BAM神经网络的定期解决方案的存在和全局渐近稳定性。通过将K-SET收缩算子的抽象定理与LMI方法以及不等式技术相结合,建立了足够的条件,以保证具有时间延迟的上述中性型BAM神经网络的周期性解决方案的存在。然后,通过将LMI方法与不等式技术组合,获得了上述中性型BAM神经网络的全局渐近稳定性的充分条件。我们的方法和结果对上述神经网络的周期性解决方案是新的和互补的现有论文。

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