This paper pays close attention to the global polynomial dissipativity (GPD) for proportional delayed BAM neural networks (PDBAMNNs). The global exponential dissipativity (GED) and the global dissipativity (GD) are also talked about. Under the help of novel Lyapunov functionals and a generalized Halanay inequality, a set of dissipative criteria for such systems are led out, together with the global polynomial attracting set (GPAS) and the global attracting set (GAS). Further, the relationship among GPD, GED and GD is unveiled. Finally, a proposed theoretical condition is validated through a simulation experiment.

中文翻译：

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比例延迟 BAM 神经网络的多项式耗散性

本文密切关注比例延迟 BAM 神经网络 (PDBAMNNs) 的全局多项式耗散性 (GPD)。还讨论了全局指数耗散（GED）和全局耗散（GD）。在新的Lyapunov泛函和广义Halanay不等式的帮助下，导出了此类系统的一组耗散准则，以及全局多项式吸引集（GPAS）和全局吸引集（GAS）。此外，揭示了 GPD、GED 和 GD 之间的关系。最后，通过仿真实验验证了所提出的理论条件。