全局渐近鲁棒稳定性 global asymptotic robust stability
In this paper, we will investigate the global robust stability of static neural networks with reaction-diffusion terms and absolutely exponential stability of local field neural networks.
对此,本文讨论了反应扩散静态神经网络的全局鲁棒稳定性和反应扩散局域神经网络的绝对指数稳定性。
参考来源 - 时滞反应扩散神经网络的稳定性分析·2,447,543篇论文数据，部分数据来源于NoteExpress
仿真结果表明，该控制器对系统参数的不确定性和有界干扰具有一定的鲁棒性，并能保证闭环系统全局稳定。
The simulation result shows that the controller is robust to some nonlinear uncertainties and bounded disturbance, and it can guarantee the global boundness of all closed-loop signals.
计算机仿真表明，遗传算法可以方便地得到全局最优解，故控制器可以快速稳定地跟踪预定航向，且系统具有较好的鲁棒性。
Computer simulation proves this algorithms can easily get the optimum solution, so the controller can trace the course quickly and smoothly, and the system has good robustness.
讨论了混合时滞区间神经网络的全局鲁棒指数稳定性。
The global robust exponential stability is investigated for interval neural networks with mixed delay.
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