具有遗忘时滞的静态神经网络的H_∞状态估计

H_∞ state estimation of static neural networks with leakage delay

本文研究了具有遗忘时滞的静态神经网络的H∞状态估计问题.首先降低了时变时滞可微的条件,然后通过构造合适的Lyapunov-Krasovskii泛函,设计保H∞性能的状态估计器,使得误差系统实现全局渐近稳定.最后,借助Matlab中线性矩阵不等式工具箱进行数值仿真,验证了结论的有效性.

This paper focuses on the study of H∞ state estimation of static neural networks having leakage delay.With the skills to construct Lyapunov-Krasovskii functionals,a state estimator is designed for the estimation of H∞ performance,and the results are derived without applying differentiability on time-varying delays.Finally,a numerical example is provided to demonstrate the effectiveness and advantages of the obtained results.