节点文献
一类具有加性时滞的神经网络系统的混杂控制
Hybrid Control for Neural Networks with Additive Time Varying Delays
【摘要】 本文研究了具有加性时变时滞的神经网络系统混杂控制.基于混合触发机制构建了神经网络滤波误差系统模型,有效避免了芝诺现象通过求解一类矩阵不等式,给出了使得被控系统具有耗散滤波性能的充分条件,进而得到了基于混合触发机制的H_∞滤波、无源滤波、(Q,S,R)-耗散滤波和L2-L_∞滤波.最后,通过数值例子验证了方法的有效性.
【Abstract】 This paper is concerned with the hybrid control for neural networks with additive time varying delays.The neural network filtering error system is modeled based on the hybrid triggered scheme,and the Zeno phenomenon can be effectively avoided.Some sufficient conditions are derived by solving the matrix inequalities for the existence of reliable dissipative filtering performance.Moreover,H∞ filters,passive filters,(Q,S,R)-dissipative filters and L2-L∞ filters are also obtained based on the hybrid trigger mechanism.Finally,some numerical examples are used to illustrate the effectiveness of the proposed methods.
【Key words】 Neural Network; Hybrid Control; Additive Time Varying Delays; Dissipative Theory;
- 【文献出处】 生物数学学报 ,Journal of Biomathematics , 编辑部邮箱 ,2020年01期
- 【分类号】TP183;O231
- 【下载频次】7