摘要
本文针对一类带有混合时变时滞(离散和分布时滞)的区间递归神经网络进行了全局鲁棒稳定性研究.与之前的处理方法不同,在本文中通过使用一种新型的增广Lyapunov-Krasovskii泛函,从而得到了一类新颖的关于区间递归神经网络的时滞依赖全局鲁棒稳定性判据.在新的增广泛函中,由于首次使用了带有激活函数的积分项,系统状态和激活函数之间的关系将被更好地表示出来.因此,本文提出的判据具有更小的保守性.同时,在本文提出的判据中,放松了时变时滞变化率必须小于1的限制.仿真结果进一步证明了本文结果的有效性.
Global robust stability of interval recurrent neural networks with mixed time-varying delays （discrete timevarying delay and distributed time-varying delay） is investigated. Being different from existing reports, the novel delaydependent robust stability criteria for interval recurrent neural networks with mixed time-varying delays employ a new augmented Lyapunov-Krasovskii functional. In the new augmented functional, we introduce an integral term to the activation function, which gives a preferable representation of the relation between states of the system and the activation function. Because of the new functional, the criteria proposed in this paper are less conservative than the currently existing ones. Moreover, the employment of the Jensen＇s inequality in proving the criteria relaxes the restriction on the time derivative of the time-varying delay in the proposed criteria. The simulation is provided to verify the effectiveness of the proposed results.
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
2009年第12期1325-1330,共6页
Control Theory & Applications
基金
国家自然科学基金资助项目(60774048
60728307)
高校博士点基金资助项目(20070145015)
高等学校学科创新引智计划资助项目(B08015)
