Finite-Time Stability Analysis of Fractional Order Delayed Memristive Neural Networks

被引:0
作者
Li, Ruoxia [1 ]
Cao, Jinde [1 ]
Wan, Ying [1 ]
机构
[1] Southeast Univ, Dept Math, Nanjing, Jiangsu, Peoples R China
来源
2016 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN) | 2016年
基金
中国国家自然科学基金;
关键词
STABILIZATION; SYNCHRONIZATION;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, the finite-time stability analysis of non-autonomous and autonomous fractional order memristive systems with a pure time delay and commensurate order between 0 and 1 is proposed. First, two appropriate concepts of the finite-time stability for the mentioned system with and without external input are introduced. Then, a sufficient condition for finite-time stability of the underlying system is derived in the frame of some useful inequalities and appropriate properties of the norm. In particular, the results are presented in form of algebraic inequality, which turn out to be more efficient from the computational point of view. Finally, simulation results are given to testify the merits of the derived conditions.
引用
收藏
页码:2329 / 2335
页数:7
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