Finite-Time Boundedness of QVMNNs with Time-Varying Delays

被引:0
|
作者
Wei, Ruoyu [1 ]
Cao, Jinde [1 ]
Li, Cliengsheng [1 ]
机构
[1] Southeast Univ, Sch Math, Nanjing, Peoples R China
来源
2020 12TH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTATIONAL INTELLIGENCE (ICACI) | 2020年
关键词
memristor; finite-time boundedness; quaternion; time delays; MEMRISTIVE NEURAL-NETWORKS; SYNCHRONIZATION; STABILITY;
D O I
10.1109/icaci49185.2020.9177741
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
With the introduction of quaternion number and memristor connection weights, the quaternion-valued memristive neural networks (QVMNNs) is then constructed. Based on the differential theory and quaternion feature, the finite-time boundedness problem of QVMNNs is considered in both quaternion area and complex area. Theorems for guaranteeing finite-time boundedness of QVMNNs are achieved by appropriately choosing the Lyapunov functional and applying linear matrix inequality (LMI). Finally, a simulation example is presented to demonstrate our results.
引用
收藏
页码:470 / 477
页数:8
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