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

页码：470 / 477

页数：8

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