Fixed-time synchronization of complex-valued memristive competitive neural networks based on two novel fixed-time stability theorems

被引：0
作者：
Chenguang Xu
Minghui Jiang
Junhao Hu
机构：
[1] China Three Gorges University,Three Gorges Mathematical Research Center
[2] China Three Gorges University,Institute of Nonlinear Complex Systems
[3] South Central University for Nationalities,College of Mathematics and Statistics
来源：
Neural Computing and Applications | 2023年 / 35卷
关键词：
Complex number field; Memristive competitive neural networks; Fixed-time synchronization; Non-separation approach;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The fixed-time synchronization (FTS) of complex-valued memristive competitive neural networks (CVMCNNs) with mixed delays is the main topic of this paper. Firstly, two new fixed-time (FT) stability criteria are obtained. In the FT stability criterion, the exponent is usually positive, but the exponent can be less than zero and varies with the error state in this paper. Then, based on two new stability theorems, the FTS of CVMCNNs is studied in the sense of 1-norm and 2-norm, respectively, without dividing the complex-valued state variables into the real part (RP) and the imaginary part (IP). Finally, two numerical simulation examples are given to further demonstrate the validity and superiority of our results.
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页码：22605 / 22620
页数：15
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