期刊
NEURAL COMPUTING & APPLICATIONS
卷 32, 期 11, 页码 7321-7332出版社
SPRINGER LONDON LTD
DOI: 10.1007/s00521-019-04227-4
关键词
Neural networks; Mixed time-varying delays; Halanay inequality; Matrix measure; Modified function projective synchronization
This paper is concerned with the modified function projective synchronization of Cohen-Grossberg neural networks systems with parameter mismatch and mixed time-varying delays. Due to the existence of parameter mismatch between the drive and slave systems, complete modified function projective synchronization is not possible to achieve. So a new concept, viz., weak modified function projective synchronization, is discussed up to a small error bound. Several generic criteria are derived to show weak modified function projective synchronization between the systems. The estimation of error bound is done using matrix measure and Halanay inequality. Simulation results are proposed graphically for different particular cases to show the synchronization between parameter-mismatched systems, which validate the effectiveness of our proposed theoretical results.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据