Paper Info
Title
Novel Inequalities to Global Mittag–Leffler Synchronization and Stability Analysis of Fractional-Order Quaternion-Valued Neural Networks
Abstract
This article is concerned with the problem of the global Mittag-Leffler synchronization and stability for fractional-order quaternion-valued neural networks (FOQVNNs). The systems of FOQVNNs, which contain either general activation functions or linear threshold ones, are successfully established. Meanwhile, two distinct methods, such as separation and nonseparation, have been employed to solve the transformation of the studied systems of FOQVNNs, which dissatisfy the commutativity of quaternion multiplication. Moreover, two novel inequalities are deduced based on the general parameters. Compared with the existing inequalities, the new inequalities have their unique superiorities because they can make full use of the additional parameters. Due to the Lyapunov theory, two novel Lyapunov-Krasovskii functionals (LKFs) can be easily constructed. The novelty of LKFs comes from a wider range of parameters, which can be involved in the construction of LKFs. Furthermore, mainly based on the new inequalities and LKFs, more multiple and more flexible criteria are efficiently obtained for the discussed problem. Finally, four numerical examples are given to demonstrate the related effectiveness and availability of the derived criteria.
Year
DOI
Venue
2021
10.1109/TNNLS.2020.3015952
IEEE Transactions on Neural Networks and Learning Systems
Keywords
DocType
Volume
Fractional-order neural networks (FNNs),quaternion-valued neural networks (QVNNs),stability,synchronization
Journal
32
Issue
ISSN
Citations 
8
2162-237X
1
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Jianying Xiao1394.21
Jinde Cao211399733.03
Jun Cheng353643.22
Shiping Wen4123172.34
Ruimei Zhang51158.14
Shouming Zhong61470121.41