Synchronization of BAM Cohen-Grossberg FCNNs with mixed time delays
Document Type
Article
Publication Date
4-1-2021
Abstract
This paper deals with the synchronization problem of bidirectional associative memory (BAM) Cohen-Grossberg fuzzy cellular neural networks (CGFCNNs) with discrete time-varying and unbounded distributed delays. Some sufficient conditions are obtained to guarantee the robust synchronization of BAM CGFCNNs with discrete time-varying and unbounded distributed delays subjected to parametric uncertainty by using Lyapunov-Krasovskii (LK) functional and Linear matrix inequality (LMI) approach. Sufficient criteria ensure that the error dynamics of considered system is globally asymptotically stable. Finally, numerical examples with simulations are given to show the efficacy of the derived results.
Keywords
Linear matrix inequality, Fuzzy cellular neural networks, Delay, Synchronization, Cohen-Grossberg neural networks
Divisions
Science
Funders
UCSI University Research Excellence & Innovation Grant (REIG) (REIG-FBM-2020/033),University of Malaya, Frontier Research Grant 2017 (FG037-17AFR)
Publication Title
Iranian journal of Fuzzy Systems
Volume
18
Issue
2
Publisher
Univ Sistan & Baluchestan
Publisher Location
PO BOX 98135-987, ZAHEDAN, 00000, IRAN