title: Boundedness, Mittag-Leffler stability and asymptotical ω-periodicity of fractional-order fuzzy neural networks.
abstract: We show that the ω-periodic fractional-order fuzzy neural networks cannot generate non-constant ω-periodic signals. In addition, several sufficient conditions are obtained to ascertain the boundedness and global Mittag-Leffler stability of fractional-order fuzzy neural networks. Furthermore, S-asymptotical ω-periodicity and global asymptotical ω-periodicity of fractional-order fuzzy neural networks is also characterized. The obtained criteria improve and extend the existing related results. To illustrate and compare the theoretical criteria, some numerical examples with simulation results are discussed in detail.
authors.affiliation: College of Mathematics and Statistics, Hubei Normal University, Huangshi 435002, China; School of Automation, Huazhong University of Science and Technology, Wuhan 430074, China; Institute for Information and System Science, Xi'an Jiaotong University, Xi'an 710049, China. Electronic address: hbnuwu@yeah.net.
authors.forename: Ailong
authors.initials: A
authors.lastname: Wu
authors.affiliation: School of Automation, Huazhong University of Science and Technology, Wuhan 430074, China. Electronic address: hustzgzeng@gmail.com.
authors.forename: Zhigang
authors.initials: Z
authors.lastname: Zeng
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D017143:Fuzzy Logic; D016571:Neural Networks, Computer; D010507:Periodicity
keywords: -asymptotical -periodicity; Boundedness; Fractional-order systems; Fuzzy neural networks; Mittag-Leffler stability