Asymptotic stability of delayed fractional-order fuzzy neural networks with impulse effects. Issue 15 (October 2018)

• Record Type: Journal Article
• Authors: Chen, Jiyang; Li, Chuandong; Yang, Xujun
• Is Part Of: Journal of the Franklin Institute. Volume 355:Issue 15(2018)
• Page Start: 7595
• Page End: 7608
• Publication Date: 2018-10
• Subjects: Science -- Periodicals; Technology -- Periodicals; Patents -- United States -- Periodicals; 505
• DOI: 10.1016/j.jfranklin.2018.07.039
• Languages: English
• ISSNs: 0016-0032

Abstract

Abstract: In this paper, we investigate the asymptotic stability of fractional-order fuzzy neural networks with fixed-time impulse and time delay. According to the fractional Barbalat's lemma, Riemann–Liouville operator and Lyapunov stability theorem, some sufficient conditions are obtained to ensure the asymptotic stability of the fractional-order fuzzy neural networks. Two numerical examples are also given to illustrate the feasibility and effectiveness of the obtained results.