Global asymptotic stability of impulsive fractional-order BAM neural networks with time delay. Issue 2 (February 2017)

• Record Type: Journal Article
• Authors: Wang, Fei; Yang, Yongqing; Xu, Xianyun; Li, Li
• Is Part Of: Neural computing & applications. Volume 28:Issue 2(2017)
• Page Start: 345
• Page End: 352
• Publication Date: 2017-02
• Subjects: Fractional-order -- BAM -- Asymptotic stability -- Impulsive -- Delay; Neural networks (Computer science) -- Periodicals; Neural circuitry -- Periodicals; Artificial intelligence -- Periodicals; Neural Networks (Computer) -- Periodicals; Réseaux neuronaux (Informatique) -- Périodiques; Réseaux nerveux -- Périodiques; Intelligence artificielle -- Périodiques; 006.32
• DOI: 10.1007/s00521-015-2063-0
• Languages: English
• ISSNs: 0941-0643

Abstract

Abstract In this paper, we study the global asymptotic stability of fractional-order BAM neural networks. We take both time delay and impulsive effects into consideration. Based on Lyapunov stability theorem, fractional Barbalat's lemma and Razumikhin-type stability theorem, some stability conditions that are independent of the form of specific delays can be obtained. At last, two illustrative examples are given to show the independence of the obtained two main results and to show the effectiveness of the obtained results.