Stability analysis and robust synchronization of fractional‐order competitive neural networks with different time scales and impulsive perturbations. (22nd October 2019)

• Record Type: Journal Article
• Authors: Pratap, Anbalagan; Raja, Ramachandran; Agarwal, Ravi P; Cao, Jinde
• Is Part Of: International journal of adaptive control and signal processing. Volume 33:Number 11(2019)
• Page Start: 1635
• Page End: 1660
• Publication Date: 2019-10-22
• Subjects: fractional‐order competitive neural networks -- impulses -- Mittag‐Leffler function -- robust synchronization -- stability -- time‐delay; Adaptive control systems -- Periodicals; Adaptive signal processing -- Periodicals; 629.836
• DOI: 10.1002/acs.3056
• Languages: English
• ISSNs: 0890-6327

Abstract

Summary: This article mainly examine a class of robust synchronization, global stability criterion, and boundedness analysis for delayed fractional‐order competitive type‐neural networks with impulsive effects and different time scales. Firstly, by endowing the robust analysis skills and a new class of Lyapunov‐Krasovskii functional approach, the error dynamical system is furnished to be a robust adaptive synchronization in the voice of linear matrix inequality (LMI) technique. Secondly, by ignoring the uncertain parameter terms, the existence of equilibrium points are established by means of topological degree properties, and the solution representation of the considered network model are provided. Thirdly, a novel global asymptotic stability condition is proposed in the voice of LMIs, which is less conservative. Finally, our analytical results are justified with two numerical examples with simulations.