Novel stability conditions of fuzzy neural networks with mixed delays under impulsive perturbations

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• 作者：Mei-Yan Lin ^{2063933223@qq.com} ; Cheng-De Zheng ; ^{chd4211853@163.com}
• 关键词：Impulse ; Fuzzy neural networks ; Linear convex combination ; Reciprocal convex combination ; Quadratic convex combination
• 刊名：Optik - International Journal for Light and Electron Optics
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：131
• 期：Complete
• 页码：869-884
• 全文大小：562 K
• 卷排序：131

文摘

This paper investigates the problem of stability of fuzzy neural networks with time-varying and continuously distributed delays under impulsive perturbations. Two new delay-dependent criteria are obtained in terms of linear convex combination technique, the reciprocal convex lemma, Wirtinger-based integral inequality, and the quadratic convex combination method. The first presented criterion does not require all the symmetric matrices involved in the employed quadratic Lyapunov–Krasovskii functional to be positive definite. Furthermore, the conservatism of delay-dependent stability conditions can be reduced due to the relaxation on the positive-definiteness of some Lyapunov matrices. It is shown numerically that the stability criteria proposed in this paper are less conservative than some of the latest results in the literature.