NDLI: Novel Delay-Dependent Stability Criteria for Fuzzy Neural Networks Using Delay-Decomposition Approach

Content Provider	Springer Nature Link
Author	Wang, Zhanshan Gu, Yun Zheng, Cheng De Zhang, Xiaoyu
Copyright Year	2015
Abstract	This paper investigates the global asymptotic stability of fuzzy neural networks with time-varying and unbounded continuously distributed delays in mean square. Based on a new Lyapunov–Krasovskii functional, by effective combination of Jensen integral inequality with reciprocally convex and quadratic convex combination method, several novel sufficient conditions are derived to ensure the global asymptotic stability of the equilibrium point of the considered networks in mean square. The proposed results, which are expressed in terms of linear matrix inequalities, can be easily verified via MATLAB software. The main advantage of the proposed criteria lies in its reduced conservatism by means of the time delay-decomposition technique and Wirtinger-based inequality. In addition to that, a numerical example is given to demonstrate the effectiveness and less conservativeness of our theoretical results over the existing literature.
Ending Page	526
Page Count	26
Starting Page	501
File Format	PDF
ISSN	0278081X
e-ISSN	15315878
Journal	Circuits, Systems, and Signal Processing
Issue Number	2
Volume Number	35
Language	English
Publisher	Springer US
Publisher Date	2015-05-20
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Delay-decomposition approach Quadratic convex combination Lyapunov and other classical stabilities (Lagrange, Poisson, $L^p, l^p$ , etc.) Signal, Image and Speech Processing Electronics and Microelectronics, Instrumentation Fuzzy neural networks Reciprocally convex combination Circuits and Systems Neural networks, artificial life and related topics Electrical Engineering
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Signal Processing

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