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期刊名称: Nonlinearity
Volume:23    Issue:7        Page:1709-1726
ISSN:0951-7715

Delay-dependent stability of neural networks of neutral type with time delay in the leakage term期刊论文

作者: Li Xiaodi Cao Jinde
DOI:10.1088/0951-7715/23/7/010

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页码: 1709-1726
被引频次: 143
出版者: IOP Publishing,IOP PUBLISHING LTD
期刊名称: Nonlinearity
ISSN: 0951-7715
卷期: Volume:23    Issue:7
语言: English
摘要: This paper studies the global asymptotic stability of neural networks of neutral type with mixed delays. The mixed delays include constant delay in the leakage term (i.e. 'leakage delay'), time-varying delays and continuously distributed delays. Based on the topological degree theory, Lyapunov method and linear matrix inequality (LMI) approach, some sufficient conditions are derived ensuring the existence, uniqueness and global asymptotic stability of the equilibrium point, which are dependent on both the discrete and distributed time delays. These conditions are expressed in terms of LMI and can be easily checked by the MATLAB LMI toolbox. Even if there is no leakage delay, the obtained results are less restrictive than some recent works. It can be applied to neural networks of neutral type with activation functions without assuming their boundedness, monotonicity or differentiability. Moreover, the differentiability of the time-varying delay in the non-neutral term is removed. Finally, two numerical examples are given to show the effectiveness of the proposed method.
相关主题: GLOBAL EXPONENTIAL STABILITY, MATHEMATICS, APPLIED, CONTINUOUSLY DISTRIBUTED DELAYS, ROBUST STABILITY, LMI OPTIMIZATION APPROACH, PHYSICS, MATHEMATICAL, VARYING DELAYS, BAM,

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