Stability analysis of neutral neural networks with time-varying delays

LIU Jin; ZHAO Weirui

doi:10.3969/j.issn.1000-5641.201911016

Issue 4

Jul. 2020

Turn off MathJax

Article Contents

Article Navigation > Journal of East China Normal University (Natural Sciences) > 2020 > (4): 35-44

LIU Jin, ZHAO Weirui. Stability analysis of neutral neural networks with time-varying delays[J]. Journal of East China Normal University (Natural Sciences), 2020, (4): 35-44. doi: 10.3969/j.issn.1000-5641.201911016

Citation:

LIU Jin, ZHAO Weirui. Stability analysis of neutral neural networks with time-varying delays[J]. Journal of East China Normal University (Natural Sciences), 2020, (4): 35-44. doi: 10.3969/j.issn.1000-5641.201911016

Citation:

PDF( 691 KB)

Stability analysis of neutral neural networks with time-varying delays

doi: 10.3969/j.issn.1000-5641.201911016

LIU Jin,
ZHAO Weirui^,

School of Science, Wuhan University of Technology, Wuhan　430070, China

Received Date: 2019-03-27
Available Online: 2020-07-20
Publish Date: 2020-07-25

Abstract

Abstract

In this paper, a class of neutral neural networks with time-varying delays was considered. First, the existence and uniqueness of equilibrium was obtained using the homeomorphic mapping theorem. Next, by constructing the corresponding Lyapunov functional and using Lyapunov stability theory, sufficient conditions for the global asymptotic stability of equilibrium were established. A comparison between our results and the existing results was made, revealing that our results can be used as criteria for judging the stability of some systems. Lastly, several numerical simulations were carried out to illustrate the results.
- neutral system,
- neural network,
- time-varying delays,
- global asymptotic stability

FullText(HTML)

References(11)

References

[1]	PARK J H, KNOW O M, LEE S M. LMI optimization approach on stability for delayed neural networks of neutral-type [J]. Applied Mathematics and Computation, 2007, 169(1): 1245-1255.
[2]	MAHMOUD M S, ISMAIL A. Improved results on robust exponential stability criteria for neutral-type delayed neural networks [J]. Applied Mathematics and Computation, 2010, 217(7): 3011-3019. DOI: 10.1016/j.amc.2010.08.034.
[3]	LAKSHMANAN S, PARK J H, JUNG H Y, et al. A delay partitioning approach to delay-dependent stability analysis for neutral type neural networks with discrete and distributed delays [J]. Neurocomputing, 2013, 111(6): 81-89.
[4]	AOUITI C, MIAADI F. Finite time stabilization of neutral Hopfield neural networks with mixed delays [J]. Neural Processing Letters, 2018, 48(3): 1645-1669. DOI: 10.1007/s11063-018-9791-y.
[5]	罗日才, 许弘雷, 王五生. 一类新的变时滞中立型神经网络的全局渐近稳定性条件 [J]. 数学物理学报(A 辑), 2015, 35(3): 634-640.
[6]	ORMAN Z. New sufficient conditions for global stability of neutral-type neural networks with time delays [J]. Neurocomputing, 2012, 97(1): 141-148.
[7]	OZCAN N. New conditions for global stability of neutral-type delayed Cohen-Grossberg neural networks [J]. Neural Networks, 2018, 106(1): 1-7.
[8]	CHEN S S, ZHAO W R, XU Y N. Criteria for globally exponential stability of delayed Cohen-Grossberg neural network [J]. Mathematics and Computers in Simulation, 2009, 79(5): 1527-1543. DOI: 10.1016/j.matcom.2008.07.002.
[9]	周正珍. 时滞Cohen-Grossberg神经网络的稳定性分析 [D]. 长沙: 中南大学, 2009.
[10]	SAMLI R, ARIK S. New results for global stability of a class of neutral-type neural systems with time delays [J]. Applied Mathematics & Computation, 2009, 210(2): 564-570.
[11]	AKCA H, COVACHEV V, COVACHEVA Z. Global asymptotic stability of Cohen-Grossberg neural networks of neutral type [J]. Journal of Mathematical Sciences, 2015, 205(6): 719-732. DOI: 10.1007/s10958-015-2278-8.