DocumentCode
458817
Title
LMI Approach for Stochastic Stability of Markovian Jumping Hopfield Neural Networks with Wiener Process
Author
Lou, Xuyang ; Cui, Baotong
Author_Institution
Res. Center of Control Sci. & Eng., Southern Yangtze Univ., Jiangsu
Volume
1
fYear
2006
fDate
16-18 Oct. 2006
Firstpage
107
Lastpage
112
Abstract
This paper deals with the stochastic stability problem for Markovian jumping Hopfield neural networks (MJHNNs) with time-varying delays and Wiener process. Our attention is focused on developing sufficient conditions on stochastic stability, even if the system contains Wiener process. All the obtained results are presented in terms of linear matrix inequality. The efficiency of the proposed results is demonstrated via two numerical examples
Keywords
Hopfield neural nets; Markov processes; linear matrix inequalities; time-varying systems; LMI approach; Markovian jumping Hopfield neural network; Wiener process; linear matrix inequality; stochastic stability; time-varying delay; Asymptotic stability; Delay effects; Hopfield neural networks; Linear matrix inequalities; Neural networks; Stability analysis; Stochastic processes; Stochastic systems; Sufficient conditions; Symmetric matrices;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems Design and Applications, 2006. ISDA '06. Sixth International Conference on
Conference_Location
Jinan
Print_ISBN
0-7695-2528-8
Type
conf
DOI
10.1109/ISDA.2006.187
Filename
4021418
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