DocumentCode
2398993
Title
Ultimate boundedness of stochastic Cohen-Grossberg neural networks with delays
Author
Zhou, Qinghua ; Wan, Li ; Cheng, Guo
Author_Institution
Dept. of Math., Zhaoqing Univ., Zhaoqing, China
fYear
2012
fDate
19-20 May 2012
Firstpage
333
Lastpage
336
Abstract
The ultimate boundedness is one of foundational concepts, which plays an important role in investigating the global asymptotic stability, its control and synchronization for dynamical systems. The ultimate boundedness of stochastic Cohen-Grossberg neural networks with time-varying delays is investigated. By employing Lyapunov method and matrix technique, some novel results and criteria on stochastic ultimate boundedness are derived. Finally, a numerical example is given to illustrate the correctness and effectiveness of our theoretical results.
Keywords
Lyapunov methods; asymptotic stability; delays; matrix algebra; neural nets; stochastic systems; Lyapunov method; dynamical systems synchronization; global asymptotic stability; matrix technique; stochastic Cohen-Grossberg neural networks; time-varying delays; ultimate boundedness; Asymptotic stability; Delay; Neural networks; Numerical stability; Stability criteria; Stochastic processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems and Informatics (ICSAI), 2012 International Conference on
Conference_Location
Yantai
Print_ISBN
978-1-4673-0198-5
Type
conf
DOI
10.1109/ICSAI.2012.6223628
Filename
6223628
Link To Document