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
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;
Conference_Titel :
Systems and Informatics (ICSAI), 2012 International Conference on
Conference_Location :
Yantai
Print_ISBN :
978-1-4673-0198-5
DOI :
10.1109/ICSAI.2012.6223628
