DocumentCode
3110579
Title
Global dissipativity for Cohen-Grossberg neural networks with both time-varying delays and infinite distributed delays
Author
Tu, Zhengwen ; Jian, Jigui ; Wang, Weiwei
Author_Institution
Inst. of Nonlinear & Complex Syst., China Three Gorges Univ., Yichang, China
fYear
2011
fDate
26-28 March 2011
Firstpage
982
Lastpage
985
Abstract
In this paper, we study the global dissipativity for Cohen-Grossberg neural networks with both time-varying delays and infinite distributed delays. Based on Lyapunov functions, mean value theorem and inequality techniques, several algebraic criterions for the global dissipativity are obtained. Meanwhile, the estimations of the positive invariant set and globally attractive set are given out. Finally, one example is given and analyzed to demonstrate our results.
Keywords
Lyapunov methods; delays; neural nets; time-varying systems; Cohen-Grossberg neural network; Lyapunov function; inequality technique; infinite distributed delay; mean value theorem; time-varying delay; Artificial neural networks; Asymptotic stability; Circuit stability; Delay; Delay effects; Numerical stability; Stability analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Science and Technology (ICIST), 2011 International Conference on
Conference_Location
Nanjing
Print_ISBN
978-1-4244-9440-8
Type
conf
DOI
10.1109/ICIST.2011.5765137
Filename
5765137
Link To Document