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
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;
Conference_Titel :
Information Science and Technology (ICIST), 2011 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-9440-8
DOI :
10.1109/ICIST.2011.5765137
