Title :
Robust stability of interval neural networks with multiple delays
Author :
Jialing Liu ; Xiaofeng Liao
Author_Institution :
Dept. of Comput. Sci. & Eng., Chongqing Inst. of Technol., Chongqing
Abstract :
In this paper, a new criterion is established for global robust asymptotic stability of a class of interval neural networks with multiple constant delays via the Lyapunov-Krasovskii stability theory and the linear matrix inequality (LMI) approach. A numerical example is also given to show the effectiveness of our results.
Keywords :
Lyapunov matrix equations; Lyapunov methods; asymptotic stability; delays; neural nets; robust control; Lyapunov-Krasovskii stability theory; global robust asymptotic stability; interval neural networks; linear matrix inequality; multiple constant delays; Asymptotic stability; Automation; Computer science; Delay effects; Intelligent control; Linear matrix inequalities; Neural networks; Robust stability; Stability criteria; Uncertainty; Lyapunov-Krasovskii functional; interval delayed neural networks (IDNN); linear matrix inequality (LMI); robust stability; time delays;
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
DOI :
10.1109/WCICA.2008.4594508
