Title :
Global Robust Stability for Neural Networks with Delays
Author :
Li, Zhonghua ; Wang, Jianjun
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Leshan Teachers´´ Coll., Leshan
Abstract :
In this paper, some criteria are derived for global robust asymptotic stability of a class of interval neural networks with multiple delays via the Lyapunov-Krasovskii stability theory for functional differential equations and the linear matrix inequality (LMI) approach. Numerical example is also given to show the effectiveness of our results.
Keywords :
Lyapunov matrix equations; asymptotic stability; delays; differential equations; functional equations; linear matrix inequalities; neurocontrollers; robust control; Lyapunov-Krasovskii stability theory; delay; functional differential equation; global robust asymptotic stability; interval neural network; linear matrix inequality approach; Application software; Asymptotic stability; Computer science; Educational institutions; Information technology; Intelligent networks; Linear matrix inequalities; Neural networks; Robust stability; Stability criteria;
Conference_Titel :
Intelligent Information Technology Application Workshops, 2008. IITAW '08. International Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-0-7695-3505-0
DOI :
10.1109/IITA.Workshops.2008.87
