Title :
Robust Stability Analysis of Interval Neural Networks with Time Delay
Author_Institution :
Coll. of Comput. Sci. & Inf. Eng., Zhejiang Gongshang Univ., Hangzhou
Abstract :
The problem of robust stability analysis for time-delayed interval neural networks with nonlinear perturbation is investigated via Lyapunov stability theory. The interval neural networks are equivalent to parameter matched uncertain systems with some matrix transformations. The sufficient conditions for robust stability of interval neural networks with time delay are developed. The robust stable criteria in this paper are presented in terms of linear matrix inequality
Keywords :
Lyapunov methods; delays; linear matrix inequalities; neural nets; perturbation techniques; stability; uncertain systems; Lyapunov stability theory; linear matrix inequality; nonlinear perturbation; parameter matched uncertain system; robust stability analysis; time-delayed interval neural network; Computer science; Delay effects; Educational institutions; Linear matrix inequalities; Lyapunov method; Neural networks; Robust stability; Robustness; Stability analysis; Sufficient conditions;
Conference_Titel :
Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9422-4
DOI :
10.1109/ICNNB.2005.1614651
