Title :
Robust Stability Analysis for Time-Delayed Neural Networks with Nonlinear Disturbance
Author_Institution :
Coll. of Comput. Sci. & Inf. Eng., Zhejiang Gongshang Univ., Hangzhou
Abstract :
The problem of robust stability analysis for time-delayed neural networks with nonlinear disturbance is investigated via Lyapunov stability theory. By constructing suitable Lyapunov functional and using matrix transformation, sufficient conditions on robust asymptotic and exponential stability of time-delayed neural networks with nonlinear disturbance are developed. All the stable criteria in this paper are presented in terms of linear matrix inequality
Keywords :
Lyapunov methods; asymptotic stability; delays; linear matrix inequalities; neural nets; nonlinear systems; Lyapunov stability theory; exponential stability; linear matrix inequality; nonlinear disturbance; robust asymptotic stability; robust stability analysis; time-delayed neural networks; Computer science; Delay effects; Educational institutions; Linear matrix inequalities; Lyapunov method; Neural networks; Neurons; Robust stability; 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.2005.1614652
