Title :
Global Asymptotic Stability of Recurrent Neiural Networks with Time-Varying Delays
Author :
Jiang, Haijun ; Cao, Jinde
Author_Institution :
Dept. of Math., Southeast Univ., Nanjing
Abstract :
This paper investigates the existence of equilibrium point and its global asymptotic stability for recurrent neural networks with time-varying delays. Various sufficient conditions ensuring the existence of equilibrium point and its global asymptotic stability are given. The results obtained in this paper extend and generalize those given in previous literature
Keywords :
asymptotic stability; delays; recurrent neural nets; time-varying systems; equilibrium point; global asymptotic stability; recurrent neural networks; time-varying delays; Artificial neural networks; Asymptotic stability; Delay effects; Mathematics; Neural networks; Nonlinear equations; Recurrent neural networks; Signal processing; Sufficient conditions; Time varying systems;
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.2005.1614589
