Title :
On global robust exponential stability of interval neural networks with delays
Author :
Sun, Changyin ; Song, Shiji ; Feng, Chun-Bo
Author_Institution :
Res. Inst. of Autom., Southeast Univ., Nanjing, China
fDate :
6/24/1905 12:00:00 AM
Abstract :
In this paper, based on globally Lipschitz continuous activation functions, new conditions ensuring existence, uniqueness and global robust exponential stability of the equilibrium point of interval neural networks with delays are obtained. The delayed Hopfield network, bidirectional associative memory network and cellular neural network are special cases of the network model considered. All the results obtained are generalizations of some recent results reported in the literature for neural networks with constant delays
Keywords :
asymptotic stability; content-addressable storage; neural nets; transfer functions; Lipschitz continous activation functions; bidirectional associative memory network; cellular neural network; delayed Hopfield network; equilibrium point; exponential stability; interval neural networks; Associative memory; Convergence; Delay effects; Electronic mail; Fluctuations; Neural networks; Robust stability; Stability analysis; Sun; Very large scale integration;
Conference_Titel :
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7278-6
DOI :
10.1109/IJCNN.2002.1007580
