TY - GEN
T1 - On absolute stability of delayed neural networks
AU - Sun, Guigen
AU - Sun, Changyin
N1 - Publisher Copyright:
© 2002 IEEE.
PY - 2002
Y1 - 2002
N2 - This paper first investigates the absolute exponential stability (AEST) of delayed neural networks with a general class of partially Lipschitz continuous and monotone increasing activation functions. The main results obtained are that if the interconnection matrix T of the delayed neural networks satisfies that -T is an H -matrix with nonnegative diagonal elements and there exists k satisfying the condition concerned, then the neural network system is absolutely stable (ABST).
AB - This paper first investigates the absolute exponential stability (AEST) of delayed neural networks with a general class of partially Lipschitz continuous and monotone increasing activation functions. The main results obtained are that if the interconnection matrix T of the delayed neural networks satisfies that -T is an H -matrix with nonnegative diagonal elements and there exists k satisfying the condition concerned, then the neural network system is absolutely stable (ABST).
KW - Absolute exponential stability
KW - delayed neural networks
KW - partially Lipschitz continous
UR - https://www.scopus.com/pages/publications/84976421795
U2 - 10.1109/ICCCAS.2002.1179099
DO - 10.1109/ICCCAS.2002.1179099
M3 - 会议稿件
AN - SCOPUS:84976421795
T3 - 2002 International Conference on Communications, Circuits and Systems and West Sino Exposition, ICCCAS 2002 - Proceedings
SP - 1675
EP - 1679
BT - 2002 International Conference on Communications, Circuits and Systems and West Sino Exposition, ICCCAS 2002 - Proceedings
A2 - Li, Lemin
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 1st International Conference on Communications, Circuits and Systems, ICCCAS 2002
Y2 - 29 June 2002 through 1 July 2002
ER -