DocumentCode
401620
Title
Asymptotic stability of feedback neural networks with time-delay
Author
Zheng, Hong-Zhen ; Gu, Feng-Qi ; Sun, Yu-shan
Author_Institution
Dept. of Comput. Sci. & Eng., Harbin Inst. of Technol., Wehai, China
Volume
2
fYear
2003
fDate
2-5 Nov. 2003
Firstpage
1113
Abstract
This paper analyzes feedback neural networks with time-delay by discussing asymptotic stability of equilibrium point for a class of recurrent neural networks with time delay. Under certain assumptions, we obtain the sufficient conditions for asymptotic stability of equilibrium point and the asymptotic stability convergence of the trajectory. An example is given to illustrate the feasibility of the neural networks.
Keywords
asymptotic stability; delays; recurrent neural nets; asymptotic stability convergence; equilibrium point; feedback neural networks; recurrent neural networks; time-delay; Artificial neural networks; Associative memory; Asymptotic stability; Biological neural networks; Convergence; Erbium; Neural networks; Neurofeedback; Recurrent neural networks; Sun;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN
0-7803-8131-9
Type
conf
DOI
10.1109/ICMLC.2003.1259651
Filename
1259651
Link To Document