DocumentCode
2252009
Title
Dynamic analysis of winner-take-all neural networks with global inhibitory feedback
Author
Yu, Yongbin ; Jin, Ju ; Zhang, Rongquan ; Ebong, Idongesit E. ; Mazumder, Pinaki
Author_Institution
School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, 610054, P.R. China
fYear
2015
fDate
28-30 July 2015
Firstpage
3497
Lastpage
3500
Abstract
This work studies dynamical behavior of a general class of winner-take-all (WTA) neural networks with global inhibitory feedback. Sufficient conditions for the neural network to have equilibrium solution and WTA point are obtained. Furthermore, new conditions for exponential stabilization of the WTA neural network are presented. Finally, simulation results verify the feasibility and effectiveness of our method. The results can be extended to design other competitive neural networks.
Keywords
Biological neural networks; Mathematical model; Neurons; Recurrent neural networks; Simulation; Stability analysis; Winner-take-all; exponentially stable; inhibition; neural network;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference (CCC), 2015 34th Chinese
Conference_Location
Hangzhou, China
Type
conf
DOI
10.1109/ChiCC.2015.7260178
Filename
7260178
Link To Document