DocumentCode
1159783
Title
An improved maxnet
Author
Chang, Yi C. ; Yu, Sung-Nien ; Kuo, Chung J.
Author_Institution
Dept. of Electr. Eng., Nat. Chung Cheng Univ., Taipei, Taiwan
Volume
34
Issue
6
fYear
2004
Firstpage
2416
Lastpage
2420
Abstract
In the proposed model, dynamic inhibitory weights are used to speed up the convergence rate, and a new convergence rule is applied to find all maxima. The hardware implementation of the proposed model is presented in the study, and simulation results indicate that the proposed model converges much faster than the other networks.
Keywords
convergence; neural nets; set theory; Maxnet model; convergence rate; dynamic inhibitory weight; winner-take-all network; Acceleration; Computational complexity; Convergence; Hardware; Limiting; Logic; Pattern recognition; Research and development; Signal processing; Signal processing algorithms; Convergence rate; inhibitory weights; winner-take-all network; Algorithms; Computer Simulation; Feedback; Models, Statistical; Neural Networks (Computer); Pattern Recognition, Automated; Signal Processing, Computer-Assisted;
fLanguage
English
Journal_Title
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
Publisher
ieee
ISSN
1083-4419
Type
jour
DOI
10.1109/TSMCB.2004.834420
Filename
1356029
Link To Document