Two alternative soft self-organizing maps: their algorithms and applications

Author

Sum, John

Author_Institution

Dept. of Comput., Hong Kong Polytech. Univ., China

Volume

3

fYear

2003

fDate

5-8 Oct. 2003

Firstpage

2587

Abstract

This paper presents two SOM-like algorithms that are extended from two alternative soft competition algorithms namely maximum likelihood competitive learning (MLCL) and fuzzy competitive learning (FCL). Simulation results on the topographic map formation are presented and a possible application of such algorithms for data transmission is elucidated. It is observed that under certain circumstances, the performance of these SSOM algorithms in a vowel data transmission problem can be comparable to and sometimes even better than that of using SOM.

Keywords

fuzzy systems; maximum likelihood estimation; self-organising feature maps; unsupervised learning; vector quantisation; FCL; MLCL; SOM algorithms; data transmission; fuzzy competitive learning; maximum likelihood competitive learning; soft self organizing maps; topographic map formation; Biomedical signal processing; Clustering algorithms; Computational modeling; Data communication; Image communication; Neurons; Self organizing feature maps; Signal processing algorithms; Uniform resource locators; Vector quantization;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man and Cybernetics, 2003. IEEE International Conference on

ISSN

1062-922X

Print_ISBN

0-7803-7952-7

Type

conf

DOI

10.1109/ICSMC.2003.1244273

Filename

1244273