DocumentCode
3282011
Title
The Growing Self-Organizing Surface Map: Improvements
Author
DalleMole, Vilson L. ; Araujo, Aluizio F. R.
fYear
2008
fDate
26-30 Oct. 2008
Firstpage
183
Lastpage
188
Abstract
The growing self organizing surface map (GSOSM) is a novel map model that learns a 2D surface immersed in a 3D space. The GSOSM model introduces a novel connection learning rule called CCHL. In this paper we present an overview of GSOSM model and its connection learning rule CCHL. The GSOSM dynamic is analyzed and changes are proposed to improve the algorithm performance and time run. The results of the proposed improvements are depicted and discussed.
Keywords
learning (artificial intelligence); self-organising feature maps; algorithm performance; connection learning rule; growing self-organizing surface map; Algorithm design and analysis; Clouds; Least squares approximation; Neural networks; Organizing; Performance analysis; Shape; Signal processing algorithms; Surface fitting; Surface reconstruction; GSOSM; SOM; Surface Reconstruction;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2008. SBRN '08. 10th Brazilian Symposium on
Conference_Location
Salvador
ISSN
1522-4899
Print_ISBN
978-1-4244-3219-6
Electronic_ISBN
1522-4899
Type
conf
DOI
10.1109/SBRN.2008.16
Filename
4665913
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