Winner-Relaxing Self-Organizing Maps
| dc.creator | Claussen, Jens Christian | |
| dc.date | 2002-08-21 | |
| dc.date | 2004-11-02 | |
| dc.date.accessioned | 2026-07-07T06:31:50Z | |
| dc.date.available | 2026-07-07T06:31:50Z | |
| dc.description | A new family of self-organizing maps, the Winner-Relaxing Kohonen Algorithm, is introduced as a generalization of a variant given by Kohonen in 1991. The magnification behaviour is calculated analytically. For the original variant a magnification exponent of 4/7 is derived; the generalized version allows to steer the magnification in the wide range from exponent 1/2 to 1 in the one-dimensional case, thus provides optimal mapping in the sense of information theory. The Winner Relaxing Algorithm requires minimal extra computations per learning step and is conveniently easy to implement. | |
| dc.description | 14 pages (6 figs included). To appear in Neural Computation | |
| dc.identifier | https://arxiv.org/abs/cond-mat/0208414 | |
| dc.identifier | http://arxiv.org/abs/cond-mat/0208414 | |
| dc.identifier | Neural Computation 17 (5), 996-1009 (2005) | |
| dc.identifier | doi:10.1162/0899766053491922 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/98726 | |
| dc.subject | Disordered Systems and Neural Networks | |
| dc.subject | Neural and Evolutionary Computing | |
| dc.subject | Adaptation and Self-Organizing Systems | |
| dc.subject | Neurons and Cognition | |
| dc.title | Winner-Relaxing Self-Organizing Maps | |
| dc.type | text |