Winner-Relaxing Self-Organizing Maps

Details Winner-Relaxing Self-Organizing Maps Winner-Relaxing Self-Organizing Maps

2002-08-21

arxiv.org/abs/cond-mat/0208414v2

Neural Computation 17 (5), 996-1009 (2005)

Physics

Condensed Matter

Disordered Systems and Neural Networks

14 pages (6 figs included). To appear in Neural Computation

Scientific paper

10.1162/0899766053491922

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.

Affiliated with

Also associated with

No associations

Rating

Winner-Relaxing Self-Organizing Maps does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Winner-Relaxing Self-Organizing Maps, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Winner-Relaxing Self-Organizing Maps will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-220662