1 research outputs found
Winner-relaxing and winner-enhancing Kohonen maps: Maximal mutual information from enhancing the winner
The magnification behaviour of a generalized family of self-organizing
feature maps, the Winner Relaxing and Winner Enhancing Kohonen algorithms is
analyzed by the magnification law in the one-dimensional case, which can be
obtained analytically. The Winner-Enhancing case allows to acheive a
magnification exponent of one and therefore provides optimal mapping in the
sense of information theory. A numerical verification of the magnification law
is included, and the ordering behaviour is analyzed. Compared to the original
Self-Organizing Map and some other approaches, the generalized Winner Enforcing
Algorithm requires minimal extra computations per learning step and is
conveniently easy to implement.Comment: 6 pages, 5 figures. For an extended version refer to cond-mat/0208414
(Neural Computation 17, 996-1009