Several other models without a fixed network dimensionality are known. DeSieno (1988) proposed a method where frequent winners get a ``bad conscience'' for winning so often and, therefore, add a penalty term to the distance from the input signal. This leads eventually to a situation where each unit wins approximately equally often (entropy maximization).

Kangas et al. (1990) proposed to use the minimum spanning tree among the
units as neighborhood topology to eliminate the *a priori* choice for a
topology in some models.

Some other methods have been proposed.

Sat Apr 5 18:17:58 MET DST 1997