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.