The name of the whole class of networks came from the designation of algorithm called self-organizing Kohonen's maps. They had been described ine the publication "Self Organizing Map". Kohonen proposed two kinds of proximity : rectangular and gauss. The first is :
and the second: 
"lambda" is the radius of proximity, it decreases in time.
Use of Kohonen's method gives us better results than "Winner Takes All" method. Organization of the net is better (neurons organization represents the distribution of input data in a better way) and the convergence of the algorithm is higher. Because of that the time of single iteration is a few times longer - wages of many neurons , not only winners', have to be modified.