Kohonen Feature Map

The Kohonen Feature Map was first introduced by finnish professor Teuvo Kohonen (University of Helsinki) in 1982.

It is probably the most useful neural net type, if the learning process of the human brain shall be simulated. The "heart" of this type is the feature map, a neuron layer where neurons are organizing themselves according to certain input values.

The type of this neural net is both feedforward (input layer to feature map) and feedback (feature map).

(A Kohonen Feature Map is used in the sample applet)

Type	feedforward / feedback
Neuron layers	1 input layer, 1 map layer
Input value types	binary, real
Activation function	sigmoid
Learning method	unsupervised
Learning algorithm	selforganization
Mainly used in	pattern classification, optimization problems, simulation