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|
|Mainly used in||pattern classification, optimization problems, simulation|