Kohonen Feature Map


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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)


Sample Structure


Kohonen Feature Map / Self-organizing Map / SOM
Kohonen Feature Map / Self-organizing Map

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
Neural Net Components in an Object Oriented Class Structure