Herzlich Willkommen auf den neuen Seiten des Südring Centers Rangsdorf.Unsere Homepage hat sich etwas Schickes übergezogen und erstrahlt nun für Sie im neuen Gewand.The artificial neural network introduced by the Finnish professor Teuvo Kohonen in the 1980s is sometimes called a Kohonen map or network.
The update formula for a neuron v with weight vector W where s is the step index, t an index into the training sample, u is the index of the BMU for D(t), α(s) is a monotonically decreasing learning coefficient and D(t) is the input vector; Θ(u, v, s) is the neighborhood function which gives the distance between the neuron u and the neuron v in step s.
Depending on the implementations, t can scan the training data set systematically (t is 0, 1, 2...
Associated with each node are a weight vector of the same dimension as the input data vectors, and a position in the map space.
The usual arrangement of nodes is a two-dimensional regular spacing in a hexagonal or rectangular grid.
The blue blob is the distribution of the training data, and the small white disc is the current training datum drawn from that distribution.
At first (left) the SOM nodes are arbitrarily positioned in the data space.
This is partly motivated by how visual, auditory or other sensory information is handled in separate parts of the cerebral cortex in the human brain.
An illustration of the training of a self-organizing map.
After many iterations the grid tends to approximate the data distribution (right).