TOR VERGATA UNIVERSITY UNSUPERVISED CLASSIFICATION ...

Chapter 1 19
This interaction determines a modification of the weights dependent on
neighborhood function and the response of the neuron. Gauss‘s function can be
used for this purpose:
where rc is the position vector of the winning neuron, rj is the position vector of the
jth neuron of the map (Fig. 1.2) and σ is named proximity parameter.
Fig. 1.2: radius of interaction
When the process starts, σ parameter has a high value, thus the area of bubble is
wide. During the learning phase, the bubble decreases its dimension, until a certain
user-defined value.
The weights of the neurons in the bubble are, therefore, updated according to the
following formula:
where is the learning rate and decreases gradually during the learning phase.