Classification Algorithm Based on Kohonen Network

Kohonen Network is a type of self-organizing competitive neural network designed for unsupervised learning. It autonomously identifies environmental features and performs clustering. Proposed by Professor Teuvo Kohonen from the University of Helsinki, Finland, the network adjusts weights through self-organizing feature mapping, causing the neural network to converge into a representation where each neuron specifically matches or responds to a particular input pattern. The learning process involves unsupervised self-organization, where neurons compete to specialize in different input patterns, enabling specific neurons to act as detectors for certain input patterns during recognition tasks. After training, neurons are divided into distinct regions, each exhibiting unique response characteristics to input models.