The target of a Kohonen guide is to include vectors of subjective measurement to discrete guide involved neurons. The guide needs to be prepared to make its very own association of the preparation information. It contains it is possible that a couple of measurements. When preparing the guide the area of the neuron stays steady yet the loads vary contingent upon the worth. This self-association procedure has various parts, in the main stage, each neuron worth is instated with a little weight and the info vector. In the subsequent stage, the neuron nearest to the fact of the matter is the 'triumphant neuron' and the neurons associated with the triumphant neuron will likewise move towards the point like in the realistic beneath. The separation between the point and the neurons is determined by the euclidean separation, the neuron with the least separation wins. Through the cycles, every one of the focuses is bunched and every neuron speaks to every sort of group. This is the substance behind the association of Kohonen Neural Network.