Vectors from any dimension are fed into a discrete map in this neural network. The map is used to create training data for an organization. The map could have one or two dimensions. Depending on the value, the weight of the neurons may fluctuate. The location of the neuron will not vary during the training of the map and will remain constant. In the initial stage of the self-organization process, each neuron value is given an input vector and a little weight. The neuron that is nearest to the point is the winner. In the second phase, other neurons will join the winning neuron in moving towards the target.