Competitive learning is a form of unsupervised learning which performs clustering over the input data. In a competitive learning network with n-output neurons, each output neuron is associated with a cluster. When a data point from a cluster is presented to the network, only the neuron corresponding to that cluster responds, while all other neurons remain silent. The single neuron that responds is often called a “winner” and therefore a competitive learning network of the kind just described is also known as a “winner-take-all” network.