 Competitive learning

Units compete to respond to an input, and the winning unit or sparse winning set strengthens its representation of that input. A prototype update is $w_k\leftarrow w_k+\eta (x-w_k)$ for the winner $k$, with $0<\eta <1$. The winner moves toward the sample: $w_k^{\prime }-x=(1-\eta )(w_k-x)$. Competition and constraints prevent all units from learning the same unrestricted average.