6.3 Synaptic convergence to centroids:AVQ Algorithms Competitive learning adaptively quantizes the input pattern space R".Probability density function p(x)characterizes the continuous distributions of patterns in R. We shall prove that competitive AVQ synaptic vector m, converge exponentially quickly to pattern-class centroids and. more generally,at equilibrium they vibrate about the centroids in a Browmian motion 2003.11.19 62003.11.19 6 6.3 Synaptic convergence to centroids: AVQ Algorithms We shall prove that competitive AVQ synaptic vector converge exponentially quickly to pattern-class centroids and, more generally, at equilibrium they vibrate about the centroids in a Browmian motion. m j Competitive learning adaptively quantizes the input pattern space . Probability density function characterizes the continuous distributions of patterns in . n R p(x) n R