Chapter 6 Architecture and Equilibria 6.3 Synaptic convergence to centroids:AVQ Al gor ithms The Stochastic unsupervised competitive learning law: ● m)=S0yj儿x-m]+nj 6-10 We want to show that at equilibrium m=x We assume S,≈I,(x) 6-11 The equilibrium and convergence depend on approximation (6-11),so 6-10 reduces m=1D,(x)[x-m]+n 6-12 2004.11.10 102004.11.10 10 Chapter 6 Architecture and Equilibria 6.3 Synaptic convergence to centroids:AVQ Algorithms The Stochastic unsupervised competitive learning law: = ( )[ − ]+ 6 −10 • j j j mj nj m S y x We want to show that at equilibrium mj = xj S  I (x) 6−11 Dj j We assume The equilibrium and convergence depend on approximation (6-11) ,so 6-10 reduces : = ( )[ − ]+ 6 −12 • j D mj nj m I x x j