Dynamical stability of a high-dimensional self-organizing map

The convergence and the convergence rate of one self-organization algorithm for the high-dimensional self-organizing map in the linearized Amari model are studied in the context of stochastic approximation. The conditions on the neighborhood function and the learning rate are given to guarantee the convergence. It is shown that the convergence of the algorithm can be accelerated by averaging.

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