A self-organizing network that can follow non-stationary distributions
A new on-line criterion for identifying “useless” neurons of a self-organizing network is proposed. When this criterion is used in the context of the (formerly developed) growing neural gas model to guide deletions of units, the resulting method is able to closely track nonstationary distributions. Slow changes of the distribution are handled by adaptation of existing units. Rapid changes are handled by removal of “useless” neurons and subsequent insertions of new units in other places.
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