Abstract
One of the main problems associated with artificial neural networks
on-line learning methods is the
estimation of model order.
In this paper, we report about a new approach to constructing a
resource-allocating network exploiting weights adaptation using
QRD-based recursive least-squares technique. Further, we studied
the performance of Dynamic Cell Structures algorithm
for on-line adaptation of centers positions. The
proposed method was tested on the task of Mackey-Glass
time-series prediction. Order of resulting
networks and their prediction abilities were superior to those
previously reported by Platt.
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