A new learning algorithm is presented for enhancing the scale or structure
of an already trained self-organising map (SOM) without the need to re-use
the original training data. Alternative methods for the insertion of these
additional interpolating neurons, while still preserving the learnt topolog
y, are presented together with two illustrative examples of the algorithm i
n operation.