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86 Extensions to the Standard PSOM Algorithm

Training L-PSOM 2x2
1
data 5x5

1
0.5
-1 0
-0.5
0 -0.5
0.5 -1
1

PSOM 5x5 C-PSOM 5x5

Figure 6.7: a–d; PSOM manifolds with a 5 5 training set. (a) training points
are equidistantly sampled for all PSOMs; (b) shows the resulting mapping of the
local PSOM with sub-grid size

. (c) There are little overshoots in the marginal
mapping areas of the equidistant spaced PSOM (i) compared to (d) the mapping
of the Chebyshev-spaced PSOM (ii) which is for n already visually identical

to the goal map.