Kernel-based topographic map formation by local density modeling

Authors:
Marc M. Van Hulle
Affiliations:
K. U. Leuven, Laboratorium voor Neuro-en Psychofysiologie, Leuven, Belgium
Venue:
Neural Computation
Year:
2002

Citing 9
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Abstract

We introduce a new learning algorithm for kernel-based topographic map formation. The algorithm generates a gaussian mixture density model by individually adapting the gaussian kernels' centers and radii to the assumed gaussian local input densities.