PSOM+ : Parametrized Self-Organizing Maps for noisy and incomplete data
Klanke, Stefan
Klanke
Stefan
Ritter, Helge
Ritter
Helge
We present an extension to the Parametrized Self-Organizing Map that allows
the construction of continuous manifolds from noisy, incomplete and not necessarily grid-
organized training data. All three problems are tackled by minimizing the overall smoothness
of a PSOM manifold. For this, we introduce a matrix which defines a metric in the space of
PSOM weights, depending only on the underlying grid layout. We demonstrate the method
with several examples, including the kinematics of a PA10 robot arm.
2005