%0 Journal Article
	%A Alexandros Leontitsis and  Archana P. Sangole
	%D 2008
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 18, 2008
	%T Estimating an Optimal Neighborhood Size in the Spherical Self-Organizing Feature Map
	%U https://publications.waset.org/pdf/2190
	%V 18
	%X This article presents a short discussion on
optimum neighborhood size selection in a spherical selforganizing
feature map (SOFM). A majority of the literature
on the SOFMs have addressed the issue of selecting optimal
learning parameters in the case of Cartesian topology SOFMs.
However, the use of a Spherical SOFM suggested that the
learning aspects of Cartesian topology SOFM are not directly
translated. This article presents an approach on how to
estimate the neighborhood size of a spherical SOFM based on
the data. It adopts the L-curve criterion, previously suggested
for choosing the regularization parameter on problems of
linear equations where their right-hand-side is contaminated
with noise. Simulation results are presented on two artificial
4D data sets of the coupled Hénon-Ikeda map.
	%P 2208 - 2212