@article{(Open Science Index):https://publications.waset.org/pdf/2190,
	  title     = {Estimating an Optimal Neighborhood Size in the Spherical Self-Organizing Feature Map},
	  author    = {Alexandros Leontitsis and  Archana P. Sangole},
	  country	= {},
	  institution	= {},
	  abstract     = {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.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {2},
	  number    = {6},
	  year      = {2008},
	  pages     = {2208 - 2212},
	  ee        = {https://publications.waset.org/pdf/2190},
	  url   	= {https://publications.waset.org/vol/18},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 18, 2008},
	}