Excellence in Research and Innovation for Humanity
@article{(International Science Index):http://waset.org/publications/2190,
  title    = {Estimating an Optimal Neighborhood Size in the Spherical Self-Organizing Feature Map},
  author    = {Alexandros Leontitsis and  Archana P. Sangole},
  country   = {},
  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, Electrical, Automation, Control and Information Engineering},  volume    = {2},
  number    = {6},
  year      = {2008},
  pages     = {2208 - 2212},
  ee        = {http://waset.org/publications/2190},
  url       = {http://waset.org/Publications?p=18},
  bibsource = {http://waset.org/Publications},
  issn      = {eISSN:1307-6892},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 18, 2008},