@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}, }