Note on generalized self-organizing network algorithms
James C. Bezdek · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1990
In this note we identify some similarities and differences between two clustering models, viz., the fuzzy c-means (FCM) and Kohonen self-organizing (KSO) feature map approaches. This leads us to suggest that there is an important unknown relationship between the two methodologies. Consequently, we propose several avenues of research which, if successfully resolved, will strengthen both the FCM and Kohonen models and their utility for applications in clustering and classifier design.