A density based membership function for fuzzy clustering
Giuseppe Acciani, R. Caradonna, E. Chiarantoni, Giuseppe Grassi · 2003
This paper presents a new approach to fuzzy clustering using a membership function sensitive to density. It is a fuzzy membership function which allows the action range of the neural units matching the area they reach, even when the data set is contaminated by uniformly distributed noise points, without a need to fix a priori the number of clusters.