A growing self-organizing algorithm for dynamic clustering
R. Ohta, Toshimichi Saito · 2002
Presents a growing self-organizing algorithm for dynamic clustering. Controlling a signal counter of each cell, the network can grow. Also, if there exists undesired cell for the clustering, the cell can be deleted virtually. Our algorithm can reinforce the clustering function and the learned network can adapt flexibly to time-variant input space.