Title :
Batch self-organizing maps on a unit sphere
Author_Institution :
Cincinnati Univ., OH, USA
Abstract :
Kohonen´s batch map over data on a unit sphere is modified. An energy function is proposed and the convergence of the algorithm is proven. It is shown that this deterministic, batch-mode self-organizing algorithm is efficient and performs well
Keywords :
convergence; pattern recognition; self-organising feature maps; unsupervised learning; Kohonen´s batch map; batch self-organizing maps; convergence; deterministic batch-mode self-organizing algorithm; energy function; unit sphere; Application software; Clustering algorithms; Computer simulation; Convergence; Data visualization; Displays; Partitioning algorithms; Postal services; Self organizing feature maps; Stochastic processes;
Conference_Titel :
Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
0-7803-4859-1
DOI :
10.1109/IJCNN.1998.687215
