A Neural-Network-Based Approach to Detecting Hyperellipsoidal Shells

Authors:
Mu-Chun Su;I-Chen Liu
Affiliations:
Department of Electrical Engineering, Tamkang University, Taiwan, R.O.C., e-mail: muchun@ee.tku.edu.tw;Department of Electrical Engineering, Tamkang University, Taiwan, R.O.C., e-mail: muchun@ee.tku.edu.tw
Venue:
Neural Processing Letters
Year:
1999

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Abstract

This paper presents a novel class of neural networks which can be trained in an unsupervised manner to detect a mixture of hyperellipsoidal shells and/or segments of hyperellipsoidal shells. This approach is computationally and implementationally simpler than other clustering algorithms that have been suggested for this purpose. Experimental results on several data sets are presented.