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 segment of hyperellipsoidal shells. This approach is computationally and implementationally simpler than other clustering algorithms that have been suggested for this purpose. Experimental results are given to show the effectiveness of the proposed method.
Original language | English |
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Pages (from-to) | 1779-1781 |
Number of pages | 3 |
Journal | Proceedings of the IEEE International Conference on Systems, Man and Cybernetics |
Volume | 2 |
State | Published - 1998 |
Event | Proceedings of the 1998 IEEE International Conference on Systems, Man, and Cybernetics. Part 2 (of 5) - San Diego, CA, USA Duration: 11 Oct 1998 → 14 Oct 1998 |