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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Chang Jou Quen Zong Wu Shuh-Chuan Tsay Yuh-Jiuan Tsay Shih-Shien Yu |
| Copyright Year | 1991 |
| Description | Author affiliation: Telecommun. Labs., Minist. of Commun., Chung-Li, Taiwan (Chang Jou; Quen Zong Wu; Shuh-Chuan Tsay; Yuh-Jiuan Tsay; Shih-Shien Yu) |
| Abstract | Proposes a distance based neural network for pattern classification. In the beginning of network training, a hyperellipsoid is constructed for each training pattern. The authors try to merge the hyperellipsoids of the same classes without interfering with the hyperellipsoids of other classes. Because each class is represented by several hyperellipsoids, any pattern which is located in or nearest to one of these hyperellipsoids is classified to this class. This distance based neural network does not need any hidden layer. An example is given to compare the performances of this network and the multilayer perceptron. It shows that better performance may be obtained by using this network.< |
| Starting Page | 1176 |
| Ending Page | 1179 |
| File Size | 2934919 |
| Page Count | 4 |
| File Format | |
| ISBN | 0780300505 |
| DOI | 10.1109/ISCAS.1991.176245 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1991-06-11 |
| Publisher Place | Singapore |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Neural networks Pattern classification Self organizing feature maps Multilayer perceptrons Computer networks Nearest neighbor searches Cost function Helium Merging |
| Content Type | Text |
| Resource Type | Article |
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