Kernel Fuzzy Kohonen’s Clustering Neural Network and It’s Recursive Learning
- 作者: Bodyanskiy Y.V.1, Deineko A.O.1, Eze F.M.1
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隶属关系:
- Kharkiv National University of Radio Electronics
- 期: 卷 52, 编号 3 (2018)
- 页面: 166-174
- 栏目: Article
- URL: https://journals.rcsi.science/0146-4116/article/view/175481
- DOI: https://doi.org/10.3103/S0146411618030045
- ID: 175481
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详细
The architecture of multilayer kernel clustering neuro-fuzzy system and algorithm of its self-learning are intended for the recovery of overlapped clusters in situations when the streams of observations are fed in the online mode is proposed. The designed system, based on the T. Kohonen’s self-organizing map, permits to recover linearly nonseparated data classes, processes information in an online mode, doesn’t suffer from the “curse of dimensionality” and is easy in implementation.
作者简介
Ye. Bodyanskiy
Kharkiv National University of Radio Electronics
Email: anastasiya.deineko@gmail.com
乌克兰, Kharkiv, 61166
A. Deineko
Kharkiv National University of Radio Electronics
编辑信件的主要联系方式.
Email: anastasiya.deineko@gmail.com
乌克兰, Kharkiv, 61166
F. Eze
Kharkiv National University of Radio Electronics
Email: anastasiya.deineko@gmail.com
乌克兰, Kharkiv, 61166
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