Kernel Fuzzy Kohonen’s Clustering Neural Network and It’s Recursive Learning
- Авторы: Bodyanskiy Y.V.1, Deineko A.O.1, Eze F.M.1
-
Учреждения:
- Kharkiv National University of Radio Electronics
- Выпуск: Том 52, № 3 (2018)
- Страницы: 166-174
- Раздел: Article
- URL: https://journals.rcsi.science/0146-4116/article/view/175481
- DOI: https://doi.org/10.3103/S0146411618030045
- ID: 175481
Цитировать
Аннотация
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.
Об авторах
Ye. Bodyanskiy
Kharkiv National University of Radio Electronics
Email: anastasiya.deineko@gmail.com
Украина, Kharkiv, 61166
A. Deineko
Kharkiv National University of Radio Electronics
Автор, ответственный за переписку.
Email: anastasiya.deineko@gmail.com
Украина, Kharkiv, 61166
F. Eze
Kharkiv National University of Radio Electronics
Email: anastasiya.deineko@gmail.com
Украина, Kharkiv, 61166
Дополнительные файлы
