Multilevel neural net adaptive models using the metagraph approach
- 作者: Fedorenko Y.S.1, Gapanyuk Y.E.1
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隶属关系:
- N.E. Bauman Moscow State Technical University
- 期: 卷 25, 编号 4 (2016)
- 页面: 228-235
- 栏目: Article
- URL: https://journals.rcsi.science/1060-992X/article/view/194913
- DOI: https://doi.org/10.3103/S1060992X16040020
- ID: 194913
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详细
The paper considers adaptive models enabling real-time processing of data flows. The drawbacks of current algorithms are examined. A method that combines advantages of deep learning, self-organizing neural nets and the metagraph approach is offered for designing adaptive models. A part of the method is realized, data clustering experiments are carried out and experimental results are analyzed.
作者简介
Yuri Fedorenko
N.E. Bauman Moscow State Technical University
编辑信件的主要联系方式.
Email: fedyura11235@mail.ru
俄罗斯联邦, Moscow
Yuri Gapanyuk
N.E. Bauman Moscow State Technical University
Email: fedyura11235@mail.ru
俄罗斯联邦, Moscow
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