Multilevel neural net adaptive models using the metagraph approach


如何引用文章

全文:

开放存取 开放存取
受限制的访问 ##reader.subscriptionAccessGranted##
受限制的访问 订阅存取

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

补充文件

附件文件
动作
1. JATS XML

版权所有 © Allerton Press, Inc., 2016