Robust Training of ADALINA Based on the Criterion of the Maximum Correntropy in the Presence of Outliers and Correlated Noise

被引：0
|
作者：
Rudenko, Oleg [1 ]
Bersonov, Oleksandr [1 ]
机构：
[1] Kharkiv Natl Univ Radio Elect, Nauky Ave 14, UA-61166 Kharkiv, Ukraine
来源：
COLINS 2021: COMPUTATIONAL LINGUISTICS AND INTELLIGENT SYSTEMS, VOL I | 2021年 / 2870卷
关键词：
ADALINA; optimization; neural network; algorithm; gradient; training; estimation;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In the given paper the main relations that describe an adaptive multi-step algorithm for training ADALINA are obtained. The use of such an algorithm accelerates the learning process by using information not only about one last cycle, but also about a number of previous cycles. The robustness of the estimates is ensured by the application of the maximum correlation criterion.
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页数：12
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