Assessment of a Neural Network for the Correction of Measurement Errors

被引:1
|
作者
Meier, Phil [1 ]
Rohrmann, Kris [1 ]
Sandner, Marvin [1 ]
Prochaska, Marcus [1 ]
机构
[1] Ostfalia Univ Appl Sci, Fac Elect Engn, Wolfenbuettel, Germany
来源
2021 IEEE SENSORS | 2021年
关键词
magnetic field sensors; neuronal networks; angular measurements;
D O I
10.1109/SENSORS47087.2021.9639768
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Many modern technology trends such as autonomous driving, image processing or speech recognition are prime examples for the application of machine learning methods. However, the application of these methods is often omitted in safety critical areas since verification and validation of the learned features are problematic. The following work uses a multilayer perceptron in order to correct measurement errors for an angular sensing system and suggests a methodology to extract the learned features. This is possible since the considered system is clearly defined with well known parameters, which is typically for most sensing applications.
引用
收藏
页数:4
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