Identification and Classification of Signal Distortions Based on Wavelet Transform and Neural Networks

被引：0
|
作者：
Rykov, A. [1 ]
Luppov, A. [1 ]
Krasikov, M. [1 ]
机构：
[1] Vyatka State Univ, Kirov, Russia
来源：
2018 INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING, APPLICATIONS AND MANUFACTURING (ICIEAM) | 2018年
关键词：
wavelet transform; neural networks; SDR; signal distortion;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
This paper describes an algorithm for the automatic identification and classifying of signal distortions in the systems for testing radio receivers based on software-defined radio systems. The algorithm is based on the wavelet transform of a signal to isolate the distortion features simultaneously in the frequency and time domains as well as on the neural networks to automatically determine the presence of signal distortions and their classification.
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页数：4
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