Open AccessEMI signal feature enhancement based on extreme energy difference and deep auto‐encoder
Author(s) -
Li Hongyi,
Chen Shengyu,
Xu Shaofeng,
Song Ziming,
Chen Jiaxin,
Zhao Di
Publication year - 2018
Publication title -
iet signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.384
H-Index - 42
eISSN - 1751-9683
pISSN - 1751-9675
DOI - 10.1049/iet-spr.2017.0354
Subject(s) - emi , electromagnetic interference , feature (linguistics) , feature extraction , computer science , energy (signal processing) , signal (programming language) , interference (communication) , pattern recognition (psychology) , encoder , artificial intelligence , speech recognition , electronic engineering , engineering , mathematics , telecommunications , statistics , philosophy , linguistics , channel (broadcasting) , operating system , programming language
To enhance features of different electromagnetic interference (EMI) signals, which are significant for further feature extraction and pattern recognition, the authors propose an EMI signal feature enhancement method based on extreme energy difference and a deep auto‐encoder. Experimental results show that this method can effectively enhance features of EMI signals and improve recognition accuracy.