@inproceedings{4d642452c62047a9ba795edc48e8a696,
title = "Spectrum Prediction Method Based on EMD and ELM in HFSWR",
abstract = "High frequency surface wave radar (HFSWR) works in shortwave bands with complex electronmagnetic environment, so it is difficult to find a optimal frequency for the next working cycle. Frequency monitoring system (FMS) is introduced into the new system radar to provide the optimal frequency real-time. This paper proposes a spectrum prediction method based on Empirical mode decomposition (EMD) and Extreme learning machine (ELM) to find the optimal frequency in FMS. The simulation result shows that the method predicts spectrum more effective than traditional method and it provides a good method to select the optimal frequency in HFSWR.",
keywords = "Empirical mode decomposition, Extreme learning machine, high frequency surface wave radar, spectrum prediction",
author = "Hongzhi Li and Changjun Yu and Bin Zhao",
note = "Publisher Copyright: {\textcopyright} 2018 KIEES.; 2018 International Symposium on Antennas and Propagation, ISAP 2018 ; Conference date: 23-10-2018 Through 26-10-2018",
year = "2018",
month = jul,
day = "2",
language = "英语",
series = "ISAP 2018 - 2018 International Symposium on Antennas and Propagation",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "ISAP 2018 - 2018 International Symposium on Antennas and Propagation",
address = "美国",
}