Electromagnetic Signal Classification Based on Class Exemplar Selection and Multi-Objective Linear Programming

In the increasingly complex electromagnetic environment, a variety of new signal types are appearing; however, existing electromagnetic signal classification (ESC) models cannot handle new signal types. In this context, the emergence of class-incremental learning aims to incrementally update the cla...

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Veröffentlicht in:	Remote sensing (Basel, Switzerland) Jg. 14; H. 5; S. 1177
Hauptverfasser:	Zhou, Huaji, Bai, Jing, Niu, Linchun, Xu, Jie, Xiao, Zhu, Zheng, Shilian, Jiao, Licheng, Yang, Xiaoniu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 01.03.2022
Schlagworte:	Algorithms Bias Categories class exemplar selection class incremental learning Classification Classifiers data collection Datasets Deep learning Distillation electromagnetic signal classification Entropy Linear programming multi-objective linear programming Multiple objective analysis Neural networks normalized mutual information Radiation Radio equipment Receivers & amplifiers Remote sensing Signal classification Signal processing Teaching methods
ISSN:	2072-4292, 2072-4292
Online-Zugang:	Volltext
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