Semi-Supervised Specific Emitter Identification Based on Bispectrum Feature Extraction CGAN in Multiple Communication Scenarios
Author:
Affiliation:
1. Department of Information Fusion, Naval Aviation University, Yantai, China
Funder
National Natural Science Foundation of China
Taishan Scholars Project of Shandong Province
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Aerospace Engineering
Link
http://xplorestaging.ieee.org/ielx7/7/10041225/09801648.pdf?arnumber=9801648
Reference46 articles.
1. Specific Emitter Identification Based on Deep Residual Networks
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4. Generative adversarial networks;goodfellow;Adv Neural Inf Process Syst,2014
5. Specific Emitter Identification Based on Variational Mode Decomposition and Spectral Features in Single Hop and Relaying Scenarios
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