Semi-Supervised Specific Emitter Identification Method Using Metric-Adversarial Training-Reference-Cited by-同舟云学术

Semi-Supervised Specific Emitter Identification Method Using Metric-Adversarial Training

Author:

Fu Xue¹^ORCID,Peng Yang¹^ORCID,Liu Yuchao²,Lin Yun³^ORCID,Gui Guan¹^ORCID,Gacanin Haris⁴^ORCID,Adachi Fumiyuki⁵^ORCID

Affiliation:

1. College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China

2. School of Electronic and Information Engineering, Beihang University, Beijing, China

3. College of Information and Communication Engineering, Harbin Engineering University, Harbin, China

4. Institute for Communication Technologies and Embedded Systems, RWTH Aachen University, Aachen, Germany

5. International Research Institute of Disaster Science, Tohoku University, Sendai, Japan

Funder

Key Project of Natural Science Foundation of the Higher Education Institutions of Jiangsu Province

Jiangsu Provincial Key Research and Development Program

Foundation of Nanjing Vocational College of Information Technology

Postgraduate Graduate Research and Practice Innovation Programs 2020

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Link

Reference60 articles.

2. Automatic differentiation in PyTorch;paszke;Proc Conf Neural Inf Process Syst (NeurIPS),2017

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