Few-Shot Specific Emitter Identification Using Asymmetric Masked Auto-Encoder-Reference-Cited by-同舟云学术

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Few-Shot Specific Emitter Identification Using Asymmetric Masked Auto-Encoder

Published:2023-10 Issue:10 Volume:27 Page:2657-2661
ISSN:1089-7798
Container-title:IEEE Communications Letters
language:
Short-container-title:IEEE Commun. Lett.

Author:

Yao Zhisheng¹,Fu Xue¹^ORCID,Guo Lantu²,Wang Yu¹^ORCID,Lin Yun³^ORCID,Shi Shengnan¹^ORCID,Gui Guan¹^ORCID

Affiliation:

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

2. School of Information and Electronics, Beijing Institute of Technology, Beijing, China

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

Funder

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

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Modeling and Simulation

Link

http://xplorestaging.ieee.org/ielx7/4234/10275739/10243409.pdf?arnumber=10243409

Reference27 articles.

1. Few-Shot Learning for Radar Emitter Signal Recognition Based on Improved Prototypical Network

2. Specific Emitter Identification with Limited Samples: A Model-Agnostic Meta-Learning Approach

3. Unsupervised Radio Frequency Fingerprint Identification Based on Curriculum Learning

4. Radio Frequency Signal Identification Using Transfer Learning Based on LSTM

5. Towards Scalable and Channel-Robust Radio Frequency Fingerprint Identification for LoRa

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