IAFNet: Few-Shot Learning for Modulation Recognition in Underwater Impulsive Noise
Author:
Affiliation:
1. School of Information Systems Engineering, Strategic Support Force Information Engineering University, Zhengzhou, China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Science Applications,Modeling and Simulation
Link
http://xplorestaging.ieee.org/ielx7/4234/9771287/09714286.pdf?arnumber=9714286
Reference12 articles.
1. Modulation Recognition of Underwater Acoustic Communication Signals Based on Data Transfer
2. Impulsive Noise Mitigation in Underwater Acoustic Communication Systems: Experimental Studies
3. Intelligent Denoising-Aided Deep Learning Modulation Recognition With Cyclic Spectrum Features for Higher Accuracy
4. Deep Modulation Recognition in an Unknown Environment
5. Learning to Compare: Relation Network for Few-Shot Learning
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3. SSL-LRN: A Lightweight Semi-Supervised-Learning-Based Approach for UWA Modulation Recognition;Journal of Marine Science and Engineering;2024-08-04
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5. A Few-Shot Modulation Recognition Method Based on Multi-Modal Feature Fusion;IEEE Transactions on Vehicular Technology;2024-07
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