Efficient Open-Set Recognition for Interference Signals Based on Convolutional Prototype Learning

Efficient Open-Set Recognition for Interference Signals Based on Convolutional Prototype Learning

Interference classification plays an important role in anti-jamming communication. Although the existing interference signal recognition methods based on deep learning have a higher accuracy than traditional methods, these have poor robustness while rejecting interference signals of unknown classes...

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Bibliographic Details
Main Authors: Xiangwei Chen, Zhijin Zhao, Xueyi Ye, Shilian Zheng, Caiyi Lou, Xiaoniu Yang
Format: Article
Language:English
Published: MDPI AG 2022-04-01
Series:Applied Sciences
Subjects:
open-set recognition
interference signal
prototype learning
convolutional neural network
attention
Online Access:https://www.mdpi.com/2076-3417/12/9/4380

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