Radio–Image Transformer: Bridging Radio Modulation Classification and ImageNet Classification

Radio–Image Transformer: Bridging Radio Modulation Classification and ImageNet Classification

Radio modulation classification is widely used in the field of wireless communication. In this paper, in order to realize radio modulation classification with the help of the existing ImageNet classification models, we propose a radio–image transformer which extracts the instantaneous amplitude, ins...

Full description

Bibliographic Details
Main Authors: Shichuan Chen, Kunfeng Qiu, Shilian Zheng, Qi Xuan, Xiaoniu Yang
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Electronics
Subjects:
modulation classification
deep learning
ImageNet
convolutional neural network
Online Access:https://www.mdpi.com/2079-9292/9/10/1646

Internet

https://www.mdpi.com/2079-9292/9/10/1646

Similar Items