Radar Intra-Pulse Modulation Signal Recognition Using Multi-Branch Denoising Convolutional Neural Network and Inception- ResN et-v2-Reference-Cited by-同舟云学术

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Radar Intra-Pulse Modulation Signal Recognition Using Multi-Branch Denoising Convolutional Neural Network and Inception- ResN et-v2

Published:2024-05-17 Issue: Volume:44 Page:396-402
ISSN:
Container-title:2024 9th International Conference on Electronic Technology and Information Science (ICETIS)
language:
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Author:

Liao Yanping¹,Tian Nongkai¹

Affiliation:

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

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10592861/10593657/10593735.pdf?arnumber=10593735

Reference15 articles.

1. Radar emitter identification algorithm based on deep learning;Zhou;Journal of Xi dian University,2017

2. Low Probability of Intercept Radar Signal Recognition Based on Stacked Sparse Auto-encoder;Guo;Journal of Electronics & Information Technology,2018

3. Improved residual neural network algorithm for radar intra-pulse modulation classification;Xu;Journal of Jilin University,2021

4. Radar Signal Modulation Type Recognition Based on Denoising Convolutional Neural Network;Xiao;Journal of Electronics & Information Technology,2021

5. Automatic modulation classification of radar signals utilizing X-net

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