Enhancing the generalization ability of deep learning model for radio signal modulation recognition
Author:
Funder
the University-Enterprise Cooperation Projects
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
https://link.springer.com/content/pdf/10.1007/s10489-022-04374-7.pdf
Reference42 articles.
1. Dobre OA, Abdi A, Bar-Ness YWS (2007) Survey of automatic modulation classification techniques: Classical approaches and new trends. IET Commun 1(2):137–156
2. Jeong S, Lee U, Kim SC (2018) Spectrogram-based automatic modulation recognition using convolutional neural network. In: 2018 tenth international conference on ubiquitous and future networks (ICUFN). IEEE, pp 843–845
3. Nandi AK, Azzouz EE (1998) Algorithms for automatic modulation recognition of communication signals. IEEE Trans Commun 46(4):431–436
4. Qi P, Zhou X, Zheng S, Li Z (2020) Automatic modulation classification based on deep residual networks with multimodal information. IEEE Trans Cognitive Commun Netw 7(1):21– 33
5. Zhang M, Zeng Y, Han Z, Gong Y (2018) Automatic modulation recognition using deep learning architectures. In: 2018 IEEE 19th international workshop on signal processing advances in wireless communications (SPAWC). IEEE, pp 1–5
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