[1] O'SHEA T J, ROY T, CLANCY T C. Over-the-air deep learning based radio signal classification[J]. IEEE Journal of Selected Topics in Signal Processing, 2018,12(1):168-179.
[2] O'SHEA T, HOYDIS J. An introduction to deep learning for the physical layer[J]. IEEE Transactions on Cognitive Communications and Networking, 2017,3(4):563-575.
[3] LIN Y,TU Y,DOU Z,et al. The application of deep learning in communication signal modulation recognition[C]// 2017 IEEE/CIC International Conference on Communications in China(ICCC). Qingdao,China:IEEE, 2017:1-5.
[7] TU Y, LIN Y, WANG J, et al. Semi-supervised learning with generative adversarial networks on digital signal modulation classification[J]. Computers, Materials & Continua, 2018,55(2):243-254.
[9] SZEGEDY C,ZAREMBA W,SUTSKEVR I,et al. Intriguing properties of neural networks[C]// 2nd International Conference on Learning Representations. Banff,Canada:[s.n.], 2012:1-10.
[10] LIN Y,ZHAO H,TU Y,et al. Threats of adversarial attacks in DNN-based modulation recognition[C]// 2020 IEEE Conference on Computer Communications. Toronto,ON,Canada:IEEE, 2020:2469-2478.
[11] MADRY A, MAKELOV A, SCHMIDT L, et al. Towards deep learning models resistant to adversarial attacks[C]// The 6th International Conference on Learning Representations. Vancouver,Canada:[s.n.], 2016:1-23.
[12] KURAKIN A,GOODFELLOW I,BENGIO S. Adversarial examples in the physical world[C]// The 6th International Conference on Learning Representations. Vancouver,Canada:[s.n.], 2016:128-141.
[13] GOODFELLOW I J, SHLENS J, SZEGEDY C. Explaining and harnessing adversarial examples[C]// The 5th International Conference on Learning Representations. San Diego,CA,USA:2015:1-11.
[14] YUAN X, HE P, ZHU Q, et al. Adversarial examples: attacks and defenses for deep learning[J]. IEEE Transactions on Neural Networks and Learning Systems, 2019,30(9):2805-2824.
[15] O'SHEA T, WEST N. Radio machine learning dataset generation with GNU radio[J]. Proceedings for the 6th GNU Radio Conference, 2016,1(1):1-6.
[16] DeepSig. Deepsig dataset:radioml 2016[EB/OL]. [2020-12-10]. https://www.deepsig.io/datasets.