A. K. Nandi and E. E. Azzouz, "Automatic analogue modulation recognition," Signal processing, vol. 46, no. 2, pp. 211-222, 1995.
 Z. Zhu and A. K. Nandi, Automatic modulation classification: principles, algorithms and applications. John Wiley & Sons, 2015.
 N. Ghani and R. Lamontagne, "Neural networks applied to the classification of spectral features for automatic modulation recognition," in Proceedings of MILCOM'93-IEEE Military Communications Conference, 1993, vol. 1, pp. 111-115: IEEE.
 M. D. Wong and A. K. Nandi, "Automatic digital modulation recognition using spectral and statistical features with multi-layer perceptrons," in Proceedings of the sixth international symposium on signal processing and its applications (Cat. No. 01EX467), 2001, vol. 2, pp. 390-393: IEEE.
 G. Arulampalam, V. Ramakonar, A. Bouzerdoum, and D. Habibi, "Classification of digital modulation schemes using neural networks," in ISSPA'99. Proceedings of the Fifth International Symposium on Signal Processing and its Applications (IEEE Cat. No. 99EX359), 1999, vol. 2, pp. 649-652: IEEE.
 I. A. H. El Rube and N. E.-d. El-Madany, "Cognitive digital modulation classifier using artificial neural networks for NGNs," in 2010 Seventh International Conference on Wireless and Optical Communications Networks-(WOCN), 2010, pp. 1-5: IEEE.
 O. A. Dobre, A. Abdi, Y. Bar-Ness, and W. Su, "Survey of automatic modulation classification techniques: classical approaches and new trends," IET communications, vol. 1, no. 2, pp. 137-156, 2007.
 S. Peng et al., "Modulation classification based on signal constellation diagrams and deep learning," IEEE transactions on neural networks and learning systems, vol. 30, no. 3, pp. 718-727, 2018.
 A. E. El-Mahdy and N. M. Namazi, "Classification of multiple M-ary frequency-shift keying signals over a Rayleigh fading channel," IEEE Transactions on Communications, vol. 50, no. 6, pp. 967-974, 2002.
 F. Hameed, O. A. Dobre, and D. C. Popescu, "On the likelihood-based approach to modulation classification," IEEE Transactions on Wireless Communications, vol. 8, no. 12, pp. 5884-5892, 2009.
 A. K. Nandi and E. E. Azzouz, "Algorithms for automatic modulation recognition of communication signals," IEEE Transactions on communications, vol. 46, no. 4, pp. 431-436, 1998.
 Z.-L. Tang, S.-M. Li, and L.-J. Yu, "Implementation of deep learning-based automatic modulation classifier on FPGA SDR platform," Electronics, vol. 7, no. 7, p. 122, 2018.
 E. E. Azzouz and A. K. Nandi, "Modulation recognition using artificial neural networks," in Automatic Modulation Recognition of Communication Signals: Springer, 1996, pp. 132-176.
 Z. Wu, X. Wang, Z. Gao, and G. Ren, "Automatic digital modulation recognition based on support vector machines," in 2005 International Conference on Neural Networks and Brain, 2005, vol. 2, pp. 1025-1028: IEEE.
 M. W. Aslam, Z. Zhu, and A. K. Nandi, "Automatic modulation classification using combination of genetic programming and KNN," IEEE Transactions on wireless communications, vol. 11, no. 8, pp. 2742-2750, 2012.
 X. Lin, R. Liu, W. Hu, Y. Li, X. Zhou, and X. He, "A deep convolutional network demodulator for mixed signals with different modulation types," in 2017 IEEE 15th Intl Conf on Dependable, Autonomic and Secure Computing, 15th Intl Conf on Pervasive Intelligence and Computing, 3rd Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress (DASC/PiCom/DataCom/CyberSciTech), 2017, pp. 893-896: IEEE.
 T. J. O’Shea, J. Corgan, and T. C. Clancy, "Convolutional radio modulation recognition networks," in International conference on engineering applications of neural networks, 2016, pp. 213-226: Springer.
 A. P. Hermawan, R. R. Ginanjar, D.-S. Kim, and J.-M. Lee, "Cnn-based automatic modulation classification for beyond 5g communications," IEEE Communications Letters, vol. 24, no. 5, pp. 1038-1041, 2020.
 S. Rajendran, W. Meert, D. Giustiniano, V. Lenders, and S. Pollin, "Deep learning models for wireless signal classification with distributed low-cost spectrum sensors," IEEE Transactions on Cognitive Communications and Networking, vol. 4, no. 3, pp. 433-445, 2018.
 M. Alameh, Y. Abbass, A. Ibrahim, G. Moser, and M. Valle, "Touch Modality Classification Using Recurrent Neural Networks," IEEE Sensors Journal, 2021.
 X. Liu, D. Yang, and A. El Gamal, "Deep neural network architectures for modulation classification," in 2017 51st Asilomar Conference on Signals, Systems, and Computers, 2017, pp. 915-919: IEEE.
 R. Zhou, F. Liu, and C. W. Gravelle, "Deep learning for modulation recognition: a survey with a demonstration," IEEE Access, vol. 8, pp. 67366-67376, 2020.
 R. M. Al‐Makhlasawy, A. A. Hefnawy, M. M. Abd Elnaby, and F. E. Abd El‐Samie, "Modulation classification in the presence of adjacent channel interference using convolutional neural networks," International Journal of Communication Systems, vol. 33, no. 13, p. e4295, 2020.
 A. Shrestha and A. Mahmood, "Review of deep learning algorithms and architectures," IEEE Access, vol. 7, pp. 53040-53065, 2019.
 I. Goodfellow, Y. Bengio, and A. Courville, Deep learning. MIT press, 2016.
 G. Huang, Z. Liu, L. Van Der Maaten, and K. Q. Weinberger, "Densely connected convolutional networks," in Proceedings of the IEEE conference on computer vision and pattern recognition, 2017, pp. 4700-4708.
 C. Szegedy et al., "Going deeper with convolutions," in Proceedings of the IEEE conference on computer vision and pattern recognition, 2015, pp. 1-9.
 T. N. Sainath, O. Vinyals, A. Senior, and H. Sak, "Convolutional, long short-term memory, fully connected deep neural networks," in 2015 IEEE international conference on acoustics, speech and signal processing (ICASSP), 2015, pp. 4580-4584: IEEE.
 T. J. O'shea and N. West, "Radio machine learning dataset generation with gnu radio," in Proceedings of the GNU Radio Conference, 2016, vol. 1, no. 1.
 N. E. West and T. O'Shea, "Deep architectures for modulation recognition," in 2017 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN), 2017, pp. 1-6: IEEE.
 T. J. O’Shea, T. Roy, and T. C. Clancy, "Over-the-air deep learning based radio signal classification," IEEE Journal of Selected Topics in Signal Processing, vol. 12, no. 1, pp. 168-179, 2018.
 M. Sadeghi and E. G. Larsson, "Adversarial attacks on deep-learning based radio signal classification," IEEE Wireless Communications Letters, vol. 8, no. 1, pp. 213-216, 2018.
 Y. Zeng, M. Zhang, F. Han, Y. Gong, and J. Zhang, "Spectrum analysis and convolutional neural network for automatic modulation recognition," IEEE Wireless Communications Letters, vol. 8, no. 3, pp. 929-932, 2019.
 S. Hu, Y. Pei, P. P. Liang, and Y.-C. Liang, "Deep neural network for robust modulation classification under uncertain noise conditions," IEEE Transactions on Vehicular Technology, vol. 69, no. 1, pp. 564-577, 2019.
 W. Lee, M. Kim, and D.-H. Cho, "Deep power control: Transmit power control scheme based on convolutional neural network," IEEE Communications Letters, vol. 22, no. 6, pp. 1276-1279, 2018.