Robust Training of Artificial Feedforward Neural Networks. - Moumen T. El-Melegy; Mohamed H. Essai; Ali A. Amer (Foundations of Computational Intelligence (1), 2009)

Deep learning-based pilot-assisted channel state estimator for OFDM systems. - Mohamed Hassan Essai Ali (IET Commun., 2021)

Channel state information estimation for 5G wireless communication systems: recurrent neural networks approach. - Mohamed Hassan Essai Ali; Ibrahim B. M. Taha (PeerJ Comput. Sci., 2021)

Developing Novel Activation Functions Based Deep Learning LSTM for Classification. - Mohamed Hassan Essai Ali; Adel B. Abdel-Raman; Eman A. Badry (IEEE Access, 2022)

Deep Learning Gated Recurrent Neural Network-Based Channel State Estimator for OFDM Wireless Communication Systems. - Mohamed Hassan Essai Ali; M. Lotfy Rabeh; Sherif Hekal; Abeer N. Abbas (IEEE Access, 2022)

A promising Ka band leaky-wave antenna based on a periodic structure of non-identical irregularities. - Mohamed N. Shaaban; Mohamed Hassan Essai Ali; M. S. Yasseen; Aydar R. Nasybullin; Yuri E. Sedelnikov (EURASIP J. Wirel. Commun. Netw., 2022)

Developing Novel Robust Loss Functions-Based Classification Layers for DLLSTM Neural Networks. - Mohamad Abou Houran; Mohamed Hassan Essai Ali; Adel B. Abdel-Raman; Eman A. Badry; Alaaeldien Hassan; Hany A. Atallah (IEEE Access, 2023)

Automatic Modulation Classification: Convolutional Deep Learning Neural Networks Approaches. - Hany S. Hussein; Mohamed Hassan Essai Ali; Mohamed A. Ismeil; Mohamed N. Shaaban; Mona Lotfy Mohamed; Hany A. Atallah (IEEE Access, 2023)

Modified state activation functions of deep learning-based SC-FDMA channel equalization system. - Mohamed A. Mohamed; Hassan A. Hassan; Mohamed H. Essai; Hamada Esmaiel; Ahmed S. Mubarak; Osama A. Omer (EURASIP J. Wirel. Commun. Netw., 2023)

An efficient deep neural network channel state estimator for OFDM wireless systems. - Hassan A. Hassan; Mohamed A. Mohamed; Mohamed N. Shaaban; Mohamed Hassan Essai Ali; Osama A. Omer (Wirel. Networks, 2024)