en 5-Signal Processing Signal Processing Research Paper Research Paper <span style="font-size:10.0pt"><span new="" roman="" style="font-family:" times="">Signal forecasting in the medical field has many applications, such as signal correction and anomaly detection. According to this application, robust forecasting is required to obtain a signal identical to the original signal. This study proposes a forecasting technique that obtains a robust signal that can be used in different applications. A long short-term memory neural network (LSTM-NN) was used to predict future samples from present and past samples. An Electroencephalography (EEG) dataset was used to test this technique. Four channels were used as input examples, one of which was the predicted output. All four channel samples were fed into the four networks to predict the future samples. To decrease complexity, only one hidden layer is used for this purpose. The statistical results are promising for applications that require an almost perfectly predicted signal. The number of hidden cells is first very low (five cells only), which gives a Root Mean Square Error of less than 20, whereas when the number of hidden cells is increased to 100, the Root Mean Square Error (RMSE) is approximately 7.5 for all four channels.</span></span> EEG signal, Robust Forecasting, LSTM, GRU, Deep Learning. 38 53 http://ijeee.iust.ac.ir/browse.php?a_code=A-10-5733-1&slc_lang=en&sid=1 Duaa A. Kareem doaa.abas@buog.edu.iq 1800319475328460017701 1800319475328460017701 No Polymers and Petrochemicals Engineering Department, College of Oil and Gas Engineering, Basrah University for Oil and Gas, Basrah, Iraq. Zaineb M. Alhakeem zainebalhakeem@buog.edu.iq 1800319475328460017702 1800319475328460017702 Yes Department of Chemical and Petroleum Refining Engineering, College of Oil and Gas Engineering, Basrah University for Oil and Gas, Basrah, Iraq. Nawar Hayder Tawfeeq nawar.hayder@buog.edu.iq 1800319475328460017703 1800319475328460017703 No Department of Oil and Gas Engineering, College of Oil and Gas Engineering, Basrah University for Oil and Gas, Basrah, Iraq. Batool Dahham Al-Ali batool.dahham@buog.edu.iq 1800319475328460017704 1800319475328460017704 No Department of Oil and Gas Engineering, College of Oil and Gas Engineering, Basrah University for Oil and Gas, Basrah, Iraq. Heba Hakim hiba.abdulzahrah@uobasrah.edu.iq 1800319475328460017705 1800319475328460017705 No Computer Engineering Department, College of Engineering, Basrah University of Basrah, Basrah, Iraq.