Machine Learning, Deep Learning and Computational Intelligence for Wireless Communication

Dr. E.S. Gopi has authored eight books, of which seven have been published by Springer. He has also contributed 9 book chapters to books published by Springer. He has several papers in international journals and conferences to his credit. He has 20 years of teaching and research experience. He is the coordinator for the pattern recognition and the computational intelligence laboratory. He is currently Associate Professor, Department of Electronics and Communication Engineering, National Institute of Technology, Tiruchirappalli, India. His books are widely used all over the world. His research interests include machine intelligence, pattern recognition, signal processing and computational intelligence. He is the series editor for the series “Signals and Communication Technology”, Springer publication. The India International Friendship Society (IFS) has awarded him the “Shiksha Rattan Puraskar Award” for his meritorious services in the field of education. The award was presented byDr. Bhishma Narain Singh, Former Governor, Assam and Tamil Nadu, India. He is also awarded with the "Glory of India Gold Medal" by International Institute of Success Awareness. This award was presented by Shri Syed Sibtey Razi, Former Governor of Jharkhand, India. He was also awarded with "Best Citizens of India 2013" by The International Publishing House.

• Deep Learning to Predict the Number of Antennas in a Massive MIMO Setup based on Channel Characteristics.- Optimal Design of Fractional Order PID Controller for AVR System using Black Widow Optimization (BWO) Algorithm.- LSTM Network for Hotspot Prediction in Traffic Density of Cellular Network.- Generative Adversarial Network and Reinforcement Learning to Estimate Channel Coefficients.- Self-Interference Cancellation in Full-duplex Radios for 5G Wireless Technology using Neural Network.- Dimensionality Reduction of KDD-99 using Self-perpetuating Algorithm.- Energy Efficient Neigbour Discovery using Bacterial Foraging Optimization (BFO) Technique for Asynchronous Wireless Sensor Networks.- LSTM based Outlier Detection Method for WSNs.- An Improved Swarm Optimization Algorithm based Harmonics Estimation and Optimal Switching Angle Identification.- A Study of Ensemble Methods for Classification.