Del 749 - Lecture Notes in Electrical Engineering

Machine Learning, Deep Learning and Computational Intelligence for Wireless Communication

Proceedings of MDCWC 2020

Häftad, Engelska, 2022

Av E. S. Gopi

3 229 kr

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This book is a collection of best selected research papers presented at the Conference on Machine Learning, Deep Learning and Computational Intelligence for Wireless Communication (MDCWC 2020) held during October 22nd to 24th 2020, at the Department of Electronics and Communication Engineering, National Institute of Technology Tiruchirappalli, India. The presented papers are grouped under the following topics (a) Machine Learning, Deep learning and Computational intelligence algorithms (b)Wireless communication systems and (c) Mobile data applications and are included in the book. The topics include the latest research and results in the areas of network prediction, traffic classification, call detail record mining, mobile health care, mobile pattern recognition, natural language processing, automatic speech processing, mobility analysis, indoor localization, wireless sensor networks (WSN), energy minimization, routing, scheduling, resource allocation, multiple access, powercontrol, malware detection, cyber security, flooding attacks detection, mobile apps sniffing, MIMO detection, signal detection in MIMO-OFDM, modulation recognition, channel estimation, MIMO nonlinear equalization, super-resolution channel and direction-of-arrival estimation. The book is a rich reference material for academia and industry.

Produktinformation

Utgivningsdatum2022-05-30
Mått155 x 235 x undefined mm
FormatHäftad
SpråkEngelska
SerieLecture Notes in Electrical Engineering
Antal sidor643
FörlagSpringer Verlag, Singapore
ISBN9789811602917

Tillhör följande kategorier

Systemvetenskap och AI inom Data och it
Hårdvara inom Data och it
Elektronik och kommunikationer inom Naturvetenskap och teknik

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.