Proceedings of the International Conference on Machine Learning, Deep Learning and Computational Intelligence for Wireless Communication: MDCWC 2023 (Signals and Communication Technology) - Tapa dura

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Dr. E. S. Gopi has solely authored 9 books and edited 1 book in the area of signal processing and pattern recognition. He has got several research papers published in the reputed journals, reviewed book chapters and conference proceedings. He has 25 years of teaching and research experience. He is the coordinator for pattern recognition and the computational intelligence laboratory. He is currently a Professor, Department of Electronics and Communication Engineering, National Institute of Technology, Trichy (Government of India). His books are widely used all over the world. His book on “Pattern recognition and Computational intelligence using Matlab”, Springer, was recognized as one of the best eBooks under the “pattern recognition” and “Matlab” categories by the Book authority, Authorities’ leading site for book recommendations by thought leaders. He is the series editor for the series “Signals and Communication Technology”, a Springer publication. He has completedthe project offered by GTRE (DRDO) as the principal investigator on “Hunting representative sensors and constructing regression model for between sensor outcomes using ML”. His video course on “Pattern recognition”, “Statistical theory of Communication” and “Linear algebra and stochastic process” are well appreciated by his fellow students. He is also serving as one of the Workshops, Tutorials & Symposia officers for Machine Learning For Communications Emerging Technologies Initiative (IEEE ComSoc). He organized the first virtual international conference (MDCWC2020) at NIT, Tiruchirappalli and edited the proceedings published by Springer. He has organized many workshops, which include MDCWC2021 as the special session during the IEEE Conference on ICIAfS2021, MDCWC2022, the first long virtual workshop at NIT, Tiruchirappalli. Recently, the second International conference on MDCWC2023 was organized by him. He was the convener for the conference. He has delivered many invited talks, whichinclude the talk under the Global Initiative of Academic Networks (GIAN) course on “Machine learning for wireless communication” and Speaker for the IEEE Training school in Machine learning for wireless communication, TOMSK Polytechnic University. His research interests include Machine intelligence, pattern recognition, Statistical signal processing and Computational intelligence.

Dr. P. Maheswaran obtained his PhD from IIITDM Kancheepuram in the area of wireless communication. At present, he is serving as an Assistant Professor in the Dept. of ECE, National Institute of Technology, Tiruchirappalli. Between 2011 and 2013, he was with Tata Consultancy Services as a Systems Engineer. He briefly served as an Assistant Professor in the Dept. of ECE, SRM Institute of Science and Technology, Chennai from 2017 to 2018. From 2019 to 2020, he was with IIT Madras as a postdoctoral fellow. His research areas include wireless communication, signal processing, cooperative communication, MIMO communication system, index modulation, spatial modulation, and OTFS.

De la contraportada

This book is a collection of best selected research papers presented at the 2nd Conference on Machine Learning, Deep Learning and Computational Intelligence for Wireless Communication (MDCWC 2023) held during June 22-24th, 2023, at the 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. 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, power control, 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.