Machine Learning, Deep Learning and Computational Intelligence for Wireless Communication : Proceedings of MDCWC 2020 /

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, Nati...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Gopi, E. S. (Editor)
Format: eBook
Language:English
Published: Singapore : Springer Singapore : Imprint: Springer, 2021.
Edition:1st ed. 2021.
Series:Lecture Notes in Electrical Engineering, 749
Subjects:
Online Access:Connect to the full text of this electronic book
Description
Summary: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, 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.
Physical Description:1 online resource (XIX, 643 pages 387 illustrations, 304 illustrations in color.)
ISBN:9789811602894
ISSN:1876-1119 ;
DOI:10.1007/978-981-16-0289-4