Signal and Information Processing, Networking and Computers
Proceedings of the 5th International Conference on Signal and Information Processing, Networking and Computers (ICSINC) Herausgegeben:Sun, Songlin; Fu, Meixia; Xu, Lexi
Signal and Information Processing, Networking and Computers
Proceedings of the 5th International Conference on Signal and Information Processing, Networking and Computers (ICSINC) Herausgegeben:Sun, Songlin; Fu, Meixia; Xu, Lexi
This proceedings book presents selected papers from the 5th Conference on Signal and Information Processing, Networking and Computers (ICSINC), held in Yuzhou, China, from November 29 to December 1, 2018. It focuses on the current research in a wide range of areas in the fields of information theory, communication systems, computer science, signal processing, aerospace technologies, and other related technologies. With contributions from experts from both academia and industry, it is a valuable resource for anyone who is interested in this field.
This proceedings book presents selected papers from the 5th Conference on Signal and Information Processing, Networking and Computers (ICSINC), held in Yuzhou, China, from November 29 to December 1, 2018. It focuses on the current research in a wide range of areas in the fields of information theory, communication systems, computer science, signal processing, aerospace technologies, and other related technologies. With contributions from experts from both academia and industry, it is a valuable resource for anyone who is interested in this field.
Prof. Songlin Sun received his Ph.D. degree in Communication and Information Systems from Beijing University of Posts and Telecommunications (BUPT), China in 2003. He is currently a Professor at the School of Information and Communication Engineering, BUPT. He also serves at the National Engineering Laboratory for Mobile Network Security and Key Laboratory of Trustworthy Distributed Computing and Service (BUPT) Ministry of Education. Prof. Songlin Sun is a senior member of IEEE, a professional member of ACM and a senior member of CCF. His research focuses on signal processing, wireless communications, and multimedia. He has published over 120 research papers, including more than 20 journal papers and 100 conference papers. He also serves on the Technical Program Committees (TPC) of numerous conferences. Ms. Meixia Fu received her bachelor degree in Qingdao University of Science and Technology, Qingdao, China in 2014. Her research interests include computer vision, humanaction recognition and big data mining. She has published several papers on journal and conference. She is an IEEE student member. Dr. Lexi Xu received his Ph.D. degree from School of Electronic Engineering and Computer Science, Queen Mary University of London, London, UK in 2013. Dr. Xu is currently a senior engineer at China Unicom Network Technology Research Institute, Beijing, China. He is also a senior researcher of National Engineering Laboratory for Next Generation Internet Broadband Service Application. Dr. Xu is a member of IEEE, and a China Unicom delegate in CCSA, ITU, ETSI. He has been involved in more than 30 big data research projects and network optimization projects. Dr. Xu has published more than 60 technical papers and he serves on the Technical Program Committees (TPC) of 8 international conferences. His research interests include big data, self-organizing networks, and radio resource management in LTE-A/5G.
Inhaltsangabe
Big Data Analytics.- Compressed Sensing.- Information Theory & Statistics.- Quantum Information & Coding Theory.- Spectrum Estimation & Modeling.- Spectrum Shaping & Filters.- Signal Detection and Synchronization.- Signal Processing in Networked Systems.- Pattern Recognition & Learning.- AI & Neural Networks.- Machine Learning.
Big Data Analytics.- Compressed Sensing.- Information Theory & Statistics.- Quantum Information & Coding Theory.- Spectrum Estimation & Modeling.- Spectrum Shaping & Filters.- Signal Detection and Synchronization.- Signal Processing in Networked Systems.- Pattern Recognition & Learning.- AI & Neural Networks.- Machine Learning.
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