Signal and Information Processing, Networking and Computers (eBook, PDF)

Proceedings of the 4th International Conference on Signal and Information Processing, Networking and Computers (ICSINC)
Redaktion: Sun, Songlin

• Format: PDF

Produktbeschreibung

This proceedings book presents selected papers from the 4th Conference on Signal and Information Processing, Networking and Computers (ICSINC) held in Qingdao, China on May 23-25, 2018. It focuses on the current research in a wide range of areas related to 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 anyone interested in this field.

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Produktdetails

• Verlag: Springer Nature Singapore
• Seitenzahl: 308
• Erscheinungstermin: 3. November 2018
• Englisch
• ISBN-13: 9789811317330
• Artikelnr.: 54520404

Autorenporträt

Prof. Songlin Sun received his Ph.D. degree in Communication and Information Systems from Beijing University of Posts and Telecommunications (BUPT), Beijing, 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 20+ journal papers and 100+ conference papers. He also serves on the Technical Program Committees (TPC) of numerous conferences.

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.