Introduction to the Issue on Machine Learning for Cognition in Radio Communications and Radar

S. Kokalj-Filipovic; M. S. Greco; H. V. Poor; G. Stantchev; L. Xiao

doi:10.1109/JSTSP.2018.2796338

Introduction to the Issue on Machine Learning for Cognition in Radio Communications and Radar

S. Kokalj-Filipovic, M. S. Greco, H. V. Poor, G. Stantchev, L. Xiao

Research output: Contribution to journal › Editorial › peer-review

Original language	English (US)
Pages (from-to)	3-5
Number of pages	3
Journal	IEEE Journal on Selected Topics in Signal Processing
Volume	12
Issue number	1
DOIs	https://doi.org/10.1109/JSTSP.2018.2796338
State	Published - Feb 2018
Externally published	Yes

All Science Journal Classification (ASJC) codes

Signal Processing
Electrical and Electronic Engineering

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10.1109/JSTSP.2018.2796338

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title = "Introduction to the Issue on Machine Learning for Cognition in Radio Communications and Radar",

author = "S. Kokalj-Filipovic and Greco, {M. S.} and Poor, {H. V.} and G. Stantchev and L. Xiao",

note = "Funding Information: George Stantchev received the Ph.D. degree in Applied Mathematics and Scientific Computing from the University of Maryland at College Park, College Park, MD, USA, in 2003. He is a Computational Scientist with the Naval Research Laboratory, Washington, DC, USA. Prior to joining NRL, he was a Postdoctoral Researcher with the Center for Scientific Computation and Mathematical Modeling, University of Maryland at College Park. He has been actively involved in interdisciplinary research on a variety of topics ranging from electromagnetic modeling and simulation to nonlinear system identification and machine learning in the RF signal domain. Recently, he was a coorganizer of the Symposium on Machine Learning for Cognitive Communication Networks and Radar at the 2016 IEEE GlobalSIP Conference in Washington, DC, USA. He was the recipient of the 2017 Alan Berman Research Publication Award from the U.S. Department of the Navy. Funding Information: H. Vincent Poor (LF{\textquoteright}17) is the Michael Henry Strater University Professor of Electrical Engineering at Princeton University, Princeton, NJ, USA. His research interests include information theory and signal processing, and their applications in wireless communications and related fields. He is a member of the National Academy of Engineering and the National Academy of Sciences, and a foreign member of the Chinese Academy of Sciences, the Royal Society, and other national and international academies. Recent recognition of his work includes the 2017 IEEE Alexander Graham Bell Medal, and a D.Sc. honoris causa from Syracuse University, conferred in 2017.",

year = "2018",

month = feb,

doi = "10.1109/JSTSP.2018.2796338",

language = "English (US)",

volume = "12",

pages = "3--5",

journal = "IEEE Journal on Selected Topics in Signal Processing",

issn = "1932-4553",

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number = "1",

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T1 - Introduction to the Issue on Machine Learning for Cognition in Radio Communications and Radar

AU - Kokalj-Filipovic, S.

AU - Greco, M. S.

AU - Poor, H. V.

AU - Stantchev, G.

AU - Xiao, L.

N1 - Funding Information: George Stantchev received the Ph.D. degree in Applied Mathematics and Scientific Computing from the University of Maryland at College Park, College Park, MD, USA, in 2003. He is a Computational Scientist with the Naval Research Laboratory, Washington, DC, USA. Prior to joining NRL, he was a Postdoctoral Researcher with the Center for Scientific Computation and Mathematical Modeling, University of Maryland at College Park. He has been actively involved in interdisciplinary research on a variety of topics ranging from electromagnetic modeling and simulation to nonlinear system identification and machine learning in the RF signal domain. Recently, he was a coorganizer of the Symposium on Machine Learning for Cognitive Communication Networks and Radar at the 2016 IEEE GlobalSIP Conference in Washington, DC, USA. He was the recipient of the 2017 Alan Berman Research Publication Award from the U.S. Department of the Navy. Funding Information: H. Vincent Poor (LF’17) is the Michael Henry Strater University Professor of Electrical Engineering at Princeton University, Princeton, NJ, USA. His research interests include information theory and signal processing, and their applications in wireless communications and related fields. He is a member of the National Academy of Engineering and the National Academy of Sciences, and a foreign member of the Chinese Academy of Sciences, the Royal Society, and other national and international academies. Recent recognition of his work includes the 2017 IEEE Alexander Graham Bell Medal, and a D.Sc. honoris causa from Syracuse University, conferred in 2017.

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Introduction to the Issue on Machine Learning for Cognition in Radio Communications and Radar

All Science Journal Classification (ASJC) codes

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