HWU-ISSS & UoE-IDCOM seminars: Iterative Algorithms for Recovery in Compressed Sensing and Applications in Communications Engineering

Sep16Tue

HWU-ISSS & UoE-IDCOM seminars: Iterative Algorithms for Recovery in Compressed Sensing and Applications in Communications Engineering

Tue, 16/09/2014 - 13:00
Speaker: 
Prof Norbert Goertz
Affiliation: 
Institute of Telecommunications of the Vienna University of Technology, Austria.
Synopsis: 

Iterative algorithms are very efficient methods to recover structured signal vectors in n dimensions from m

Biography: 

Norbert Goertz received the Dipl.-Ing. degree in Electrical Engineering from the Ruhr-University of Bochum, Germany, in 1993 and the Dr.-Ing.degree from Christian-Albrechts University, Kiel, Germany, in 1999 for research work on coded speech transmission over noisy channels. In 2004 he received the Habilitation degree from Munich University of Technology, Germany, with a thesis on joint source-channel coding. From 1999 until 2000 he was a postdoctoral researcher at the Institute of Network and Systems Theory of the Christian-Albrechts University Kiel, Germany. After that he was a postdoctoral researcher at the Munich University of Technology, Institute for Communications Engineering until2004. After a 3-months research visit of the IT department at Lund University, Sweden, and a temporary C4 professorship at the University of Kassel, Germany, he went to Scotland in October 2004 where he was a Lecturer and a Senior Lecturer at the Institute for Digital Communications in the School Engineering of The University of Edinburgh. Since September 2008 he has been a full professor for Multimedia Signal Processing at the Institute of Telecommunications of the Vienna University of Technology, Austria .His research interests include Source coding of multimedia signals; Channel coding, LDPC codes in particular; Adaptive modulation; Cross-layer design and scheduling; Multiuser information theory; Source-and channel codes for user cooperation and relaying; Sparse representations and compressed sensing with applications in signal
processing and communications.

Institute:

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