Polynomial matrices – a brief overview

Dr. Stephan Alexander Weiss | 25.04.2016 | 11:00 Uhr | B04, L4101

Abstract

Polynomial matrices can help to elegantly formulate many broadband multi-sensor / multi-channel processing problems, and represent a direct extension of well-established narrowband techniques which typically involve eigen- (EVD) and singular value decompositions (SVD) for optimisation. Polynomial matrix decompositions extend the utility of the EVD to polynomial parahermitian matrices, and this talk presents a brief overview of such polynomial matrices, characteristics of the polynomial EVD (PEVD) and iterative algorithms for its solution. The presentation concludes with some surprising results when applying the PEVD to subband coding and broadband beamforming.

WeissStephan Weiss is Head of the Centre for Signal and Image Processing at the University of Strathclyde. He obtained Dipl.-Ing. and PhD degrees in 1995 and 1998 from the Universities of Erlangen-Nuernberg and from the University of Strathclyde. Since then, he has been a member of academic staff at the Universities of Southampton (1999-2006) and Strathclyde (1998/99 and since 2006). With his team we works on adaptive, array and statistical signal processing problems with applications in acoustics & audio, communications and biomedical problems. He has been co-organiser of the European Signal Processing Conference (EUSIPCO) 2009 in Glasgow and a number of other events.

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