Distinguished lecturer Prof. Tülay Adali at TUT

On Friday, June 21, Prof. Tülay Adali from University of Maryland, Baltimore County will give a lecture at Tallinn University of Technology (Ehitajate tee 5) in room VI-229 at 13:00. The lecture is a part of IEEE Signal Processing Society’s Distinguished Lecturer Program and is titled as “Complex-valued Adaptive Signal Processing: When and how to take non-circularity into account?” Access is free for everybody.
Complex-valued signals arise frequently in applications as diverse as communications, radar, geophysics, optics, and biomedicine, as most practical modulation formats are of complex type and applications such as radar and magnetic resonance imaging lead to data that are inherently complex valued. There are two key issues in the statistical signal processing of complex-valued data: (1) making use of the complete statistical information by taking the potential noncircularity of the signal into account; and (2) optimization of real-valued cost functions with respect to complex parameters.
This talk first reviews recent advances related to both issues, which are coupled. It is shown that noncircularity is an intrinsic characteristic of many signals of practical interest, and when taken into account, the methods developed for their processing provide significant performance gains. On the other hand, by using Wirtinger calculus, optimization can be carried out in a way similar to the real-valued case without the need to evaluate derivatives separately with respect to real and imaginary parts.
Hence, expressions are kept simple and one does not need to invoke unrealistic assumptions such as circularity of the signals, an unrealistic assumption that helps with tractability but prevents one from making use of the information in the phase of the signal.
After a review of the basic tools for statistical characterization and optimization, the talk presents examples in adaptive filtering, model order selection, and blind source separation, and emphasizes when and how one should account for the potential noncircularity of the signal.

Tülay Adali received the Ph.D. degree in electrical engineering from North Carolina State University, Raleigh, in 1992 and joined the faculty at the University of Maryland Baltimore County (UMBC), Baltimore, the same year where she currently is a Professor in the Department of Computer Science and Electrical Engineering. She has held visiting positions at École Supérieure de Physique et de Chimie Industrielles, Paris, France, Technical University of Denmark, Lyngby, Denmark, Katholieke Universiteit, Leuven, Belgium, and University of Campinas, Brazil.
Prof. Adali assisted in the organization of a number of international conferences and workshops including the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), the IEEE International Workshop on Neural Networks for Signal Processing (NNSP), and the IEEE International Workshop on Machine Learning for Signal Processing (MLSP).
She was the General Co-Chair, NNSP (2001–2003); Technical Chair, MLSP (2004–2008); Program Co-Chair, MLSP (2008 and 2009), 2009 International Conference on Independent Component Analysis and Source Separation; Publicity Chair, ICASSP (2000 and 2005); and Publications Co-Chair, ICASSP 2008.
Prof. Adali chaired the IEEE Signal Processing Society (SPS) MLSP Technical Committee (2003–2005, 2011–2013), served on the SPS Conference Board (1998–2006), and the Bio Imaging and Signal Processing Technical Committee (2004–2007). She was an Associate Editor for IEEE Transactions on Signal Processing (2003–2006), IEEE Transactions on Biomedical Engineering (2007–2013), IEEE Journal of Selected Areas in Signal Processing (2010-2013), and Elsevier Signal Processing Journal (2007–2010). She is currently serving on the Editorial Boards of the IEEE Proceedings and Journal of Signal Processing Systems for Signal, Image, and Video Technology, and is a member of the IEEE SPS MLSP and Signal Processing Theory and Methods Technical Committees.
Prof. Adali is a Fellow of the IEEE and the AIMBE, recipient of a 2010 IEEE Signal Processing Society Best Paper Award, 2013 University System of Maryland Regents’ Award for Research, and an NSF CAREER Award. She is an IEEE Signal Processing Society Distinguished Lecturer for 2012 and 2013.
Her research interests are in the areas of statistical signal processing, machine learning for signal processing, and biomedical data analysis.
 
Lisainformatsioon:
http://www.signalprocessingsociety.org/community/lectures/distinguished-lecturers/
http://www.csee.umbc.edu/~adali/