Events Calendar

Sparsity-Cognizant Total Least-Squares for Perturbed Compressive Sampling

Speaker: Geert Leus, Delft University of Technology

Talk Title: Sparsity-Cognizant Total Least-Squares for Perturbed Compressive Sampling

Abstract: Solving linear regression problems based on the total
least-squares (TLS) criterion has well-documented merits in various
applications, where perturbations appear both in the data vector as well as
in the regression matrix. However, existing TLS approaches do not account
for sparsity possibly present in the unknown vector of regression
coefficients. On the other hand, sparsity is the key attribute exploited by
modern compressive sampling and variable selection approaches to linear
regression, which include noise in the data, but do not account for
perturbations in the regression matrix. In this presentation, we fill this
gap by formulating and solving TLS optimization problems under sparsity
constraints. Near-optimum and reduced-complexity suboptimum sparse (S-) TLS
algorithms are developed to address the perturbed compressive sampling (and
the related dictionary learning) challenge, when there is a mismatch between
the true and adopted bases over which the unknown vector is sparse. The
novel S-TLS schemes also allow for perturbations in the regression matrix of
the least-absolute selection and shrinkage selection operator (Lasso), and
endow TLS approaches with ability to cope with sparse, under-determined
errors-in-variables models. Interesting generalizations can further exploit
prior knowledge on the perturbations to obtain novel weighted and structured
S-TLS solvers. Analysis and simulations demonstrate the practical impact of
S-TLS in calibrating the mismatch effects of contemporary grid-based
approaches to cognitive radio sensing, and robust direction-of-arrival
estimation using antenna arrays.


Biography: Geert Leus was born in Leuven, Belgium, in 1973. He received the
electrical engineering degree and the PhD degree in applied sciences from
the Katholieke Universiteit Leuven, Belgium, in June 1996 and May 2000,
respectively. He has been a Research Assistant and a Postdoctoral Fellow of
the Fund for Scientific Research - Flanders, Belgium, from October 1996 till
September 2003. During that period, Geert Leus was affiliated with the
Electrical Engineering Department of the Katholieke Universiteit Leuven,
Belgium. Currently, Geert Leus is an Associate Professor at the Faculty of
Electrical Engineering, Mathematics and Computer Science of the Delft
University of Technology, The Netherlands. During the summer of 1998, he
visited Stanford University, and from March 2001 till May 2002 he was a
Visiting Researcher and Lecturer at the University of Minnesota. His
research interests are in the area of signal processing for communications.
Geert Leus received a 2002 IEEE Signal Processing Society Young Author Best
Paper Award and a 2005 IEEE Signal Processing Society Best Paper Award. He
is the Chair of the IEEE Signal Processing for Communications Technical
Committee, and an Associate Editor for the IEEE Transactions on Signal
Processing and the EURASIP Journal on Applied Signal Processing. In the
past, he has served on the Editorial Board of the IEEE Signal Processing
Letters and the IEEE Transactions on Wireless Communications.


Host: Prof. Urbashi Mitra, ubli@usc.edu, x0-4667

Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248

Audiences: Everyone Is Invited

Contact: Gerrielyn Ramos