SAM 2012 - Plenary Speakers 
| User Parameter Free Dense and Sparse Spectral Estimation Algorithms Jian Li |
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Abstract: User parameter free algorithms, like the simple fast Fourier transform (FFT), are easy to use and are desirable for diverse practical applications. However, the data-independent FFT algorithm suffers from poor resolution and high sidelobe level problems. Many parametric, nonparametric, and sparse (semi-parametric) spectral estimation algorithms have been introduced in the literature. They possess super resolution and low sidelobe level properties. However, most of these algorithms are not user parameter free, making them difficult to use in practical applications. Many of these algorithms are sensitive to data model errors and/or require second-order statistics of the measurement vector. We present herein an iterative adaptive approach (IAA) for dense spectral estimation and a sparse learning via iterative minimization (SLIM) algorithm for sparse spectral estimation. Both algorithms are user parameter free, with the dense algorithm more accurate and the sparse algorithm computationally more efficient. We also discuss how to combine the merits of IAA and SLIM into a single hybrid algorithm that is both accurate and sparse.
Biography: Jian Li is with the Department of Electrical and Computer Engineering, University of Florida, Gainesville, where she is currently a Professor. In Fall 2007, she was on sabbatical leave at MIT, Cambridge, Massachusetts. Her current research interests include spectral estimation, statistical and array signal processing, and their applications.
Dr. Li is a Fellow of IEEE and a Fellow of IET. She received the 1994 National Science Foundation Young Investigator Award and the 1996 Office of Naval Research Young Investigator Award. She has been a member of the Editorial Board of the IEEE Signal Processing Magazine since 2010 and a member of the Editorial Board of Digital Signal Processing -- A Review Journal, a publication of Elsevier, since 2006. She is a co-author of the paper that has received the M. Barry Carlton Award for the best paper published in IEEE Transactions on Aerospace and Electronic Systems in 2005. She is also a co-author of the paper that has received the Lockheed Martin Best Student Paper Award at the 2009 SPIE Defense, Security, and Sensing Conference in Orlando, Florida.
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