Spectral estimation is important in many fields including astronomy, meteorology, seismology, communications, economics, speech analysis, medical imaging, radar, sonar, and underwater acoustics. Most existing spectral estimation algorithms are devised for uniformly sampled complete-data sequences. However, the spectral estimation for data sequences with missing samples is also important in many applications ranging from astronomical time series analysis to synthetic aperture radar imaging with angular diversity. For spectral estimation in the missing-data case, the challenge is how to extend the existing spectral estimation techniques to deal with these missing-data samples. Recently, nonparametric adaptive filtering based techniques have been developed successfully for various missing-data problems. Collectively, these algorithms provide a comprehensive toolset for the missing-data problem based exclusively on the nonparametric adaptive filter-bank approaches, which are robust and accurate, and can provide high resolution and low sidelobes. In this book, we present these algorithms for both one-dimensional and two-dimensional spectral estimation problems.
Table of Contents
Linear Source Separation
Online Software and Data
About the Author(s)Yanwei Wang
, Department of Electrical and Computer Engineering, Diagnostic Ultrasound Corporation
Yanwei Wang received the B.Sc. degree in electrical engineering from the Beijing University of Technology, China, in 1997 and the M.Sc. degree, again in electrical engineering from the University of Florida, Gainesville, in 2001. Since January 2000, he has been a research assistant with the Department of Electrical and Computer Engineering, University of Florida, where he received the Ph.D. degree in December 2004. Currently, he is with the R&D group of Diagnostic Ultrasound Corp. His research interests include spectral estimation, medical tomographic imaging, and radar/array signal processing.Jian Li
, Department of Electrical and Computer Engineering, University of Florida
Jian Li received the M.Sc. and Ph.D. degrees in electrical engineering from The Ohio State University, Columbus, in 1987 and 1991, respectively. From April 1991 to June 1991, she was an Adjunct Assistant Professor with the Department of Electrical Engineering, The Ohio State University, Columbus. From July 1991 to June 1993, she was an Assistant Professor with the Department of Electrical Engineering, University of Kentucky, Lexington. Since August 1993, she has been with the Department of Electrical and Computer Engineering, University of Florida, Gainesville, where she is currently a Professor. Her current research interests include spectral estimation, array signal processing, and their applications. Dr. Li is a member of Sigma Xi and Phi Kappa Phi. She received the 1994 National Science Foundation Young Investigator Award and the 1996 Office of Naval Research Young Investigator Award. She was an Executive Committee Member of the 2002 International Conference on Acoustics, Speech, and Signal Processing, Orlando, Florida, May 2002. She has been an Associate Editor of the IEEE Transactions on Signal Processing since 1999 and an Associate Editor of the IEEE Signal Processing Magazine since 2003. She is presently a member of the Signal Processing Theory and Methods (SPTM) Technical Committee of the IEEE Signal Processing Society.Petre Stoica
, Department of Information Technology, Division of Systems and Control, Uppsala University, Sweden
Petre Stoica (F'94) received the D.Sc. degree in automatic control from the Polytechnic Institute of Bucharest (BPI), Bucharest, Romania, in 1979 and an honorary doctorate degree in science from Uppsala University (UU), Uppsala, Sweden, in 1993. He is Professor of system modeling with the Department of Systems and Control at UU. Previously, he was a Professor of system identification and signal processing with the Faculty of Automatic Control and Computers at BPI. He held longer visiting positions with Eindhoven University of Technology, Eindhoven, The Netherlands; Chalmers University of Technology, Gothenburg, Sweden (where he held a Jubilee Visiting Professorship); UU; The University of Florida, Gainesville; and Stanford University, Stanford, CA. His main scientific interests are in the areas of system identification, time series analysis and prediction, statistical signal and array processing, spectral analysis, wireless communications, and radar signal processing. He has published seven books, ten book chapters, and some 450 papers in archival journals and conference records on these topics. The most recent book he coauthored, with R. Moses, is entitled Introduction to Spectral Analysis
(Englewood Cliffs, NJ: Prentice-Hall, 1997). He has also edited two books on signal processing advances in wireless communications and mobile communications, published by Prentice-Hall in 2001. He is on the editorial boards of five journals in the field: Journal of Forecasting; Signal Processing; Circuits, Signals, and Signal Processing; Digital Signal Processing - A Review Journal; and Multidimensional Systems and Signal Processing. He was a Co-Guest Editor for several special issues on system identification, signal processing, spectral analysis, and radar for some of the aforementioned journals, as well as for Proceeding of the IEEE.