This page is a copy of research/systems_and_control/signalproc (Wed, 31 Aug 2022 15:09:06)
Signal Processing
Currently the following people in our group perform research in this area:
Senior Researcher:
Reserchers:
PhD Students:
Some PhD theses from the group.
Our projects in this area have been supported by the European Research Council (ERC), the Swedish Foundation for Strategic Research (SSF), the Swedish Research Council (VR), Celsius/Saab, and the Swedish Foundation for International Cooperation in Research and Higher Education (STINT).
A Topical Textbook:
Spectral Analysis of Signals by Peter Stoica and Randolph Moses.
Page content:
- Current research topics
- Past research topics
- International collaborations
- Some achievements
- Selected publications
Current research topics:
- Spectral analysis for irregularly sampled data
- Robust adaptive beamforming
- Fundamental problems in temporal/spatial spectral estimation, including array processing
- Contributions to the design of sequences with good correlation properties
Some further Signal Processing projects are described on the page of the System Identification group.
Past research topics:
A selection of our many projects from the past:
- Fundamental problems in systems identification
- Model selection
- Nuclear quadrupole resonance signal processing
- High-resolution methods for target feature extraction and synthetic aperture radar imaging
- Direction-of-arrival, time delay and Doppler shift estimation in communications array systems
- Sensor array processing for moving targets, and narrowband signal processing
- Global convergence of blind adaptation algorithms
International collaborations:
- Massachusetts Institute of Technology, Electrical Engineering and Computer Science, Lincoln Laboratory
- K.U. Leuven, Belgium: ESAT-SISTA
- University of California, Los Angeles, USA
- University of Newcastle, Callaghan, Australia: School of Electrical Engineering and Computer Science
- University of Florida, USA: Spectral Analysis Lab
- Bell Laboratories, Alcatel-Lucent, NJ, USA: Mathematical Sciences Research Center
- Royal Institute of Technology, Sweden: School of Electrical Engineering
- GE Healthcare Technologies, Milwaukee WI, USA
- Karlstad University, Sweden: Dept. of Electrical Engineering
- King's College London, London, UK
- Aalborg University, Denmark: Dept. of Communication Technology
- Waverider, Toronto, Canada
- Stanford University, California, USA: Dept of Mathematics
- Ohio State University: Dept of Electrical and Computer Engineering
- Cornell University, Ithaca, NY, USA: School of Electrical and Computer Engineering
- California Institute of Technology, Pasadena, CA, USA
Some achievements:
- Best student paper award at EUSIPCO 2011 was given to the paper: Signal Processing Algorithms for Removing Banding Artifacts in MRI. In Proceedings of the 19th European Signal Processing Conference (EUSIPCO-2011), European Signals Processing Conference, pp 1000-1004, 2011. (fulltext:print).
- Several students completed their PhD theses in this research area: Erik Gudmundson, Yngve Selén, Niclas Sandgren, Richard Abrahamsson, Mats Cedervall, Girish Ganesan, Andreas Jakobsson, Erik G. Larsson, Magnus Mossberg, Joakim Sorelius, Tomas Sundin, and Per �hgren.
- The following selected textbooks on this topic have been published
- T. Söderström and P. Stoica: System Identification, Prentice Hall International, London, UK, 1989 -- paperback edition, 1994 -- Polish edition 1998;
- P. Stoica and R. Moses: Spectral Analysis of Signals, Prentice Hall, Upper Saddle River, NJ, 2005.
- J. Li and P. Stoica (Eds): MIMO Radar Signal Processing, J Wiley&Sons, USA, 2009.
- J Li and P Stoica (Eds): Robust Adaptive Beamforming, J Wiley&Sons, USA, 2006.
- G. Giannakis, Y. Hua, P. Stoica and L. Tong (eds): Signal Processing Advances in Wireless and Mobile Communications. Vol I: Trends in Channel Estimation and Equalization; Vol II: Trends in Single- and Multi-User Systems. Prentice-Hall, NJ, 2001.
- E. G. Larsson and P. Stoica: Space-Time Block Coding for Wireless Communications. Cambridge University Press, Cambridge, UK, May 2003 -- Chinese Edition 2006.
- Y. Wang, J. Li and P. Stoica: Spectral Analysis of Signals: This Missing Data Case. Morgan & Claypool Publishers, USA, 2005.
- J. Li, P. Stoica and Z. Wang: Robust Capon Beamforming. In Robust Adaptive Beamforming (J. Li and P. Stoica, Eds). J Wiley & Sons, USA, 2006.
- A. Scaglione and P. Stoica: Linear Precoding for MIMO Channels. In Space-Time Wireless Systems: From Array Processing to MIMO Communications. Cambridge University Press, Cambridge, UK, 2006.
- Some 15 papers have been published every year in leading international journals.
- One researcher of the group has been elected IEEE Fellow for contributions to the area, awarded some best paper prizes, and has been serving in several editorial positions for leading journals.
- One researcher of the group was given the 1996 Technical Achievement Award of the IEEE Signal Processing Society, the 2000 IEEE Millenium Medal, the 2002 Eurasip Individual Technical Achievement Award, the 2005 IEE Achievement Medal and the 2006 Society Award of the IEEE Signal Processing Society.
- A Senior Individual Grant was awarded for the period 1998-2003 by the Swedish Foundation for Strategic Research (SSF) for supporting our research in the Signals and Systems Modelling area. Also an advanced grant was awarded for the period 2008-2012 from the European Research Council, for joint reseach with KTH.
Selected publications:
Robust Estimation of the Covariance Matrix From Data With Outliers. In IEEE Open Journal of Signal Processing, volume 5, pp 1061-1072, Institute of Electrical and Electronics Engineers (IEEE), 2024. (DOI, Fulltext, fulltext:print).
Min-Max Framework for Algorithms in Signal Processing Applications: An Overview. In Foundations and Trends in Signal Processing, volume 18, number 4, pp 310-389, Now Publishers Inc., 2024. (DOI).
Pearson-Matthews correlation coefficients for binary and multinary classification. In Signal Processing, volume 222, Elsevier, 2024. (DOI).
Two New Algorithms for Maximum Likelihood Estimation of Sparse Covariance Matrices With Applications to Graphical Modeling. In IEEE Transactions on Signal Processing, volume 72, pp 958-971, Institute of Electrical and Electronics Engineers (IEEE), 2024. (DOI).
Diagnostic Tool for Out-of-Sample Model Evaluation. In Transactions on Machine Learning Research, number 10, OpenReview, 2023. (Article and review in full-text, fulltext:print).
Off-Policy Evaluation with Out-of-Sample Guarantees. In Transactions on Machine Learning Research, 2023.
Min-Max Probe Placement and Extended Relaxation Estimation Method for Processing Blade Tip Timing Signals. In IEEE Transactions on Instrumentation and Measurement, volume 72, Institute of Electrical and Electronics Engineers (IEEE), 2023. (DOI).
Multiple-hypothesis testing rules for high-dimensional model selection and sparse-parameter estimation. In Signal Processing, volume 213, Elsevier, 2023. (DOI).
Low-Rank Covariance Matrix Estimation for Factor Analysis in Anisotropic Noise: Application to Array Processing and Portfolio Selection. In IEEE Transactions on Signal Processing, volume 71, pp 1699-1711, IEEE, 2023. (DOI).
Analysis of the Minimum-Norm Least-Squares Estimator and Its Double-Descent Behavior [Lecture Notes]. In IEEE signal processing magazine (Print), volume 40, number 3, pp 39-75, IEEE, 2023. (DOI).
Regularized Linear Regression via Covariance Fitting. In IEEE Transactions on Signal Processing, volume 71, pp 1175-1183, IEEE, 2023. (DOI).
Online Learning for Prediction via Covariance Fitting: Computation, Performance and Robustness. In Transactions on Machine Learning Research, Transactions on Machine Learning Research, 2023. (Publications in full-text).
Multiple Hypothesis Testing-Based Cepstrum Thresholding for Nonparametric Spectral Estimation. In IEEE Signal Processing Letters, volume 29, pp 2367-2371, IEEE, 2022. (DOI).
Interval Design for Signal Parameter Estimation From Quantized Data. In IEEE Transactions on Signal Processing, volume 70, pp 6011-6020, Institute of Electrical and Electronics Engineers (IEEE), 2022. (DOI).
Covariance Matrix Estimation Under Positivity Constraints With Application to Portfolio Selection. In IEEE Signal Processing Letters, volume 29, pp 2487-2491, Institute of Electrical and Electronics Engineers (IEEE), 2022. (DOI).