Signal Processing

The research in this area is coupled to the PhD program in Signal Processing.

Currently the following people in our group perform research in this area:

Senior Researcher:

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.

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Current research topics:

Some further Signal Processing projects are described on the page of the System Identification group.

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Past research topics:

A selection of our many projects from the past:

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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

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Some achievements:

  • Best student paper award at EUSIPCO 2011 was given to the paper:
    Signal Processing Algorithms for Removing Banding Artifacts in MRI. Marcus Björk, Erik Gudmundson, Joëlle Barral, and Peter Stoica. In Proceedings of the 19th European Signal Processing Conference (EUSIPCO-2011), European Signals Processing Conference, pp 1000-1004, 2011. (fulltext).
  • 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 Åhgren.
  • 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.

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Selected publications:

Sparse representations and sphere decoding for array signal processing. T. Yardibi, J. Li, Peter Stoica, and Cattafesta, L. N. , I I I. In Digital signal processing (Print), volume 22, number 2, pp 253-262, 2012. (DOI).
Optimization of the Receive Filter and Transmit Sequence for Active Sensing. Petre Stoica, Hao He, and Jian Li. In IEEE Transactions on Signal Processing, volume 60, number 4, pp 1730-1740, 2012. (DOI).
On the Performance of Optimal Input Signals for Frequency Response Estimation. Bo Wahlberg, Hakan Hjalmarsson, and Peter Stoica. In IEEE Transactions on Automatic Control, volume 57, number 3, pp 766-771, 2012. (DOI).
On the LIMES approach to spectral analysis of irregularly sampled data. Peter Stoica and Prabhu Babu. In Electronics Letters, volume 48, number 4, pp 218-219, 2012. (DOI).
Sparse estimation of spectral lines: Grid selection problems and their solutions. Peter Stoica and Prabhu Babu. In IEEE Transactions on Signal Processing, volume 60, number 2, pp 962-967, 2012. (DOI).
SPICE and LIKES: Two hyperparameter-free methods for sparse-parameter estimation. Peter Stoica and Prabhu Babu. In Signal Processing, volume 92, number 7, pp 1580-1590, 2012. (DOI).
Perfect root-of-unity codes with prime-size alphabet. Mojtaba Soltanalian and Peter Stoica. In ICASSP2011, the 36th International Conference on Acoustics, Speech and Signal Processing, Prague, Czech Republic, International Conference on Acoustics Speech and Signal Processing ICASSP, p 3136-3139, 2011.
A combined linear programming-maximum likelihood approach to radial velocity data analysis for extrasolar planet detection. Prabhu Babu and Peter Stoica. In ICASSP2011, the 36th International Conference on Acoustics, Speech and Signal Processing, Prague, Czech Republic, International Conference on Acoustics Speech and Signal Processing ICASSP, pp 4352-4355, 2011.
A sparse covariance-based method for direction-of-arrival estimation. Peter Stoica, Prabhu Babu, and Jian Li. In ICASSP2011, the 36th International Conference on Acoustics, Speech and Signal Processing, Prague, Czech Republic., International Conference on Acoustics Speech and Signal Processing ICASSP, pp 2844-2847, 2011.
Maximum-likelihood nonparametric estimation of smooth spectra from irregularly sampled data. Peter Stoica and Prabhu Babu. In IEEE Transactions on Signal Processing, volume 59, number 12, pp 5746-5758, 2011. (DOI).
Signal Modeling and the Cramér-Rao Bound for Absolute Magnetic Resonance Thermometry in Fat Tissue. Marcus Björk, Johan Berglund, Joel Kullberg, and Peter Stoica. In 45th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, November 6-9, 2011, 2011.
Signal Processing Algorithms for Removing Banding Artifacts in MRI. Marcus Björk, Erik Gudmundson, Joëlle Barral, and Peter Stoica. In Proceedings of the 19th European Signal Processing Conference (EUSIPCO-2011), European Signals Processing Conference, pp 1000-1004, 2011. (fulltext).
Probing waveforms and adaptive receivers for active sonar. Jun Ling, Jian Li, Peter Stoica, and Michael Datum. In Journal of Acoustical Society of America, volume 129, number 6, pp 3640-3651, 2011. (DOI).
Knowledge-aided space-time adaptive processing. Xumin Zhu, Jian Li, and Peter Stoica. In IEEE Transactions on Aerospace and Electronic Systems, volume 47, number 2, pp 1325-1336, 2011. (DOI).
The Gaussian data assumption leads to the largest Cramér-Rao bound. Peter Stoica and Prabhu Babu. In IEEE signal processing magazine (Print), volume 28, number 3, pp 132-133, 2011. (DOI).