Professor in Mathematical Statistics-Statistical Signal Processing
My research interests focus on time-frequency and spectrum analysis of especially non-stationary stochastic processes. An introduction to time-frequency analysis is found here.The main applications are biomedical signals and also signals and sound/speech connected to humans and animals.
Examples of research projects
A novel matched phase reassignment (MPR) method that gives perfect time-frequency localization of two phase synchronized oscillating transient signals is proposed. The MPR is thereby a time-frequency local measure of phase synchronization and can also be used to measure phase difference between short transient signals. We have compared to commonly used phase estimators, for different types of disturbances. Simulations show that the MPR method outperforms the state-of-the-art methods. An illustrative example of phase difference estimates in ms of transient responses measured from the electrical signals of the brain is shown below. The research is a part of a WASP-Expedition project in collaboration with Bo Bernhardsson, dept of Automatic Control and Mikael Johansson, dept of Psychology, Lund University.
The reassignment technique is used to increase localization for signal components in the time-frequency representation. The technique gives perfect localization for infinite linear chirp-signals, impulses and constant frequency signals but not for short non-stationary signals. Based on the spectrogram using a Gaussian window we propose a scaled reassignment that gives perfect localization for a Gaussian function. To the right an example of two Gaussian components clearly visualized by the scaled reassignment (ScRe-Spect). The method has been applied to estimation of dolphin echo-location signals in a collaboration with Josefin Starkhammar, division of Biomedical Engineering, Lund University.
Modeling and classification of bird song
The project is a part of the e-science collaboration, eSSENCE, and is performed together with Dennis Hasselquist, Bengt Hansson and Maja Tarka at the Department of Biology, Lund University. The project applies to general bird song but is specifically focused on the song of the Great Reed Warbler.
Tailored time-frequency features
The project is a part of the e-science collaboration, eSSENCE, and is performed together with Mikael Johansson and Ines Bramao at the Department of Psychology, Lund University. The project will develop robust tools to capture the real-time activation of memories in high temporal resolution multi-channel recordings of brain activity.
Master of Science in Electrical Engineering, Lund University, 1989, and Ph.D. in Signal Processing, Lund University, 1996. Docent in Signal Processing, 2004 and Professor in Mathematical Statistics with speciality in Statistical Signal Processing, 2010.
Main supervisor of 9 PhD students, assistant supervisor of 9 PhD students and supervisor of 3 Post Doc.
Member of FUN 2022-. Director of research studies at Centre for Mathematical Sciences LTH 2018-2022. Member of the management group at Centre for Mathematical Sciences 2018-2022. Member of the board of recruitments LTH 2013-2019. Member of the steering group of eSSENCE at LTH 2013-2019. Member of the board of recruitments, LTH, 2013-2015. Vice coordinator for the program Engineering in Mathematics, LTH, 2013-2015. Head of division Mathematical Statistics, 2008-2012. Member of the board of the strategic research area E-science at LTH, 2013-2014. Member of the board of Lunarc, 2012-2014.
Larger grants: Exclusive researcher in technical science VR 5700 kkr 2004-2009. ELLIIT 4000 kkr 2021-2024. WASP expedition 2500 kkr 2019-2020. VR-eSSENCE 2000 kkr 2016-2019. VR-eSSENCE 5000 kkr 2012-2018. VR 2400 kkr 2012-2014. VR 2600 kkr 2005-2008. VR 1200 kkr 2002-2003. TFR 1900 kkr 1998-2000.
Associate editor for IEEE Trans. on Signal Processing, 2008-2010. Regular referee for IEEE Trans. on Signal Processing, Elsevier Signal Processing, IEEE Trans. on Biomedical Engineering, IEEE Trans. on Speech and Audio Processing, Elsevier Medical Engineering and Physics.
T. H. Parker, B. Sousa, S. T. Leu, S. Edmondson, C. Foo, A. Strauss, H. Kahl, K. Ballinger, E. Ross, M. Grosse Ruse, M. Sandsten, B. H. F. Verheijen and W. Jensen, "Cultural conformity and persistence in Dickcissel song are higher in locations in which males show high site delity", Ornithology, ukab061, 2022. doi: 10.1093/ornithology/ukab061.
J. Martinsson, M. Willbo, A. Pirinen, O. Mogren and M. Sandsten, "Few-Shot Bioacoustic Event Detection Using an Event-Length Adapted Ensemble of Prototypical Networks", Detection and Classification of Acoustic Scenes and Events, Nancy, France, 2022.
O. Keding and M. Sandsten, "Robust Phase Difference Estimation of Transients in High Noise Levels", European Signal Processing Conference, (EUSIPCO), Belgrade, Serbia, 2022.
M. Åkesson and M. Sandsten, "Phase Reassignment with Effcient Estimation of Phase Difference", European Signal Processing Conference, (EUSIPCO), Belgrade, Serbia, 2022.
I. Reinhold and M. Sandsten, "The Multitaper Reassigned Spectrogram for Oscillating Transients with Gaussian Envelopes", Signal Processing, vol. 198, 2022 . doi: 10.1016/j.sigpro.2022.108570.
J. Starkhammar, I. Reinhold, T. Erlöv, M. Sandsten, "Scaled Reassigned Spectrograms Applied to Linear Transducer Signals", JASA Express Letters, Vol. 1, Iss. 5, 2021. doi: 10.1121/10.0005000.
J. Brynolfsson, I. Reinhold and M. Sandsten, "A Time- Frequency-Shift Invariant Parameter Estimator for Oscillating Transient Functions Using the Matched Window Reassignment", Signal Processing, Vol. 183, 107913, 2021. doi: 10.1016/j.sigpro.2020.107913
M. Sandsten, I. Reinhold and R. Anderson, "Parameter Estimation from the Cross-Spectrogram Reassignment Vectors", European Signal Processing Conference, (EUSIPCO-virtual), Dublin, Ireland, 2021.
M. Sandsten, R. Anderson, I. Reinhold, B. Bernhardsson, C. Bergeling, and M. Johansson, "A Novel Multitaper Reassignment Method for Estimation of Phase Synchrony", European Signal Processing Conference, (EUSIPCO-virtual), Dublin, Ireland, 2021.
I. Reinhold and M. Sandsten, "Non-parametric Envelope Estimation for the Matched Window Reassignment", European Signal Processing Conference, (EUSIPCO-virtual), Dublin, Ireland, 2021.
J. Starkhammar, I. Reinhold, M. Sandsten, P. Görts, O. Wiaczek, T. Erlöv and K. Lång, "Increasing axial resolution of 'pocket-sized' ultrasound transducer RF data", Medicinteknikdagarna, Lund, 2021.
E. M. Månsson and M. Sandsten, "The Smoothed Reassigned Spectrogram for Robust Energy Estimation", European Signal Processing Conference (EUSIPCO-virtual), Amsterdam, Netherlands, 2021.
R. Anderson and M. Sandsten, "Time-Frequency Feature Extraction for Classification of Episodic Memory", EURASIP Journal on Advances in Signal Processing, Vol. 19, 2020. doi: 10.1186/s13634-020-00681-8
M. Sandsten, I. Reinhold and R. Anderson, "A Multitaper Reassigned Spectrogram for Increased Time-Frequency Localization Precision", Int. Conf. on Acoustics, Speech and Signal Processing, (ICASSP-virtual), Barcelona, Spain, 2020.
M. Sandsten, R. Anderson, I. Reinhold and J. Brynolfsson, "The Matched Reassigned Cross-Spectrogram for Phase Estimation", Int. Conf. on Acoustics, Speech and Signal Processing, (ICASSP-virtual), Barcelona, Spain, 2020.
R. Anderson and M. Sandsten, "Multitaper Spectral Granger Causality with Application to SSVEP", Int. Conf. on Acoustics, Speech and Signal Processing, (ICASSP-virtual), Barcelona, Spain, 2020.
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Centre for Mathematical Sciences
Course web page:
Stationary stochastic processes
Stationary Stochastic Processes for Scientists and Engineers, Georg Lindgren, Holger Rootzen, Maria Sandsten, Chapman and Hall CRC Press, 2013
Course web page:
Stationary and Non-Stationary Spectral Analysis
Time-Frequency Analysis of Time-Varying Signals and Non-Stationary Processes An Introduction, Maria Sandsten, 2020.