Simo Särkkä
Senior Researcher, Dr.Tech.
(BECS)
Docent [∼Adj.Prof.] (TUT & LUT)
Research Activities
Applications
- Statistical Estimation of Predator Population
- Signal Processing and State Estimation in Brain Imaging (fMRI/MEG/EEG/DOT)
- State Estimation in Inverse Problems and Kriging
- Audio signal processing, location sensing, passive sensor based target tracking.
Bayesian Inference Methods for Stochastic Dynamic Systems
- Non-Linear Kalman Filtering and Smoothing
- Continuous-Time Stochastic Models and Stochastic Differential Equations (SDE)
- Particle Filtering and Sequential Monte Carlo Methods
Bayesian Inference Methods for Spatial and Spatio-Temporal Systems
- Gaussian Process Regression and Machine Learning
- Stochastic Partial/Pseudo Differential Equations (SPDE)
- Infinite-dimensional/distributed-parameter Kalman filtering
Publications
My Google Scholar profile: http://scholar.google.com/citations?user=QVhmc9cAAAAJ
See also Department's publication list.
The PDF preprints below are draft versions of the journal and they are here to give people an opportunity to check the relevance of the articles before purchasing the final articles from the publisher. Please send me an email if you want the latest preprints of the submitted articles.
Please note that you can show or hide publications below and the related files by pressing the links labeled "show" or "hide".
2012 [hide]
- Jouni Hartikainen, Mari Seppänen and Simo Särkkä (2012). State-Space Inference for Non-Linear Latent Force Models with Application to Satellite Orbit Prediction. To Appear in Proceedings of The 29th International Conference on Machine Learning (ICML 2012).
- Simo Särkkä, Arno Solin, Aapo Nummenmaa, Aki Vehtari, Toni Auranen, Simo Vanni, Fa-Hsuan Lin (2012). Dynamic Retrospective Filtering of Physiological Noise in BOLD fMRI: DRIFTER. NeuroImage Volume 60, Issue 2, Pages 1517-1527. [show files]
- Juha Sarmavuori and Simo Särkkä (2012). Fourier-Hermite Kalman Filter. IEEE Transactions on Automatic Control (in press). [show files]
- Simo Särkkä, Ville Viikari, Miika Huusko, and Kaarle Jaakkola (2012). Phase-Based UHF RFID Tracking with Non-Linear Kalman Filtering and Smoothing. IEEE Sensors Journal (in press). [show files]
- Simo Särkkä and Jouni Hartikainen (2012). Infinite-Dimensional Kalman Filtering Approach to Spatio-Temporal Gaussian Process Regression. JMLR Workshop and Conference Proceedings Volume 22: AISTATS 2012, Pages 993-1001. [show files]
- Simo Särkkä, Pete Bunch and Simon J. Godsill (2012). A Backward-Simulation Based Rao-Blackwellized Particle Smoother for Conditionally Linear Gaussian Models. To Appear in Proceedings of SYSID 2012 (invited paper). [show files]
- Simo Särkkä and Arno Solin (2012). On Continuous-Discrete Cubature Kalman Filtering. To Appear in Proceedings of SYSID 2012. [show files]
- Simo Särkkä, Arno Solin, Aapo Nummenmaa, Aki Vehtari, Toni Auranen, Simo Vanni and Fa-Hsuan Lin (2012). Identification of Spatio-Temporal Oscillatory Signal Structure in Cerebral Hemodynamics Using DRIFTER. ISMRM 2012. [show files]
2011 [show]
2010 [show]
2009 [show]
2008 [show]
2007 [show]
2006 [show]
2005 [show]
2004 [show]
2000 [show]
Submitted [show]
Theses etc. [show]
Patents [show]
Teaching
Courses that I am giving / have given:
- Spring 2012: fMRI school 2012 of O.V. Lounasmaa Laboratory (single lecture)
- Spring 2012: S-114.4610 Special Course in Bayesian Modelling: Bayesian estimation of time-varying processes (5 p) P
- Spring 2011: MAT-55216 Topics in Applied Mathematics: Bayesian estimation of time-varying processes: discrete-time systems (5 cr) at TUT
- Spring 2011: S-114.4220 Research Seminar on Computational Science: Numerical Methods for Stochastic Differential Equations (3 p) P
- Spring 2010: S-114.4202 Special Course in Computational Engineering II: Bayesian Estimation of Time-Varying Processes (5 p)
- Spring 2009: S-114.4202 Special Course in Computational Engineering II: Bayesian Estimation of Time-Varying Processes (5 p)
- Spring 2008: S-114.4220 Research Seminar on Computational Science: Stochastic Models in Spatial and Image Analysis
- Fall 2007: S-114.4220 Research Seminar on Computational Science: Stochastic and Adaptive Control of Uncertain Systems (5 p) L V
- Fall 2006: S-114.4220 Research Seminar on Computational Science: Bayesian Estimation of Time-Varying Processes (5 p) L V
Course material:
- Simo Särkkä (2012). Bayesian Estimation of Time-Varying Systems: Discrete-Time Systems, Lectures notes of course held in Spring 2012 (PDF, slides and exercises are also available). (2011 material is here)
Software and Audio
Software Packages
Some Matlab toolboxes where I have contributed to (see also the code examples linked in the publication list above):
- DRIFTER Toolbox for Matlab
- RBMCDA Toolbox for Matlab
- EKF/UKF Toolbox for Matlab
- MCMC Methods for MLP and GP and Stuff (for Matlab)
- MCMC Diagnostics for Matlab
- FBM tools for Matlab
Audio Signal Generation Projects
- Music: Blanket, Bussikaista
Links to Material Related to Optimal Filtering
-
The Kalman Filter Page. See especially:
- R. E. Kalman's seminal (1960) paper
- Chapter 1 from book Stochastic Models, Estimation and Control, Volume I by Peter S. Maybeck (1979)
- An Introduction to the Kalman Filter
- Wikipedia also contains much useful information:
- Sequential Monte Carlo Methods Home Page
- Lecture Notes of I. Karatzas on Stochastic Differential Equations
