Publications

An automatically generated list of published contributions (LiU) from the DiVA database is available here.
Google Scholar profile

Book Chapter

S. Saha, G. Hendeby and F. Gustafsson, Mixture Kalman Filters and Beyond, Current trends in Bayesian methodology with applications, Chapman & Hall /CRC Press, May, 2015 (to appear).
S.I. Aihara, A. Bagchi and S. Saha, Filtering for Stochastic Volatility by Using Exact Sampling and Application to Term Structure Modeling, Informatics in Control, Automation and Robotics, Ferrier, J.-L., Gusikhin, O., Madani, K., Sasiadek, J. (Eds.), Lecture Notes in Electrical Engineering, Vol. 325 , Springer, 2015 (to appear).

Journal articles

S. Saha, P. K. Mandal, A. Bagchi, Y. Boers and H. Driessen. Particles based smoothed marginal MAP estimator for general state space models. IEEE Transaction on Signal Processing, 61(2), 264 - 273, 2013. [PDF]
E. Ozkan, V. Smidl, S. Saha, C. Lundquist and F. Gustafsson. Marginalized Adaptive Particle Filtering for Non-linear Models with Unknown Time-varying Noise Parameters. Automatica, 49(6), 1566-1575, 2013.[PDF] [Elsevier]
Saikat Saha and Fredrik Gustafsson. Particle filtering for dependent noise processes. IEEE Transaction on Signal Processing, 60(9), 4497 - 4508, 2012. [PDF]
S. Saha, P. K. Mandal, Y. Boers, H. Driessen and A. Bagchi. Gaussian proposal density using moment matching in SMC methods. Statistics and Computing, Vol. 19(2), pp. 203-208, 2009. [PDF]
Shin Ichi Aihara, Arunabha Bagchi and Saikat Saha. On parameter estimation of stochastic volatility models from stock data using particle filter - application to AEX index. International Journal of Innovative Computing Information and Control, Vol. 5(1), pp. 17-27, 2009.
Saikat Saha and C. S. Manohar. Inverse reliability based structural design for system dependent critical earthquake loads. Probabilistic Engineering Mechanics, Vol.20, pp. 19-31, 2005.

Conference articles

S. Saha and G. Hendeby. Rao-Blackwellized Particle Filter for Markov Modulated Nonlinear Dynamic Systems, IEEE Workshop on Statistical Signal Processing (SSP14), 2014, Gold Coast, Australia.
S. Saha. Bayesian calibration of the Schwartz-Smith Model adapted to the energy market, IEEE Workshop on Statistical Signal Processing (SSP14), 2014, Gold Coast, Australia.
C. Fritsche, S. Saha and F. Gustafsson. Bayesian Cramer-Rao Bound for Nonlinear Filtering with Dependent Noise Processes, 16th International Conference on Information Fusion (FUSION), 2013, Istanbul, Turkey.
S.I. Aihara, A. Bagchi and S. Saha. Adaptive Filtering for Stochastic Volatility by Using Exact Sampling, 10th International Conference on Informatics in Control, Automation and Robotics (ICINCO), Reykjavik, Iceland, 2013.
S. Saha, G. Hendeby and F. Gustafsson. Noise Adaptive Particle Filtering: A Hierarchical Perspective. ISBA Regional Meeting, Varanasi, India, 2013.
S. Saha, F. Gustafsson. Importance Sampling Applied to Pincus Maximization for Particle Filter MAP Estimation. Proceedings of 15th International Conference on Information Fusion (FUSION), 2012, Singapore. [IEEE]
Shin Ichi Aihara, Arunabha Bagchi and Saikat Saha. Identification of Bates Stochastic Volatility Model by Using Non-central Chi-Square Random Generation Method. Proceedings of IEEE ICASSP, 2012, Kobe, Japan (A related version presented in Bachelier Finance Society - 7th World Congress, Sydney, 2012).
S. Saha, U. Orguner, F. Gustafsson. Non-Linear Filtering with Observations from Student's t Processes. Proceedings of IEEE Aerospace Conference, 2012, Big Sky, Montana, USA.
S. Saha, F. Gustafsson. Marginalized Particle Filter for Dependent Noise Processess. Proceedings of IEEE Aerospace Conference, 2012, Big Sky, Montana, USA.
F. Gustafsson, S. Saha, U. Orguner. The Benefits of Down-Sampling in the Particle Filter. Proceedings of 14th International Conference on Information Fusion (FUSION), 2011, Chicago, USA. [IEEE]
E. Ozkan, S. Saha, F. Gustafsson and V. Smidl. Non-Parametric Bayesian Noise Density Estimation in Non-Linear Filtering. Proceedings of IEEE ICASSP, Prague, 2011.
D. Tornqvist, S. Saha and F. Gustafsson. Batched Fault Detection using Particle Smoothing. Proceedings of IEEE Aerospace Conference, 2011, Big Sky, Montana, USA.
F. Gustafsson, S. Saha, U. Orguner. Non-Linear Filtering based on Observations from Gaussian Processes. Proceedings of IEEE Aerospace Conference, 2011, Big Sky, Montana, USA.
S. Saha, E. Ozkan, F. Gustafsson and V. Smidl. Marginalized Particle Filters for Bayesian Estimation of Gaussian Noise Parameters. Proceedings of 13th International Conference on Information Fusion (FUSION), 2010, Edinburgh, UK. [IEEE]
F. Gustafsson and S. Saha. Particle filtering with dependent noises. Proceedings of 13th International Conference on Information Fusion (FUSION), 2010, Edinburgh, UK. [IEEE]
E. Ozkan, S. Saha, F. Gustafsson and V. Smidl. Estimation of Unknown Gaussian Noise Parameters in General State Space Models. Swedish Meeting on Systems and Control (Reglermote), 2010, Lund, Sweden.
S. Saha, Y. Boers, H. Driessen, P. K. Mandal and A. Bagchi. Particle Based MAP State Estimation: A Comparison. Proceedings of 12th International Conference on Information Fusion (FUSION), 2009, Seattle, USA. [IEEE]
S. Saha, P. K. Mandal, A. Bagchi, Y. Boers and H. Driessen. Parameter Estimation in a General State Space Model From Short Observation Data: A SMC based Approach. Proceedings of IEEE Workshop on Statistical Signal Processing (SSP), 2009, Cardiff, U.K.
S. Saha, P. K. Mandal and A. Bagchi. A New Approach To Particle Based Smoothed Marginal MAP. Proceedings of 16th European Signal Processing Conference (EUSIPCO), 2008, Lausanne, Switzerland. [PDF]
Shin Ichi Aihara, Arunabha Bagchi and Saikat Saha. Estimating Volatility and Model Parameters of Stochastic Volatility Models with Jumps Using Particle Filter. Proceedings of 17th IFAC World Congress, 2008, Seoul, South Korea.
S. Saha. An efficient Gaussian proposal in SMC methods. 24th Benelux meet on Systems and Control, 2007, Lommel, Belgium.
S. Saha, P. K. Mandal, Y. Boers and H. Driessen. Exact moment matching for efficient importance functions in SMC methods. Proceedings of Nonlinear Statistical Signal Processing Workshop (NSSPW), 2006, IEEE, Cambridge, UK.