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The Parallel Bayesian Toolbox for High-performance Bayesian Filtering in Metrology

). Inference in Hidden Markov Models. Springer. [7] Fraser, A.M. (2008). Hidden Markov Models and Dynamical Systems (1st ed.). Society for Industrial and Applied Mathematics. [8] Doucet, A., de Freitas, N., Gordon, N. (2001).Sequential Monte Carlo Methods in Practice.Springer. [9] Douc, R., Cappé, O., Moulines, E. (2005). Comparison of resampling schemes for particle filtering. In Image and Signal Processing and Analysis : 4th International Symposium (ISPA 2005), 15-17 September 2005.IEEE, 64-69. [10] Daum, F

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Machine Vision System Measuring the Trajectory of Upper Limb Motion Applying the Matlab Software

University. [10] Kuryło, P., Cyganiuk, J., Tertel, E., Frankovský, P. (2016). Machine vision investigate the trajectory of the motion human body – review of the methods. Acta Mechatronica , 1 (2), 7–13. [11] Deutscher, J., Blake, A., Reid, I. (2000). Articulated body motion capture by annealed particle filtering. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition . IEEE, 126–133. [12] Schmidt, J., Fritsch, J., Kwolek, B. (2006). Kernel particle filter for real-time 3D body tracking in monocular color images. In Proceedings of

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A Design of Finite Memory Residual Generation Filter for Sensor Fault Detection

alternative FIR filter for state estimation in discrete-time systems. Digital Signal Processing, 20 (3), 935-943. [12] Kim, P.S. (2013). A computationally efficient fixedlag smoother using recent finite measurements. Measurement, 46 (1), 846-850. [13] Zhao, S., Shmaliy, Y.S., Huang, B., Liu, F. (2015). Minimum variance unbiased FIR filter for discrete time-variant systems. Automatica, 53 (2), 355-361. [14] Pak, J., Ahn, C., Shmaliy, Y., Lim, M. (2015). Improving reliability of particle filter-based localization in wireless

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Realtime Motion Assessment For Rehabilitation Exercises: Integration Of Kinematic Modeling With Fuzzy Inference

. Kulic, “Online segmentation of human motion for automated rehabilitation exercise analysis,” Neural Systems and Rehabilitation Engineering, IEEE Transactions on , vol. 22, no. 1, pp. 168–180, 2014. [12] S. Schaal, A. Ijspeert, and A. Billard, “Computational approaches to motor learning by imitation,” Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences , vol. 358, no. 1431, pp. 537–547, 2003. [13] N. Gordon, B. Ristic, and S. Arulampalam, “Beyond the kalman filter: Particle filters for tracking applications,” Artech

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Electrical Capacitance Tomography Measurement of the Migration of Ice Frontal Surface in Freezing Soil

). Electrical capacitance tomography with a non-circular sensor using the dbar method. Measurement Science and Technology, 21, 1-6. [25] Watzenig, D., Brandner, M., Steiner, G. (2007). A particle filter approach for tomographic imaging based on different state-space representations. Measurement Science and Technology, 18, 30-40. [26] Soleimani, M., Vauhkonen, M., Yang, W.Q., Peyton, A., Kim, B.S., Ma, X.D. (2007). Dynamic imaging in electrical capacitance tomography and electromagnetic induction tomography using a Kalman filter. Measurement

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Simulation and Experimental Evaluation of the EKF Simultaneous Localization and Mapping Algorithm on the Wifibot Mobile Robot

) Problem, IEEE Transactions on Robotics and Automation, Vol. 17, No. 3, 2001, pp. 229–241. [13] M. Montemerlo, S. Thrun, D. Koller and B. Wegbreit, FastSLAM: A Factored Solution to the Simultaneous Localization and Mapping Problem, 8 th National Conference on Artificial Intelligence, 2002, pp. 593–598. [14] M. Montemerlo, S. Thrun, D. Koller and B. Wegbreit, FastSLAM 2.0: An Improved Particle Filtering Algorithm for Simultaneous Localization and Mapping that Provably Converges, 18 th international joint conference on Artificial intelligence, 2003, pp. 1151

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Image Reconstruction Method with the Exploitation of the Spatial Correlation for Electrical Capacitance Tomography

iteration for complicated distributions. Measurement Science and Technology, 19, 1-8. [20] Cao, Z., Xu, L.J., Wang, H.X. (2010). Electrical capacitance tomography with a non-circular sensor using the dbar method. Measurement Science and Technology, 21 (1), 1-6. [21] Watzenig, D., Brandner, M., Steiner, G. (2007). A particle filter approach for tomographic imaging based on different state-space representations. Measurement Science and Technology, 18 (1), 30-40. [22] Soleimani, M., Vauhkonen, M., Yang, W.Q., Peyton, A., Kim

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