CONTACT CZ/EN

Publications

The main research results can be found in the field of local and global nonlinear filtering, nonlinear identification, predictive and bi-criteria dual control, and passive and active fault detection. These results were published in the respected world journal magazines with high impact factor (Automatica, IEEE Transactions on Automatic Control, Signal Processing), congresses and symposia of the International Federation of Automatic Control (IFAC), and important american conferences (Conference on Decision and Control, American Control Conference).

Publications' statistics

Year 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022
Journal papers 2 5 2 1 3 2 2 2 6 5 4 2 2
Conference papers 14 14 10 13 19 18 14 16 14 14 12 8 0
Total 16 19 12 14 22 20 16 18 20 19 16 10 2

Selected team publications

Journal articles

Conference articles

  • Kost, O.,Duník, J., Straka, O. (2021). Identifiability of Unique Elements of Noise Covariances in State-Space Models. In Proceedings of the 19th IFAC Symposium on System Identification (SYSID 2021) (pp. 316-321). Amsterdam, Netherlands. doi.org/10.1016/j.ifacol.2021.08.378

  • Matoušek, J., Brandner, M., & Duník, J., (2021). Continuous Nonlinear State Prediction by Finite Volume Method on Logically Rectangular Grids. In Proceedings of the 2021 IEEE 60th IEEE Conference on Decision and Control (CDC). doi.org/10.1109/CDC45484.2021.9683293

  • Radtke, S., Ajgl, J., Straka, O., & Hanebeck, UD., (2021). Learning and Exploiting Partial Knowledge in Distributed Estimation. In Proceedins of the 2021 IEEE International Conference on Multisensor Fusion and Integration (MFI). doi.org/10.1109/MFI52462.2021.9591197

  • Straka, O., Duník, J., & Elvira, V., (2021). Importance Gauss-Hermite Gaussian Filter for Models with Non-Additive Non-Gaussian Noises. In Proceedings of the 2021 IEEE 24th International Conference on Information Fusion (FUSION). doi.org/10.23919/FUSION49465.2021.9626832

  • Matoušek, J., Duník, J., Brandner, M., & Elvira, V., (2021). Comparison of Discrete and Continuous State Estimation with Focus on Active Flux Scheme. In Proceedings of the 2021 IEEE 24rd International Conference on Information Fusion (FUSION). doi.org/10.23919/FUSION49465.2021.9626836

  • Ajgl, J. & Straka, O., (2021). Lower Bounds In Estimation Fusion With Partial Knowledge of Correlations. In Proceedings of the 2021 IEEE International Conference on Multisensor Fusion and Integration (MFI). doi.org/10.1109/MFI52462.2021.9591173

  • Ajgl, J. & Straka, O., (2021). Comparison of Confidence Sets Designs for Various Degrees of Knowledge. In Proceedings of the 2021 24th International Conference on Information Fusion (FUSION). doi.org/10.23919/FUSION49465.2021.9626991

  • Duník, J., Straka, O., & Hanebeck, UD., (2021). Cooperative Unscented Kalman Filter with Bank of Scaling Parameter Values. In Proceedings of the 2021 IEEE 24th International Conference on Information Fusion (FUSION). doi.org/10.23919/FUSION49465.2021.9626987

  • Duník, J., Straka, O., & Matoušek, J., (2020). Reliable Convolution in Point-Mass Filter for a Class of Nonlinear Models. In Proceedings of the 2020 IEEE 23rd International Conference on Information Fusion (FUSION), pp. 1-7, Rustenburg, South Africa. doi.org/10.23919/FUSION45008.2020.9190218

  • Fehér, M. & Straka, O. (2020). Time-to-go function of double-integrator system with asymmetrical constraints. In Proceeding of 2020 European Control Conference (ECC). Saint Petersburg, pp. 178-183. Sun City. doi.org/10.23919/ECC51009.2020.9143865

  • Ajgl, J. & Straka, O. (2020). Design of Confidence Sets for Estimation with Approximate Piecewise Linear Constraint. In Proceedings of the 2020 European Control Conference (ECC), pp. 825-830, Saint Petersburg. doi.org/10.23919/ECC51009.2020.9143764

  • Duník, J., Kost, O., Straka, O., & Blasch, E. (2020). Navigation and Estimation Improvement by Environmental-Driven Noise Mode Detection. In Proceedings of the 2020 IEEE/ION Position, Location and Navigation Symposium (PLANS), pp. 925-932, Portland, USA. doi.org/10.1109/PLANS46316.2020.9110200

  • Ajgl, J. & Straka, O. (2020). Inverse Covariance Intersection Fusion of Multiple Estimates. In Proceedings of the 2020 IEEE 23rd International Conference on Information Fusion (FUSION), pp. 1-8, Rustenburg, South Africa. doi.org/10.23919/FUSION45008.2020.9190614

  • Straka, O., & Duník, J. (2020). Resampling-free Stochastic Integration Filter. In Proceedings of the 2020 IEEE 23rd International Conference on Information Fusion (FUSION), pp. 1-8, Rustenburg, South Africa. doi.org/10.23919/FUSION45008.2020.9190535

  • Bouček, Z. & Flídr, M. (2020). Interpolating Control Based Trajectory Tracking. In Proceedings of the 16th International Conference on Control, Automation, Robotics and Vision, https://doi.org/10.1109/ICARCV50220.2020.9305511

  • Duník, J., Kost, O., & Straka, O. (2020). Estimation of Parameters of Gaussian Sum Distributed Noises in State-Space Models. Proceedings of the 21st IFAC World Congress, Berlin, Germany.

  • Duník, J., Straka, O., & Matoušek, J. (2020). Conditional Density Driven Grid Design in Point-Mass Filter. In Proceedings of the 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 9180-9184, Barcelona. doi.org/10.1109/ICASSP40776.2020.9052962

  • Ajgl, J. & Straka, O. (2020). Evaluation of Confidence Sets for Estimation with Piecewise Linear Constraint. In Proceedings of the 2020 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2020), pp. 146-151, Karlsruhe. doi.org/10.23919/ECC51009.2020.9143764

  • Straka, O. & Punčochář, I. (2020). Hierarchical Active Fault Diagnosis for Stochastic Large Scale Systems with Coupled Faults. Proceedings of the 2020 IEEE 23rd International Conference on Information Fusion (FUSION), pp 1-8, Rustenburg, South Africa. doi.org/10.23919/FUSION45008.2020.9190304

  • Straka, O., & Punčochář, I. (2020). Distributed Active Faults Diagnosis for Systems with Conditionally Dependent Faults. Proceedings of the 21st IFAC World Congress, Berlin, Germany.

  • Ajgl, J. & Straka, O. (2019). Calculation of Support Function for Fusion Under Partial Knowledge. In Proceedings of the 2019 IEEE International Conference on Industrial Cyber Physical Systems, 224-229. doi.org/10.1109/ICPHYS.2019.8780334

  • Bouček, Z. & Flídr, M. (2019). Modification of Explicit Interpolating Controller for Control Problem with Constant Setpoint. In Proceeding of the 15th European Workshop on Advanced Control and Diagnosis, www.researchgate.net/publication/340397107_Modification_of_Explicit_Interpolating_Controller_for_Control_Problem_with_Constant_Setpoint

  • Ajgl, J. & Straka, O. (2019). On Fusion of Partial Estimates Under Implicit Partial Knowledge of Correlation. In Proceedings of the 2019 22th International Conference on Information Fusion (FUSION), pp. 1-8, Ottawa, Canada. ieeexplore.ieee.org/document/9011251

  • Straka, O. & Punčochář, I., (2019). Decentralized and Distributed Active Fault Diagnosis for Stochastic Systems with Indirect Observations. In Proceedings of the 2019 22th International Conference on Information Fusion (FUSION), pp. 1-8, Ottawa, Canada. ieeexplore.ieee.org/document/9011433

  • Duník, J., Straka, O., & Blasch, E. (2019). Solution Separation Unscented Kalman Filter. In Proceedings of the 2019 22th International Conference on Information Fusion (FUSION), pp. 1-8, Ottawa, Canada. ieeexplore.ieee.org/document/9011214

  • Punčochář, I. & Taufer, P. (2019). Estimation of train speed and traveled distance using odometry and partial IMU. In Proceeding of the 15th European Workshop on Advanced Control and Diagnosis, Bologna.

  • Havlík, J. & Straka, O. (2019). Measures of Nonlinearity and non-Gaussianity in Orbital Uncertainty Propagation. In Proceedings of the 2019 22th International Conference on Information Fusion (FUSION), pp. 1-8, Ottawa, Canada. ieeexplore.ieee.org/document/9011445

  • Krejčí, J. & Straka, O. (2019). Adaptive Gaussian Mixture Method for Uncertainty Propagation in Space Surveillance. In Proceeding of the 15th European Workshop on Advanced Control and Diagnosis, Bologna. www.researchgate.net/publication/337544932_Adaptive_Gaussian_Mixture_Method_for_Uncertainty_Propagation_in_Space_Surveillance

  • Bouček, Z. & Flídr, M. (2019). Explicit Interpolating Control of Unmanned Aerial Vehicle. In Proceedings of 24th International Conference on Methods and Models in Automation & Robotics, pp. 384-389, Miedzyzdroje, https://doi.org/10.1109/MMAR.2019.8864719

  • Duník, J. & Straka, O. (2019). Rao-Blackwellised Point-Mass Smoothers for a Class of Conditionally Linear Dynamic Models. In Proceedings of the 2019 22th International Conference on Information Fusion (FUSION), pp. 1-8, Ottawa, Canada. https://ieeexplore.ieee.org/document/9011246

  • Ajgl, J. & Straka, O. (2019). Rectification of Partitioned Covariance Intersection. In Proceedings of the 2019 American Control Conference (ACC), pp. 5786-5791 , Philadelphia, USA. https://doi.org/10.23919/ACC.2019.8814466

  • Matoušek, J., Duník, J., & Straka, O. (2019). Point-Mass Filter: Density Specific Grid Design and Implementation. In Proceedings of the 15th European Workshop on Advanced Control and Diagnosis, Bologna. www.researchgate.net/publication/337534568_Point-Mass_Filter_Density_Specific_Grid_Design_and_Implementation

  • Král, L., Polóni, T., & Vágner, M. (2019). Identification of MEMS Gyroscope Structure Using Frequency Response Data. In Proceeding of the 15th European Workshop on Advanced Control and Diagnosis, Bologna.

  • Punčochář, I. & Straka, O. (2019). Non-centralized active fault diagnosis for stochastic systems. In Proceedings of the 2019 American Control Conference (ACC), pp. 5052-5057 , Philadelphia, USA. doi.org/10.23919/ACC.2019.8814809

  • Havlík, J., Straka, O., Hanebeck, U.D., (2018). Stochastic Integration Filter: Theoretical and Implementation Aspects. In Proceedings of the 2018 21st International Conference on Information Fusion (FUSION) (pp. 1638-1645). Cambridge, UK. doi.org/10.23919/ICIF.2018.8455586

  • Radtke, S., Noack, B., Hanebeck, U.D., Straka, O. (2018). Reconstruction of Cross-Correlations with Constant Number of Deterministic Samples. In Proceedings of the 2018 21st International Conference on Information Fusion (FUSION) (pp. 1638-1645). Cambridge, UK. doi.org/10.23919/ICIF.2018.8455221

  • Neduchal, P., Flídr, M., & Železný, M. (2018). In Fast Frontier Detection Approach in Consecutive Grid Maps. In Lecture Notes in Computer Science book series (pp. 192-201). Cham, Switzerland: Springer.

  • Kost, O., Duník, J. & Straka, O. (2018). Noise Moment and Parameter Estimation of State-Space Model. In Proceedings of the 18th IFAC Symposium on System Identification (SYSID 2018) (pp. 891-896). Stockholm, Sweden. doi.org/10.1016/j.ifacol.2018.09.107

  • Duník, J., Kost, O., Straka, O. & Blasch, E. (2018). State and Measurement Noise in Positioning and Tracking: Covariance Matrices Estimation and Gaussianity Assessment. In Proceedings of the 2018 IEEE/ION Position, Location and Navigation Symposium (PLANS) (pp. 1326-1335). Monterey, USA. doi.org/10.1109/PLANS.2018.8373523

  • Punčochář, I. & Škach, J. (2018). A Survey of Active fault Diagnosis Methods. In IFAC-PapersOnLine, 51(24) (pp. 1091-1098). doi.org/10.1016/j.ifacol.2018.09.726

  • Straka, O. & Duník, J. (2018). Entropy-based Consistency Monitoring for Stochastic Integration Filter. In Proceedings of the 21st International Conference on Information Fusion (FUSION 2018), (pp. 1676-1683), Cambridge, UK. doi.org/10.23919/ICIF.2018.8455462

  • Ajgl, J., & Straka, O. (2018). Comparison of Fusions Under Unknown and Partially Known Correlations. In Proceedings of the 7th IFAC Workshop on Distributed Estimation and Control in Networked Systems, Elsevier, (pp. 295-300).

  • Punčochář, I., & Straka, O. (2018). Multiple-model Active Fault Diagnosis with Deferred Decisions. Accepted to the 57th IEEE Conference on Decision and Control (CDC).

  • Kost, O., Duník, J., & Straka, O. (2018). Correlated Noise Characteristics Estimation for Linear Time-Varying Systems. Accepted to the 57th IEEE Conference on Decision and Control (CDC).

  • Ajgl, J. & Straka, O. (2018). Analysis of Partial Knowledge of Correlations in an Estimation Fusion Problem. In Proceedings of the 21st International Conference on Information Fusion (FUSION 2018), (pp. 100-107), Cambridge, UK. doi.org/10.23919/ICIF.2018.8455770

  • Kost, O., Duník, J. & Straka, O. (2018). Estimation of Noise Means and Covariance Matrices for Linear Time-Varying Models. In Proceedings of the American Control Conference (ACC), (pp. 265-271), Milwauke, USA. doi.org/10.23919/ACC.2018.8430851

  • Malinák, P., Soták, M., Kana, Z., Baránek, R.,& Duník, J. (2018). Pure-inertial AHRS with adaptive elimination of non-gravitational vehicle acceleration. In Proceedings of the 2018 IEEE/ION Position, Location and Navigation Symposium (PLANS) (pp. 696-707). Monterey, USA. doi.org/10.1109/PLANS.2018.8373445

  • Havlík, J., Straka, O., Duník, J., & Ajgl, J. (2018). Stochastic Integration Filter with Improved State Estimate Mean-Square Error Computation. Informatics in Control, Automation and Robotics, 430: 423–439. doi:10.1007/978-3-319-55011-4_21

  • Fehér, M., Straka, O., Šmídl, V., & Janouš, Š. (2017). Constrained time-optimal control of PMSM with continuous control domain. In Proceedings of the 2017 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE) (pp. 42-47). Pilsen, Czech Republic. ISBN: 978-1-5386-0507-3, ieeexplore.ieee.org/document/8071266

  • Ajgl, J. & Straka, O. (2017). On Weak Points of the Ellipsoidal Intersection Fusion. In Proceedings of the IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2017) (pp. 28-33). Daegu, South Korea. doi:10.1109/MFI.2017.8170403

  • Fehér, M., Straka, O., & Šmídl, V. (2017). Efficient MPC for permanent magnet synchronous motor. In Proceedings of the 25th Mediterranean Conference on Control and Automation (pp. 36 – 41). Valletta, Malta. doi:10.1109/MED.2017.7984092

  • Bouček, Z., Straka, O., & Flídr, M. (2017). Attitude Estimation for Quadrotor UAV by Unscented Kalman Filter. In Proceedings of the 14th European Workshop on Advanced Control and Diagnosis. Buccharest, Romania.

  • Fehér, M., Straka, O., & Šmídl, V. (2017). Oscillation Reduction for Time-Optimal Control of Permanent Magnet Synchronous Motor. In Proceedings of the 14th European Workshop on Advanced Control and Diagnosis. Buccharest, Romania.

  • Punčochář, I., Straka, O. & Taufer, J. (2017). Locomotive position and speed estimation in post-processing mode. In Proceedings of the 14th European Workshop on Advanced Control and Diagnosis. Bucharest, Romania.

  • Ajgl, J. & Straka, O. (2017). A Geometrical Perspective on Fusion under Unknown Correlations based on Minkowski Sums. In Proceedings of the 20th International Conference Information Fusion (FUSION 2017) (pp. 1-8). Xi'an, China. doi:10.23919/ICIF.2017.8009722

  • Duník, J., Straka, O., Ajgl, J. & Blasch, E. (2017). From Competitive to Cooperative Filter Design. In Proceedings of the 20th International Conference Information Fusion (FUSION 2017) (pp. 1-9). Xi'an, China. doi:10.23919/ICIF.2017.8009652

  • Duník, J., Straka, O., & García-Fernández, Á. F. (2017). Performance Evaluation of Nonlinearity and Non-Gaussianity Measures in State Estimation. In Proceeding of the 20th International Conference Information Fusion (FUSION 2017) (pp. 1-10). Xi'an, China. doi:10.23919/ICIF.2017.8009699

  • Prüher, J., Tronarp, F., Karvonen, T., Särkkä, S., & Straka, O. (2017). Student-t Process Quadratures for Filtering of Non-Linear Systems with Heavy-Tailed Noise. In Proceedings of the 20th International Conference Information Fusion (FUSION 2017) (pp. 1-8). Xi'an, China. doi:10.23919/ICIF.2017.8009742

  • Straka, O. & Duník, J. (2017). Stochastic Integration Student’s-t Filter. In Proceedings of the 20th International Conference Information Fusion (FUSION 2017) (pp. 1-8). Xi'an, China. doi:10.23919/ICIF.2017.8009741

  • Kost, O., Duník, J., & Straka, O. (2017). Noise Covariance Matrix Estimation in Navigation and Tracking: Impact of Linearisation Error. In Proceedings of the 56th IEEE Conference on Decision and Control (pp. 958-964). Melbourne, Australia. doi:10.1109/CDC.2017.8263782

  • Škach, J., Straka, O., & Punčochář, I. (2017). Efficient Active Fault Diagnosis Using Adaptive Particle Filter. In Proceedings of the 56th IEEE Conference on Decision and Control (pp. 5732-5738). Melbourne, Australia. doi:10.1109/CDC.2017.8264525

  • Král, L. & Straka, O. (2017). Nonlinear Estimator Design for MEMS Gyroscope with Time-varying Angular Rate. In Proceedings of the 20th World Congress of IFAC (pp. 3195–3201). Tolouse, France: Elsevier Ltd. doi:10.1016/j.ifacol.2017.08.433

  • Škach, J. & Punčochář, I. (2017). Input Design for Fault Detection Using Extended Kalman Filter and Reinforcement Learning. In Proceedings of the 20th World Congress of IFAC (pp. 7302–7307). Tolouse, France: Elsevier Ltd. doi:10.1016/j.ifacol.2017.08.1461

  • Škach, J., Punčochář, I., & Straka, O. (2017). Active Fault Diagnosis for Jump Markov Nonlinear Systems. In Proceedings of the 20th World Congress of IFAC (pp. 7308–7313). Tolouse, France: Elsevier Ltd. doi:10.1016/j.ifacol.2017.08.1465

  • Duník, J., Straka, O., & Kost, O. (2016). Measurement Difference Autocovariance Method for Noise Covariance Matrices Estimation. In Proceedings of the 55th IEEE Conference on Decision and Control (CDC). Las Vegas, NV, USA. doi: 10.1109/CDC.2016.7798296

  • Škach, J., Punčochář, I., & Lewis, F.L. (2016). Optimal Active Fault Diagnosis by Temporal-Difference Learning. In Proceedings of the 55th IEEE Conference on Decision and Control (CDC). Las Vegas, NV, USA. doi:10.1109/CDC.2016.7798581

  • Fehér, M., Straka, O., & Šmídl, V. (2016). Constrained time-optimal control of double-integrator system and its application in MPC. In Proceedings of the 13th European Workshop on Advanced Control and Diagnosis. Lille, France. doi:10.1088/1742-6596/783/1/012024

  • Kost, O., Duník, J., & Straka, O. (2016). Noise Covariance Matrices Estimation for Systems with Time-Varying Availability of Sensors. In Proceedings of the 13th European Workshop on Advanced Control and Diagnosis. Lille, France. doi:10.1088/1742-6596/783/1/012059

  • Neduchal, P. & Flídr, M. (2016). Development of a Laboratory Framework for Testing Simultaneous Localization and Mapping Approaches. In Proceeings of the 14th IFAC International Conference on Programmable Devices and Embedded Systems (PDeS 2016) (pp. 316-321). Lednice, Czech Republic. doi:10.1016/j.ifacol.2016.12.089

  • Škach, J., Punčochář, I., & Lewis, F.L. (2016). Temporal-Difference Q-learning in Active Fault Diagnosis. In Proceedings of the 2016 3rd Conference on Control and Fault-Tolerant Systems (SysTol) (pp. 281-286). Barcelona, Spain. doi:10.1109/SYSTOL.2016.7739765

  • Ajgl, J. & Straka, O. (2016). Covariance Intersection in Track-to-Track Fusion With Memory. In Proccedings of the 2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2016) (pp. 359-364). Baden-Baden, Germany. doi:10.1109/MFI.2016.7849514

  • Ajgl, J. & Straka, O. (2016). Covariance Intersection in Track-to-Track Fusion Without Memory. In Proceeding of the 19th International Conference Information Fusion (FUSION 2016) (pp. 1-8). Heidelberg, Germany.

  • Straka, O. & Duník, J. (2016). Characteristic Function Based Performance Index for Bayesian Filters. In Proceeding of the 19th International Conference Information Fusion (FUSION 2016) (pp. 1-8). Heidelberg, Germany.

  • Straka, O., Mallick, M., & Blasch, E. (2016). Survey of Nonlinearity and Non-Gaussianity Measures for State Estimation. In Proceeding of the 19th International Conference Information Fusion (FUSION 2016) (pp. 1-8). Heidelberg, Germany.

  • Havlík, J., Straka, O., Duník, J., & Ajgl, J. (2016). On Nonlinearity Measuring Aspects of Stochastic Integration Filter. In Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics (ICINCO), 2016 (pp. 353-361). Lisabon, Portugal. doi:10.5220/0005983903530361

  • Prüher, J. & Särkkä, S. (2016). On the Use of Gradient Information in Gaussian Process Quadratures. In Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing 2016 (pp. 1-6). Salerno, Italy. doi:10.1109/MLSP.2016.7738903

  • Straka, O., Duník. J., & Punčochář, I. (2016). Directional Splitting for Structure Adaptation of Bayesian Filters. In Proceedings of the 2016 American Control Conference (pp. 2705-2710). Boston, MA, USA. doi:10.1109/ACC.2016.7525327

  • Bouček, Z. & Flídr, M. (2016). Impact of multiple accelerometer IMU employment on the orientation estimate quality. In Proceedings of the 17th International Carpathian Control Conference (pp. 91-96). Tatranská Lomnica, Slovakia. doi:10.1109/CarpathianCC.2016.7501073

  • Straka, O., Duník, J., & Šimandl, M. (2015). Structure Adaptation of Nonlinear Filters based on Non-Gaussianity Measures. In Proceedings of the American Control Conference 2015 (pp. 3162-3167). Chicago, Illinois, USA. doi:10.1109/ACC.2015.7171819

  • Ajgl, J., & Šimandl, M. (2015). Design of a Robust Fusion of Probability Densities. In Proceedings of the American Control Conference 2015 (pp. 4204-4209). Chicago, Illinois, USA. doi:10.1109/ACC.2015.7171989

  • Duník, J., Straka, O., Šimandl, M., Kost, O., Ajgl, J., Soták, M., Baránek, R., & Kaňa, Z. (2015). Estimation of State and Measurement Noise Characteristics. In Proceeding of the 18th International Conference Information Fusion (FUSION 2015) (pp. 1817-1824). Washington, DC, USA.

  • Straka, O., Duník, J., & Šimandl, M. (2015). Design of Discrete Second Order Filters for Continuous-Discrete Models. In Proceeding of the 18th International Conference Information Fusion (FUSION 2015) (pp. 1825-1832). Washington, DC, USA.

  • Ajgl, J., Šimandl, M., & Duník, J. (2015). Approximation of Powers of Gaussian Mixtures. In Proceeding of the 18th International Conference Information Fusion (FUSION 2015) (pp. 878-885). Washington, DC, USA.

  • Prüher, J., & Šimandl, M. (2015). Bayesian Quadrature in Nonlinear Filtering. In Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics (ICINCO), 2015 (pp. 380-387). Colmar, Alsace, France.

  • Fehér, M., Punčochář, I., & Šimandl, M. (2015). Use of Multiple Model Change Detection for Crack Detection in Euler-Bernoulli Beam. In Proceedings of the 20th International Conference on Methods & Models in Automation & Robotics (MMAR 2015) (pp. 163-168). Miedzyzdrojie, Poland. doi:10.1109/MMAR.2015.7283865

  • Flídr, M., & Šimandl, M. (2015). A Simplified Parametrization of the Criterion for the Prediction Error Dual Controller. In Proceedings of the 20th International Conference on Methods & Models in Automation & Robotics (MMAR 2015) (pp. 671-676). Miedzyzdrojie, Poland. doi:10.1109/MMAR.2015.7283955

  • Král, L., & Šimandl, M. (2015). Parameter Estimation of MEMS Gyroscope Using Local State Estimation Methods. Proceedings of the 17th IFAC Symposium on System Identification (SYSID 2015) (pp. 279–284). Beijing, China. doi:10.1016/j.ifacol.2015.12.139

  • Duník, J., Straka, O., & Šimandl, M. (2015). Estimation of Noise Covariance Matrices for Linear Systems with Nonlinear Measurements Measures. Proceedings of the 17th IFAC Symposium on System Identification (SYSID 2015) (pp. 1130–1135). Beijing, China. doi:10.1016/j.ifacol.2015.12.283

  • Havlík, J., Šimandl, M., & Straka, M. (2015). A new practically oriented generation of nonlinear filtering toolbox. Proceedings of the 17th IFAC Symposium on System Identification (SYSID 2015) (pp. 1070–1075). Beijing, China. doi:10.1016/j.ifacol.2015.12.273

  • Franče, Z., Punčochář, I., & Šimandl, M. (2015). Effect of Optimal Control on Fuel Savings of Parallel Hybrid Electric Vehicle. Proceedings of the 2015 IEEE Vehicle Power and Propulsion Conference (VPPC 2015) (pp. 1-6). Montreal, Quebec, Canada: IEEE. doi:10.1109/VPPC.2015.7352936

  • Prüher, J., & Král, L. (2015). Functional Dual Adaptive Control with Recursive Gaussian Process Model. Journal of Physics: Conference Series, 659(1), 1–11. doi:10.1088/1742-6596/659/1/012006

  • Havlík, J., & Straka, O. (2015). Performance evaluation of iterated extended Kalman filter with variable step-length. Journal of Physics: Conference Series, 659(1), 1–12. doi:10.1088/1742-6596/659/1/012022

  • Kost, O., Straka, O, & Duník, J. (2015). Identification of State and Measurement Noise Covariance Matrices using Nonlinear Estimation Framework. Journal of Physics: Conference Series, 659(1), 1–12. doi:10.1088/1742-6596/659/1/012057

  • Škach, J., & Punčochář, I. (2015). Active fault detection: A comparison of probabilistic methods. Journal of Physics: Conference Series, 659(1), 1–12. doi:10.1088/1742-6596/659/1/012046

  • Punčochář, I., Škach, J., & Šimandl, M. (2015). Adaptive Generalized Policy Iteration in Active Fault Detection and Control. In Proceedings of the 9th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes (SAFEPROCESS 2015) (pp. 505–510). Paris, France: IFAC. doi:10.1016/j.ifacol.2015.09.576

  • Punčochář, I., Škach, J., & Šimandl, M. (2015). Infinite Time Horizon Active Fault Diagnosis based on Approximate Dynamic Programming. In Proceedings of the 54th IEEE Conference on Decision and Control (CDC 2015) (pp. 4456-4461). Osaka, Japan: IEEE. doi:10.1109/CDC.2015.7402915

  • Straka, O., Duník, J., & Šimandl, M. (2014). Performance diagnosis of local filters in state estimation of nonlinear systems. Journal of Physics: Conference Series, 570(1), 1–12. doi:10.1088/1742-6596/570/1/012004

  • Škach, J., Punčochář, I., & Šimandl, M. (2014). Approximate active fault detection and control. Journal of Physics: Conference Series, 570(1), 1–9. doi:10.1088/1742-6596/570/7/072003

  • Prüher, J., & Šimandl, M. (2014). Gaussian process based recursive system identification. Journal of Physics: Conference Series, 570(1), 1–9. doi:10.1088/1742-6596/570/1/012002

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  • Král, L.; Hering, P.; Šimandl, M. (2009) Functional Adaptive Control for Nonlinear Stochastic Systems in Presence of Outliers. In: Proceeding of the 15th IFAC Symposium on System Identification, 2009, s. 1505-1510. ISSN: 1474-6670

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  • Straka, O.; Šimandl, M. (2009) A Survey of Sample Size Adaptation Techniques for Particle Filters. In: Proceeding of the 15th IFAC Symposium on System Identification, 2009, s. 1358-1363. ISSN: 1474-6670

  • Král, L.; Punčochář, I.; Šimandl, M. (2009) Functional Dual Control for Slowly Time Variant Stochastic Systems. In Proceedings of the 7th Workshop on Advanced Control and Diagnosis. Neuveden : University of Zielona Góra, Poland

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  • Šimandl, M.; Straka, O. (2008): Functional sampling density design for particle filters. In Signal Processing. 2008, roč.2008, sv.88, č.11, s.2784-2789, ISSN 0165-1684.

  • Flídr, M.; Šimandl, M.; Král, L. (2008): Multistage Prediction Error Adaptive Dual Controller. In Proceedings of the 11th IASTED International Confernece on Inteligent Systems and Control. Calgary : ACTA Press, 2008. s. 14-19. ISBN 978-0-88986-778-9.

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  • Hering, P.; Šimandl, M. (2007): Gaussian Sum Approach with Optimal Experiment Design for Neural Network. In Proceedings of the Ninth IASTED International Conference on Signal and Image Processing. Honolulu : ACTA Press, 2007. s. 425-430. ISBN 978-0-88986-676-8.

  • Křenek, J.; Král, L.; Šimandl, M. (2007): Dual model for FARMAX models. In The 1st Young Researchers Conference on Applied Sciences. Plzeň : Západočeská univerzita, 2007. s. 201-205. ISBN 978-80-7043-574-8.

  • Křenek, J.; Šimandl, M.; Král, L. (2007): Dual Control for ARX Models. In Proceedings of 8th International Carpathian Control Conference ICCC'2007. Košice : Technical University, BERG Faculty, 2007. s. 385-388. ISBN 978-80-8073-805-1.

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  • Šimandl, M.; Straka, O. (2007): Sampling Densities of Particle Filter: A Survey and Comparison. In Proceedings of the 2007 American Control Conference. New York : AACC, 2007. s. 4437-4442. ISBN 1-4244-0989-6. ISSN 0743-1619.

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  • Šimandl M., Královec J. , Söderström T. (2006): Advanced point - mass method for nonlinear state estimation, Automatica 42, Issue 7, 1133-1145.

  • Flídr M., Duník J., Straka O., Švácha J., Šimandl M. (2006): Framework for implementing and testing nonlinear filters. In: Proceedings of the 7th IFAC Symposium on Advances in Control Education, 21-23 June, Madrid, Spain.

  • Švácha J., Šimandl M., Straka O., Flídr M. (2006): Nonlinear filtering toolbox for continuous stochastic systems with discrete measurements. In: Proceedings of the 7th IFAC Symposium on Advances in Control Education, 21-23 June, Madrid, Spain.

  • Straka O., Šimandl M. (2006): Particle filter adaptation based on efficient sample size. In: Preprints of the 14th IFAC Symposium on System Identification, Newcastle, Australia, pp. 991-996.

  • Šimandl M., Duník J. (2006): Design of derivative-free smoothers and predictors. In: Preprints of the 14th IFAC Symposium on System Identification, Newcastle, Australia, pp. 1240-1245.

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  • Šimandl M., Král L. (2006): Neural adaptive dual controller with dynamic structure. In: Proceedings of the 7th Portuguese Conference on Automatic Control, 11 -13 September, Lisboa, Portugal.

  • Hering P., Šimandl M. (2006): Gaussian sum based methods for neural network parameters estimation: aspects and comparison. In: Proceedings of the 7th Portuguese Conference on Automatic Control, 11 -13 September, Lisboa, Portugal.

  • Duník J., M. Šimandl, O. Straka and M. Flídr (2005). Performance analysis of derivative free filters, In: Proceedings of 44th IEEE Conference on Decision and Control and European Control Conference ECC 2005, Sevilla, 12.-15. December.

  • Šimandl M., I. Punčochář. and J. Královec (2005). Rolling horizon for active fault detection, In: Proceedings of 44th IEEE Conference on Decision and Control and European Control Conference ECC 2005, Sevilla, 12.-15. December.

  • Flídr, M. and M. Šimandl (2005). Prediction error dual controller. In: Proceedings of the eighth IASTED international conference on Intelligent systems and control . Anaheim : ACTA Press, s. 253-258. ISBN 0-88986-517-5

  • Šimandl, M. and P. Hering (2005). Recursive parameters estimation and structure adaptation of neural network. In: Proceedings of the eighth IASTED international conference on Intelligent systems and control. Anaheim : ACTA Press, s. 78-83. ISBN 0-88986-517-5

  • Lešek, M., M. Šimandl (2005). Pension Fund State Estimation and Optimal Investment Strategy. In:Bulletin of the Czech Econometric Society, Vol. 12, Issue 22.

  • Straka, O. and M. Šimandl (2005). Distance-based pruning for Gaussian sum method in non-Gaussian system state estimation. In: Proceedings of the eighth IASTED international conference on Intelligent systems and control. Anaheim : ACTA Press, s. 96-101. ISBN 0-88986-517-5

  • Šimandl M. and J. Švácha (2005). Separation approach for numerical solution of the Fokker-Planck equation in estimation problem, In: Preprints of the 16th IFAC World Congress, July 4-8, Prague, Czech Republic.

  • Straka O. and M. Šimandl (2005). Using the Bhattacharyya distance in functional sampling density of particle filter, In: Preprints of the 16th IFAC World Congress, July 4-8, Prague, Czech Republic.

  • Šimandl M., Punčochář I. and P. Herejt (2005). Optimal input and decision in multiple model fault detection, In: Preprints of the 16th IFAC World Congress, July 4-8, Prague, Czech Republic.

  • Šimandl M., Lešek M. and O. Straka (2005). Pension fund model design and state estimation, In: Preprints of the 16th IFAC World Congress, July 4-8, Prague, Czech Republic.

  • Královec J. and M. Šimandl (2005). Numerical solution of filtering problem with multimodal densities, In: Preprints of the 16th IFAC World Congress, July 4-8, Prague, Czech Republic.

  • Šimandl M., Král L., and P. Hering (2005). Neural network based bicriterial dual control of nonlinear systems, In: Preprints of the 16th IFAC World Congress, July 4-8, Prague, Czech Republic.

  • Flídr M. and M. Šimandl (2005). Bicriterial dual control with multiple linearization, In: Preprints of the 16th IFAC World Congress, July 4-8, Prague, Czech Republic.

  • Šimandl M. and J. Duník (2005). Sigma point gaussian sum filter design using square root unscented filters, In: Preprints of the 16th IFAC World Congress, July 4-8, Prague, Czech Republic.

  • Královec J. and M. Šimandl (2004). Filtering, Prediction and Smoothing with Point-Mass Approach, In: Preprints of the16th IFAC Symposium on Automatic control in Aerospace, June 14 - 18, St. Petersburg, Russia.

  • Straka O. and M. Šimandl (2004). Sample Size Adaptation for Particle Filters, In: Preprints of the16th IFAC Symposium on Automatic control in Aerospace, June 14 - 18, St. Petersburg, Russia.

  • Šimandl M., Hering P., L. Král (2004). Identification of Nonlinear Nongaussian Systems by Neural Networks. In: Preprints of the 6th IFAC Symposium on Nonlinear Control Systems, 1-3 September, Stuttgart, Germany.

  • Šimandl M. and J. Královec (2003). Multigrid Design in Point-mass Approach to Nonlinear State Estimation. Proceedings of the 13th IFAC Symposium on System Identification SYSID, August, Rotterdam, Netherlands.

  • Šimandl M. and O. Straka (2003). Sampling Density Design for Particle Filters. Proceedings of the 13th IFAC Symposium on System Identification SYSID, August, Rotterdam, Netherlands.

  • Šimandl M., Herejt, P.(2003).Information Processing Strategies and Multiple Model for Detection. Proceedings of the 22nd IASTED conference on Modelling, Identification and Control MIC, February, Innsbruck, Austria.

  • Šimandl M. and O. Straka (2003).Nonlinear Filtering Methods: Some Aspects and Performance Evaluation. Proceedings of the 22nd IASTED conference on Modelling, Identification and Control MIC, February, Innsbruck, Austria.

  •  Šimandl M., Královec J.(2002). Cramér-Rao Bound for Stochastic Volatility Model.Preprints of the 15th Triennial World Congress of the IFAC, Barcelona, [CD-ROM]. Oxford : Elsevier Science.

  • Šimandl M.,, Straka, O.(2002). Nonlinear Estimation by Particle Filters and Cramér-Rao Bound. Preprints of the 15th Triennial World Congress of the IFAC, Barcelona, [CD-ROM]. Oxford : Elsevier Science.