Search Results - Šimandl, M

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  1. 1
    Efficient adaptation of design parameters of derivative-free filters

    Efficient adaptation of design parameters of derivative-free filters by Šimandl, M., Straka, O., Duník, J.

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  2. 2
    Functional adaptive controller for multivariable stochastic systems with dynamic structure of neural network

    Functional adaptive controller for multivariable stochastic systems with dynamic structure of neural network by Kral, L, Simandl, M

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  3. 3
    Stochastic Integration Filter

    Stochastic Integration Filter by Dunik, J., Straka, O., Simandl, M.

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  4. 4
    Anticipative grid design in point-mass approach to nonlinear state estimation

    Anticipative grid design in point-mass approach to nonlinear state estimation by Simandl, M., Kralovec, J., Soderstrom, T.

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  5. 5
    Unscented Kalman Filter: Aspects and Adaptive Setting of Scaling Parameter

    Unscented Kalman Filter: Aspects and Adaptive Setting of Scaling Parameter by Dunik, J., Simandl, M., Straka, O.

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  6. 6
    Filtering, predictive, and smoothing Cramér–Rao bounds for discrete-time nonlinear dynamic systems

    Filtering, predictive, and smoothing Cramér–Rao bounds for discrete-time nonlinear dynamic systems by Šimandl, Miroslav, Královec, Jakub, Tichavský, Petr

    Published in Automatica (Oxford)
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  7. 7
    Positioning Using GNSS Signals and Digital Maps

    Positioning Using GNSS Signals and Digital Maps by S imandl, M, Puncocha´r, I, S kach, J

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  8. 8
    Multitarget tracking performance analysis using the non-credibility index in the Nonlinear Estimation Framework (NEF) toolbox

    Multitarget tracking performance analysis using the non-credibility index in the Nonlinear Estimation Framework (NEF) toolbox by Blasch, E P, Straka, O, Duník, J, Šimandl, M

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  9. 9
    Particle based probability density fusion with differential Shannon entropy criterion

    Particle based probability density fusion with differential Shannon entropy criterion by Ajgl, J., Simandl, M.

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  10. 10
    Neural networks in local state estimation

    Neural networks in local state estimation by Kral, L., Simandl, M.

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  11. 11
    Gaussian sum unscented Kalman filter with adaptive scaling parameters

    Gaussian sum unscented Kalman filter with adaptive scaling parameters by Straka, O., Dunik, J., Simandl, M.

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  12. 12
    Sampling Densities of Particle Filter: A Survey and Comparison

    Sampling Densities of Particle Filter: A Survey and Comparison by Simandl, M., Straka, O.

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  13. 13
    Conservative merging of hypotheses given by probability densities

    Conservative merging of hypotheses given by probability densities by Ajgl, J., Simandl, M.

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  14. 14
    Scaling parameter in unscented transform: Analysis and specification

    Scaling parameter in unscented transform: Analysis and specification by Straka, O., Dunik, J., Simandl, M.

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  15. 15
    An optimization approach to resolve the competing aims of active fault detection and control

    An optimization approach to resolve the competing aims of active fault detection and control by Siroky, J., Simandl, M., Axehill, D., Puncochar, I.

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  16. 16
    Estimation of state and measurement noise characteristics

    Estimation of state and measurement noise characteristics by Dunik, J., Straka, O., Simandl, M., Kost, O., Ajgl, J., Sotak, M., Baranek, R., Kana, Z.

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  17. 17
    Performance evaluation of local state estimation methods in bearings-only tracking problems

    Performance evaluation of local state estimation methods in bearings-only tracking problems by Straka, O., Dunik, J., Simandl, M.

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  18. 18
    Measurement-to-track assignment methods in target tracking

    Measurement-to-track assignment methods in target tracking by Boucek, V., Simandl, M., Straka, O.

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  19. 19
    Randomized unscented Kalman filter in target tracking

    Randomized unscented Kalman filter in target tracking by Straka, O., Dunik, J., Simandl, M.

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  20. 20
    Gaussian mixtures proposal density in particle filter for track-before-detect

    Gaussian mixtures proposal density in particle filter for track-before-detect by Straka, O., Simandl, M., Dunik, J.

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