Adding a conditional-bias penalty to the Kalman filter, and adapting its strength, cuts tail-end estimation error by 20-30% in synthetic linear experiments, though the result relies on hand-tuned parameters.
Landslide deformation analysis by coupling deformation time series from SAR data with hydrological factors through data assimilation,
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Adaptive Conditional Bias-Penalized Kalman Filter for Improved Estimation of Extremes and its Approximation for Reduced Computation
Adding a conditional-bias penalty to the Kalman filter, and adapting its strength, cuts tail-end estimation error by 20-30% in synthetic linear experiments, though the result relies on hand-tuned parameters.