# Kalman filter with impulse noised outliers : A robust sequential algorithm to filter data with a large number of outliers

@inproceedings{Cloez2022KalmanFW, title={Kalman filter with impulse noised outliers : A robust sequential algorithm to filter data with a large number of outliers}, author={Bertrand Cloez and B{\'e}n{\'e}dicte Fontez and Eliel Gonz'alez Garc'ia and Isabelle Sanchez}, year={2022} }

. Impulse noised outliers are data points that diﬀers signiﬁcantly from other observations. They are generally removed from the data set through local regression or Kalman ﬁlter algorithm. However, these methods, or their generalizations, are not well suited when the number of outliers is of the same order as the number of low-noise data. In this article, we propose a new model for impulse noised outliers based on simple latent linear Gaussian processes as in the Kalman Filter. We present a…

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