@inproceedings{9c0ef8ebcd2646839cf54fde261e4462,
title = "Bayesian approach of the skewed Kalman filter applied to an elastically supported structure",
abstract = "In a Bayesian Approach the Kalman filter can be regarded as recursive Bayesian estimator and be described as Bayesian dynamic network. The linear dynamic system discretized in the time domain follows a first order hidden Markov process where uncertainties in the system model and the measurement model are assumed to be Gaussian and modeled as uncorrelated white noise processes. As the assumption of linearity and Gaussianity is often violated a Bayesian approach of an extended skewed Kalman filter is derived which allows to consider a nonlinear dynamic system excited by a process with skew-normal probability distributions.",
author = "K. Runtemund and G. M{\"u}ller",
year = "2010",
language = "English",
series = "Proceedings of ISMA 2010 - International Conference on Noise and Vibration Engineering, including USD 2010",
publisher = "Katholieke Universiteit Leuven",
pages = "5335--5349",
editor = "P. Sas and B. Bergen",
booktitle = "Proceedings of ISMA 2010 - International Conference on Noise and Vibration Engineering, including USD 2010",
note = "24th International Conference on Noise and Vibration Engineering, ISMA 2010, in conjunction with the 3rd International Conference on Uncertainty in Structural Dynamics, USD 2010 ; Conference date: 20-09-2010 Through 22-09-2010",
}