CONTINUOUS-TIME SIGNAL FILTERING FROM NON-INDEPENDENT UNCERTAIN OBSERVATIONS

S. Nakamori, A. Hermoso-Carazo, J. Jiménez-López, J. Linares-Pérez

2004

Abstract

Filtering algorithms are presented as solution of the least mean-squared error linear estimation problem of continuous-time wide-sense stationary scalar signals from uncertain observations perturbed by white and coloured additive noises. These algorithms, one of them based on Chandrasekhar-type equations and the other on Riccati-type ones, are derived assuming a specific type of dependence between the Bernoulli random variables describing the uncertainty and do not require the whole knowledge of the state-space model. By comparing both algorithms it is deduced that the Chandrasekhar-type one is more advantageous from a computational viewpoint.

References

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Paper Citation


in Harvard Style

Nakamori S., Hermoso-Carazo A., Jiménez-López J. and Linares-Pérez J. (2004). CONTINUOUS-TIME SIGNAL FILTERING FROM NON-INDEPENDENT UNCERTAIN OBSERVATIONS . In Proceedings of the First International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO, ISBN 972-8865-12-0, pages 324-327. DOI: 10.5220/0001127703240327


in Bibtex Style

@conference{icinco04,
author={S. Nakamori and A. Hermoso-Carazo and J. Jiménez-López and J. Linares-Pérez},
title={CONTINUOUS-TIME SIGNAL FILTERING FROM NON-INDEPENDENT UNCERTAIN OBSERVATIONS},
booktitle={Proceedings of the First International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,},
year={2004},
pages={324-327},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001127703240327},
isbn={972-8865-12-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,
TI - CONTINUOUS-TIME SIGNAL FILTERING FROM NON-INDEPENDENT UNCERTAIN OBSERVATIONS
SN - 972-8865-12-0
AU - Nakamori S.
AU - Hermoso-Carazo A.
AU - Jiménez-López J.
AU - Linares-Pérez J.
PY - 2004
SP - 324
EP - 327
DO - 10.5220/0001127703240327