Quadratic estimation from non-independent uncertain observations with coloured noise.

Nakamori, S., et al. "Quadratic estimation from non-independent uncertain observations with coloured noise.." Extracta Mathematicae 19.3 (2004): 399-413. <http://eudml.org/doc/38754>.

@article{Nakamori2004,
abstract = {Recursive least-squares quadratic filtering and fixed-point smoothing algorithms for signal estimation from uncertain observations are derived when the uncertainty is modeled by not necessarily independent variables and the observations contain white plus coloured noise. The proposed estimators do not require the knowledge of the state-space of the model generating the signal, but only the moments, up to the fourth one, of the processes involved, along with the probability that the signal exists in the obervations and the (2,2)-element of the conditional probability matrix of the sequence describing the uncertainty.},
author = {Nakamori, S., Caballero, R., Hermoso, A., Jiménez, J., Linares, J.},
journal = {Extracta Mathematicae},
keywords = {Procesos estocásticos; Procesamiento de señal; Filtrado; Estimación},
language = {eng},
number = {3},
pages = {399-413},
title = {Quadratic estimation from non-independent uncertain observations with coloured noise.},
url = {http://eudml.org/doc/38754},
volume = {19},
year = {2004},
}

TY - JOUR
AU - Nakamori, S.
AU - Caballero, R.
AU - Hermoso, A.
AU - Jiménez, J.
AU - Linares, J.
TI - Quadratic estimation from non-independent uncertain observations with coloured noise.
JO - Extracta Mathematicae
PY - 2004
VL - 19
IS - 3
SP - 399
EP - 413
AB - Recursive least-squares quadratic filtering and fixed-point smoothing algorithms for signal estimation from uncertain observations are derived when the uncertainty is modeled by not necessarily independent variables and the observations contain white plus coloured noise. The proposed estimators do not require the knowledge of the state-space of the model generating the signal, but only the moments, up to the fourth one, of the processes involved, along with the probability that the signal exists in the obervations and the (2,2)-element of the conditional probability matrix of the sequence describing the uncertainty.
LA - eng
KW - Procesos estocásticos; Procesamiento de señal; Filtrado; Estimación
UR - http://eudml.org/doc/38754
ER -