The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Dans cet article, un nouveau filtre à maximum de vraisemblance avec des structures de réponse impulsionnelle finie (FIR) est proposé pour les modèles de signaux dans l'espace d'état avec à la fois des bruits de système et d'observation. Ce filtre est appelé filtre FIR (MLF) à maximum de vraisemblance. Le filtre MLF proposé ne nécessite pas a priori informations sur l'état initial de la fenêtre et traite linéairement les observations finies sur la fenêtre la plus récente. Le filtre MLF proposé est d'abord représenté sous forme de lots, puis sous forme itérative pour un avantage informatique. Le filtre MLF proposé possède de bonnes propriétés inhérentes telles que l'invariance temporelle, l'impartialité, le mauvais état d'exécution et la robustesse. La validité du filtre MLF proposé est illustrée par une simulation informatique sur un signal sinusoïdal.
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PyungSoo KIM, "Maximum Likelihood FIR Filter for State Space Signal Models" in IEICE TRANSACTIONS on Communications,
vol. E85-B, no. 8, pp. 1604-1607, August 2002, doi: .
Abstract: In this paper, a new maximum likelihood filter with finite impulse response (FIR) structures is proposed for state space signal models with both system and observation noises. This filter is called the maximum likelihood FIR (MLF) filter. The proposed MLF filter doesn't require a priori information of the window initial state and processes the finite observations on the most recent window linearly. The proposed MLF filter is first represented in a batch form, and then in an iterative form for computational advantage. The proposed MLF filter has good inherent properties such as time-invariance, unbiasedness, deadbeat, robustness. The validity of the proposed MLF filter is illustrated by a computer simulation on a sinusoidal signal.
URL: https://global.ieice.org/en_transactions/communications/10.1587/e85-b_8_1604/_p
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@ARTICLE{e85-b_8_1604,
author={PyungSoo KIM, },
journal={IEICE TRANSACTIONS on Communications},
title={Maximum Likelihood FIR Filter for State Space Signal Models},
year={2002},
volume={E85-B},
number={8},
pages={1604-1607},
abstract={In this paper, a new maximum likelihood filter with finite impulse response (FIR) structures is proposed for state space signal models with both system and observation noises. This filter is called the maximum likelihood FIR (MLF) filter. The proposed MLF filter doesn't require a priori information of the window initial state and processes the finite observations on the most recent window linearly. The proposed MLF filter is first represented in a batch form, and then in an iterative form for computational advantage. The proposed MLF filter has good inherent properties such as time-invariance, unbiasedness, deadbeat, robustness. The validity of the proposed MLF filter is illustrated by a computer simulation on a sinusoidal signal.},
keywords={},
doi={},
ISSN={},
month={August},}
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TY - JOUR
TI - Maximum Likelihood FIR Filter for State Space Signal Models
T2 - IEICE TRANSACTIONS on Communications
SP - 1604
EP - 1607
AU - PyungSoo KIM
PY - 2002
DO -
JO - IEICE TRANSACTIONS on Communications
SN -
VL - E85-B
IS - 8
JA - IEICE TRANSACTIONS on Communications
Y1 - August 2002
AB - In this paper, a new maximum likelihood filter with finite impulse response (FIR) structures is proposed for state space signal models with both system and observation noises. This filter is called the maximum likelihood FIR (MLF) filter. The proposed MLF filter doesn't require a priori information of the window initial state and processes the finite observations on the most recent window linearly. The proposed MLF filter is first represented in a batch form, and then in an iterative form for computational advantage. The proposed MLF filter has good inherent properties such as time-invariance, unbiasedness, deadbeat, robustness. The validity of the proposed MLF filter is illustrated by a computer simulation on a sinusoidal signal.
ER -