IEICE TRANSACTIONS on Fundamentals
Bayesian Formulation of Nonlinear Filters and Their Electronic Implementation
Summary :
Fundamental nonlinear filters including M-filters and order statistic filters are formulated generally by the maximum a-posteriori (MAP) estimation and some filters are derived with the aid of the Bayes formula. This MAP-filters reduces to M-filters if a-priori probability distribution is uniform, while the rank filters are derived when a-priori bias exists in the MAP estimation. This MAP-filters are implemented with an analog electronic circuit and the log-likelihood is shown to be a Liapunov function for the dynamics of this circuit.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E81-A No.2 pp.343-346
- Publication Date
- 1998/02/25
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- Category
- Analog Signal Processing
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Sadanobu YOSHIMOTO, Kiichi URAHAMA, "Bayesian Formulation of Nonlinear Filters and Their Electronic Implementation" in IEICE TRANSACTIONS on Fundamentals,
vol. E81-A, no. 2, pp. 343-346, February 1998, doi: .
Abstract: Fundamental nonlinear filters including M-filters and order statistic filters are formulated generally by the maximum a-posteriori (MAP) estimation and some filters are derived with the aid of the Bayes formula. This MAP-filters reduces to M-filters if a-priori probability distribution is uniform, while the rank filters are derived when a-priori bias exists in the MAP estimation. This MAP-filters are implemented with an analog electronic circuit and the log-likelihood is shown to be a Liapunov function for the dynamics of this circuit.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e81-a_2_343/_p
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@ARTICLE{e81-a_2_343,
author={Sadanobu YOSHIMOTO, Kiichi URAHAMA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Bayesian Formulation of Nonlinear Filters and Their Electronic Implementation},
year={1998},
volume={E81-A},
number={2},
pages={343-346},
abstract={Fundamental nonlinear filters including M-filters and order statistic filters are formulated generally by the maximum a-posteriori (MAP) estimation and some filters are derived with the aid of the Bayes formula. This MAP-filters reduces to M-filters if a-priori probability distribution is uniform, while the rank filters are derived when a-priori bias exists in the MAP estimation. This MAP-filters are implemented with an analog electronic circuit and the log-likelihood is shown to be a Liapunov function for the dynamics of this circuit.},
keywords={},
doi={},
ISSN={},
month={February},}
Copy
TY - JOUR
TI - Bayesian Formulation of Nonlinear Filters and Their Electronic Implementation
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 343
EP - 346
AU - Sadanobu YOSHIMOTO
AU - Kiichi URAHAMA
PY - 1998
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E81-A
IS - 2
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - February 1998
AB - Fundamental nonlinear filters including M-filters and order statistic filters are formulated generally by the maximum a-posteriori (MAP) estimation and some filters are derived with the aid of the Bayes formula. This MAP-filters reduces to M-filters if a-priori probability distribution is uniform, while the rank filters are derived when a-priori bias exists in the MAP estimation. This MAP-filters are implemented with an analog electronic circuit and the log-likelihood is shown to be a Liapunov function for the dynamics of this circuit.
ER -
English
