Fast Parameter Selection Algorithm for Linear Parametric Filters

Akira TANAKA; Masaaki MIYAKOSHI

doi:10.1093/ietfec/e90-a.12.2952

Fast Parameter Selection Algorithm for Linear Parametric Filters

Akira TANAKA, Masaaki MIYAKOSHI

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A parametric linear filter for a linear observation model usually requires a parameter selection process so that the filter achieves a better filtering performance. Generally, criteria for the parameter selection need not only the filtered solution but also the filter itself with each candidate of the parameter. Obtaining the filter usually costs a large amount of calculations. Thus, an efficient algorithm for the parameter selection is required. In this paper, we propose a fast parameter selection algorithm for linear parametric filters that utilizes a joint diagonalization of two non-negative definite Hermitian matrices.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E90-A No.12 pp.2952-2956

Publication Date: 2007/12/01

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Online ISSN: 1745-1337

DOI: 10.1093/ietfec/e90-a.12.2952

Type of Manuscript: LETTER

Category: Digital Signal Processing

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Akira TANAKA, Masaaki MIYAKOSHI, "Fast Parameter Selection Algorithm for Linear Parametric Filters" in IEICE TRANSACTIONS on Fundamentals, vol. E90-A, no. 12, pp. 2952-2956, December 2007, doi: 10.1093/ietfec/e90-a.12.2952.
Abstract: A parametric linear filter for a linear observation model usually requires a parameter selection process so that the filter achieves a better filtering performance. Generally, criteria for the parameter selection need not only the filtered solution but also the filter itself with each candidate of the parameter. Obtaining the filter usually costs a large amount of calculations. Thus, an efficient algorithm for the parameter selection is required. In this paper, we propose a fast parameter selection algorithm for linear parametric filters that utilizes a joint diagonalization of two non-negative definite Hermitian matrices.
URL: https://globals.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e90-a.12.2952/_p

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@ARTICLE{e90-a_12_2952,
author={Akira TANAKA, Masaaki MIYAKOSHI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Fast Parameter Selection Algorithm for Linear Parametric Filters},
year={2007},
volume={E90-A},
number={12},
pages={2952-2956},
abstract={A parametric linear filter for a linear observation model usually requires a parameter selection process so that the filter achieves a better filtering performance. Generally, criteria for the parameter selection need not only the filtered solution but also the filter itself with each candidate of the parameter. Obtaining the filter usually costs a large amount of calculations. Thus, an efficient algorithm for the parameter selection is required. In this paper, we propose a fast parameter selection algorithm for linear parametric filters that utilizes a joint diagonalization of two non-negative definite Hermitian matrices.},
keywords={},
doi={10.1093/ietfec/e90-a.12.2952},
ISSN={1745-1337},
month={December},}

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TY - JOUR
TI - Fast Parameter Selection Algorithm for Linear Parametric Filters
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2952
EP - 2956
AU - Akira TANAKA
AU - Masaaki MIYAKOSHI
PY - 2007
DO - 10.1093/ietfec/e90-a.12.2952
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E90-A
IS - 12
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - December 2007
AB - A parametric linear filter for a linear observation model usually requires a parameter selection process so that the filter achieves a better filtering performance. Generally, criteria for the parameter selection need not only the filtered solution but also the filter itself with each candidate of the parameter. Obtaining the filter usually costs a large amount of calculations. Thus, an efficient algorithm for the parameter selection is required. In this paper, we propose a fast parameter selection algorithm for linear parametric filters that utilizes a joint diagonalization of two non-negative definite Hermitian matrices.
ER -