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".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Nous présentons une nouvelle méthode d'estimation de la transition spectrale de signaux non stationnaires dans les cas de faible rapport signal sur bruit (SNR). Au lieu des fonctions de base utilisées dans la modélisation autorégressive (AR) variable dans le temps proposée précédemment, nous introduisons une contrainte de transition spectrale dans la fonction de coût décrite par les coefficients de corrélation partielle (PARCORR) afin que la méthode soit applicable aux signaux non stationnaires bruités dont les modèles de transition du spectre sont complexes. En appliquant cette méthode à l'analyse des signaux vibratoires sur le septum interventriculaire (IVS) du cœur, mesurés de manière non invasive par la nouvelle méthode développée dans notre laboratoire utilisant des ultrasons, le modèle de transition spectrale est clairement obtenu au cours d'un cycle cardiaque pour des sujets normaux et d'un patient atteint de cardiomyopathie.
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Copier
Hiroshi KANAI, Yoshiro KOIWA, "PARCORR-Based Time-Dependent AR Spectrum Estimation of Heart Wall Vibrations" in IEICE TRANSACTIONS on Fundamentals,
vol. E82-A, no. 4, pp. 572-579, April 1999, doi: .
Abstract: We present a new method for estimation of spectrum transition of nonstationary signals in cases of low signal-to-noise ratio (SNR). Instead of the basic functions employed in the previously proposed time-varying autoregressive (AR) modeling, we introduce a spectrum transition constraint into the cost function described by the partial correlation (PARCORR) coefficients so that the method is applicable to noisy nonstationary signals of which spectrum transition patterns are complex. By applying this method to the analysis of vibration signals on the interventricular septum (IVS) of the heart, noninvasively measured by the novel method developed in our laboratory using ultrasonics, the spectrum transition pattern is clearly obtained during one cardiac cycle for normal subjects and a patient with cardiomyopathy.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e82-a_4_572/_p
Copier
@ARTICLE{e82-a_4_572,
author={Hiroshi KANAI, Yoshiro KOIWA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={PARCORR-Based Time-Dependent AR Spectrum Estimation of Heart Wall Vibrations},
year={1999},
volume={E82-A},
number={4},
pages={572-579},
abstract={We present a new method for estimation of spectrum transition of nonstationary signals in cases of low signal-to-noise ratio (SNR). Instead of the basic functions employed in the previously proposed time-varying autoregressive (AR) modeling, we introduce a spectrum transition constraint into the cost function described by the partial correlation (PARCORR) coefficients so that the method is applicable to noisy nonstationary signals of which spectrum transition patterns are complex. By applying this method to the analysis of vibration signals on the interventricular septum (IVS) of the heart, noninvasively measured by the novel method developed in our laboratory using ultrasonics, the spectrum transition pattern is clearly obtained during one cardiac cycle for normal subjects and a patient with cardiomyopathy.},
keywords={},
doi={},
ISSN={},
month={April},}
Copier
TY - JOUR
TI - PARCORR-Based Time-Dependent AR Spectrum Estimation of Heart Wall Vibrations
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 572
EP - 579
AU - Hiroshi KANAI
AU - Yoshiro KOIWA
PY - 1999
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E82-A
IS - 4
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - April 1999
AB - We present a new method for estimation of spectrum transition of nonstationary signals in cases of low signal-to-noise ratio (SNR). Instead of the basic functions employed in the previously proposed time-varying autoregressive (AR) modeling, we introduce a spectrum transition constraint into the cost function described by the partial correlation (PARCORR) coefficients so that the method is applicable to noisy nonstationary signals of which spectrum transition patterns are complex. By applying this method to the analysis of vibration signals on the interventricular septum (IVS) of the heart, noninvasively measured by the novel method developed in our laboratory using ultrasonics, the spectrum transition pattern is clearly obtained during one cardiac cycle for normal subjects and a patient with cardiomyopathy.
ER -