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
Penapis ε ialah penapis tak linear untuk mengurangkan hingar dan boleh digunakan bukan sahaja untuk isyarat pertuturan tetapi juga untuk isyarat imej. Reka bentuk penapis adalah mudah dan ia boleh mengurangkan bunyi dengan berkesan dengan parameter penapis yang mencukupi. Kertas kerja ini membentangkan kaedah untuk menganggar parameter penapis optimum bagi ε-penapis berdasarkan dekorasi bunyi-bunyi isyarat dan menunjukkan bahawa ia menghasilkan parameter penapis optimum berkenaan dengan pelbagai aras hingar. Kaedah yang dicadangkan boleh digunakan apabila hingar yang hendak dikeluarkan tidak berkaitan dengan isyarat, dan ia tidak memerlukan sebarang pengetahuan lain seperti varians hingar dan data latihan.
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Salinan
Mitsuharu MATSUMOTO, Shuji HASHIMOTO, "Estimation of Optimal Parameter in ε-Filter Based on Signal-Noise Decorrelation" in IEICE TRANSACTIONS on Information,
vol. E92-D, no. 6, pp. 1312-1315, June 2009, doi: 10.1587/transinf.E92.D.1312.
Abstract: ε-filter is a nonlinear filter for reducing noise and is applicable not only to speech signals but also to image signals. The filter design is simple and it can effectively reduce noise with an adequate filter parameter. This paper presents a method for estimating the optimal filter parameter of ε-filter based on signal-noise decorrelation and shows that it yields the optimal filter parameter concerning a wide range of noise levels. The proposed method is applicable where the noise to be removed is uncorrelated with signal, and it does not require any other knowledge such as noise variance and training data.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E92.D.1312/_p
Salinan
@ARTICLE{e92-d_6_1312,
author={Mitsuharu MATSUMOTO, Shuji HASHIMOTO, },
journal={IEICE TRANSACTIONS on Information},
title={Estimation of Optimal Parameter in ε-Filter Based on Signal-Noise Decorrelation},
year={2009},
volume={E92-D},
number={6},
pages={1312-1315},
abstract={ε-filter is a nonlinear filter for reducing noise and is applicable not only to speech signals but also to image signals. The filter design is simple and it can effectively reduce noise with an adequate filter parameter. This paper presents a method for estimating the optimal filter parameter of ε-filter based on signal-noise decorrelation and shows that it yields the optimal filter parameter concerning a wide range of noise levels. The proposed method is applicable where the noise to be removed is uncorrelated with signal, and it does not require any other knowledge such as noise variance and training data.},
keywords={},
doi={10.1587/transinf.E92.D.1312},
ISSN={1745-1361},
month={June},}
Salinan
TY - JOUR
TI - Estimation of Optimal Parameter in ε-Filter Based on Signal-Noise Decorrelation
T2 - IEICE TRANSACTIONS on Information
SP - 1312
EP - 1315
AU - Mitsuharu MATSUMOTO
AU - Shuji HASHIMOTO
PY - 2009
DO - 10.1587/transinf.E92.D.1312
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E92-D
IS - 6
JA - IEICE TRANSACTIONS on Information
Y1 - June 2009
AB - ε-filter is a nonlinear filter for reducing noise and is applicable not only to speech signals but also to image signals. The filter design is simple and it can effectively reduce noise with an adequate filter parameter. This paper presents a method for estimating the optimal filter parameter of ε-filter based on signal-noise decorrelation and shows that it yields the optimal filter parameter concerning a wide range of noise levels. The proposed method is applicable where the noise to be removed is uncorrelated with signal, and it does not require any other knowledge such as noise variance and training data.
ER -