Improve Akaike’s Information Criterion Estimation Based on Denoising of Quadrature Mirror Filter Bank

Improve Akaike’s Information Criterion Estimation Based on Denoising of Quadrature Mirror Filter Bank

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Akaike’s Information Criterion (AIC) is a popular method for estimation the number of sources impinging on an array of sensors, which is a problem of great interest in several applications. The performance of AIC degrades under low Signal-to-Noise Ratio (SNR). This paper is concerned with the devel...

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Autor principal: Mohammed H. Miry
Formato: article
Lenguaje:EN
Publicado: Al-Khwarizmi College of Engineering – University of Baghdad 2019
Materias:
Chemical engineering
TP155-156
Engineering (General). Civil engineering (General)
TA1-2040
Acceso en línea:https://doaj.org/article/9cbc9611ebe1419996f3a2e93997a577
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spelling oai:doaj.org-article:9cbc9611ebe1419996f3a2e93997a5772021-12-02T02:52:09ZImprove Akaike’s Information Criterion Estimation Based on Denoising of Quadrature Mirror Filter Bank1818-11712312-0789https://doaj.org/article/9cbc9611ebe1419996f3a2e93997a5772019-03-01T00:00:00Zhttp://alkej.uobaghdad.edu.iq/index.php/alkej/article/view/583https://doaj.org/toc/1818-1171https://doaj.org/toc/2312-0789 Akaike’s Information Criterion (AIC) is a popular method for estimation the number of sources impinging on an array of sensors, which is a problem of great interest in several applications. The performance of AIC degrades under low Signal-to-Noise Ratio (SNR). This paper is concerned with the development and application of quadrature mirror filters (QMF) for improving the performance of AIC. A new system is proposed to estimate the number of sources by applying AIC to the outputs of filter bank consisting quadrature mirror filters (QMF). The proposed system can estimate the number of sources under low signal-to-noise ratio (SNR). Mohammed H. MiryAl-Khwarizmi College of Engineering – University of BaghdadarticleChemical engineeringTP155-156Engineering (General). Civil engineering (General)TA1-2040ENAl-Khawarizmi Engineering Journal, Vol 5, Iss 4 (2019)
institution DOAJ
collection DOAJ
language EN
topic Chemical engineering
TP155-156
Engineering (General). Civil engineering (General)
TA1-2040
spellingShingle Chemical engineering
TP155-156
Engineering (General). Civil engineering (General)
TA1-2040
Mohammed H. Miry
Improve Akaike’s Information Criterion Estimation Based on Denoising of Quadrature Mirror Filter Bank
description Akaike’s Information Criterion (AIC) is a popular method for estimation the number of sources impinging on an array of sensors, which is a problem of great interest in several applications. The performance of AIC degrades under low Signal-to-Noise Ratio (SNR). This paper is concerned with the development and application of quadrature mirror filters (QMF) for improving the performance of AIC. A new system is proposed to estimate the number of sources by applying AIC to the outputs of filter bank consisting quadrature mirror filters (QMF). The proposed system can estimate the number of sources under low signal-to-noise ratio (SNR).
format article
author Mohammed H. Miry
author_facet Mohammed H. Miry
author_sort Mohammed H. Miry
title Improve Akaike’s Information Criterion Estimation Based on Denoising of Quadrature Mirror Filter Bank
title_short Improve Akaike’s Information Criterion Estimation Based on Denoising of Quadrature Mirror Filter Bank
title_full Improve Akaike’s Information Criterion Estimation Based on Denoising of Quadrature Mirror Filter Bank
title_fullStr Improve Akaike’s Information Criterion Estimation Based on Denoising of Quadrature Mirror Filter Bank
title_full_unstemmed Improve Akaike’s Information Criterion Estimation Based on Denoising of Quadrature Mirror Filter Bank
title_sort improve akaike’s information criterion estimation based on denoising of quadrature mirror filter bank
publisher Al-Khwarizmi College of Engineering – University of Baghdad
publishDate 2019
url https://doaj.org/article/9cbc9611ebe1419996f3a2e93997a577
work_keys_str_mv AT mohammedhmiry improveakaikesinformationcriterionestimationbasedondenoisingofquadraturemirrorfilterbank
_version_ 1718402113772453888

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