Blind Source Separation On Biomedical Field By Using Nonnegative Matrix Factorization

Toh, Cheng Chuan and Abdul Majid, Darsono and Mohd Shakir, Md Saat and Azmi, Awang Md Isa and Norlezah, Hashim (2016) Blind Source Separation On Biomedical Field By Using Nonnegative Matrix Factorization. ARPN Journal Of Engineering And Applied Sciences, 11 (13). pp. 8200-8206. ISSN 1819-6608

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Abstract

The study of separating heart from lung sound has been investigated and researched for years. However, a novel approach based on nonnegative matrix factorization (NMF) as a skill of blind source separation (BSS) that utilized in biomedical field is fresh presented. Lung sound gives beneficial information regarding lung status through respiratory analysis. However, interrupt of heart sound is the obstacle from taking precise and exact information during respiratory analysis. Thus, separation heart sound from lung sound is a way to overcome this issue in order to determine the accuracy of respiratory analysis. This paper proposes factorizations approach that concern on the 2 dimensional which is combination of frequency domain and time domain or well known as NMF2D. The proposed method is developed under the divergence of Least Square Error and Kullback-Leibler and it demonstrates from a single channel source. In this paper, we will forms a multivariate data and it will proceed for dimension reduction by log frequency domain. Experimental tests and comparisons will be made via different divergence to verify and evaluate efficiency of the proposed method in term performance measurement.

Item Type:	Article
Uncontrolled Keywords:	blind source separation, nonnegative matrix factorization, KL divergence, LSE divergence.
Subjects:	T Technology > T Technology (General)
Divisions:	Faculty of Electronics and Computer Engineering
Depositing User:	Mohd Hannif Jamaludin
Date Deposited:	21 Sep 2016 02:41
Last Modified:	09 Sep 2021 00:18
URI:	http://eprints.utem.edu.my/id/eprint/17101
Statistic Details:	View Download Statistic

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