β-Divergence Nonnegative Matrix Factorization on Biomedical Blind Source Separation

Authors

  • A. M. Darsono Faculty of Electronic and Computer Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia
  • C. C. Toh Faculty of Electronic and Computer Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia
  • M. S. Md Saat Faculty of Electronic and Computer Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia
  • A. A. M. Isa Faculty of Electronic and Computer Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia
  • N. A. Manap Faculty of Electronic and Computer Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia
  • M. M. Ibrahim Faculty of Electronic and Computer Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia

Keywords:

Blind Source Separation, Nonnegative Matrix Factorization, ?-Divergence, KL Divergence, LSE Divergence,

Abstract

β-divergence has been studied for years, but it is yet to be discovered thoroughly. In this paper, we proposed the nonnegative matrix factorization (NMF) by using β-divergence in blind source separation (BSS) on biomedical field. The proposed idea is basically aimed at the separation of normal heart sound with normal lung sound. Temporal codes and spectral basis were modelled into a separated source, which is applied to the synthesis and real life data using multiplicative update rules. In the experiment, estimated and original source were compared to evaluate the performance of various source separation algorithms within a general framework, where the original sources and the noise that perturbed the mixture were included.

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Published

2017-04-15

How to Cite

Darsono, A. M., Toh, C. C., Md Saat, M. S., Isa, A. A. M., Manap, N. A., & Ibrahim, M. M. (2017). β-Divergence Nonnegative Matrix Factorization on Biomedical Blind Source Separation. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(2), 1–4. Retrieved from https://jtec.utem.edu.my/jtec/article/view/827

Issue

Vol. 9 No. 2: April - June 2017

Section

Articles

License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)

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