Atıf İçin Kopyala
Celik H., Karaboga N.
ELEKTRONIKA IR ELEKTROTECHNIKA, cilt.28, sa.5, ss.62-67, 2022 (SCI-Expanded)
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Yayın Türü:
Makale / Tam Makale
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Cilt numarası:
28
Sayı:
5
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Basım Tarihi:
2022
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Doi Numarası:
10.5755/j02.eie.31232
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Dergi Adı:
ELEKTRONIKA IR ELEKTROTECHNIKA
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Derginin Tarandığı İndeksler:
Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Applied Science & Technology Source, Central & Eastern European Academic Source (CEEAS), Communication Abstracts, Computer & Applied Sciences, INSPEC, Metadex, Directory of Open Access Journals, Civil Engineering Abstracts
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Sayfa Sayıları:
ss.62-67
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Anahtar Kelimeler:
Blind source separation, Denoising, Multiobjective optimization, Strength Pareto evolutionary algorithm 2, Optimization
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Erciyes Üniversitesi Adresli:
Evet
Özet
Blind Source Separation is an optimization method frequently used in statistical signal processing applications. There are many application areas such as ambient listening, denoising, signal detection, and so on. In this study, a new Strength Pareto Evolutionary Algorithm 2-based signal separation method is proposed, which combines Multi-Objective Optimization and Blind Source Separation algorithms. The proposed method has been tested for denoising, which is widely used in biomedical signal processing. That is, the Electrocardiogram (ECG) and White Gaussian Noise are mixed together with normally distributed random numbers and the original signals of the mixed signals are obtained again. To evaluate the performance of the proposed method and others (Multi-Objective Blind Source Separation and Independent Component Analysis), the Signal-to-Noise Ratio (SNR) of the ECG signal obtained from mixed signals has been measured. As a result of the simulation studies, it is seen that the performance of the proposed method is satisfactory.