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Blind Source Separation Spectrum Detection Method Based on Wavelet Transform and Singular Spectrum Analysis

Hu, Qian and Luo, Zhongqiang and Xiao, Wenshi (2025) Blind Source Separation Spectrum Detection Method Based on Wavelet Transform and Singular Spectrum Analysis. INFOCOMMUNICATIONS JOURNAL, 17 (4). pp. 41-48. ISSN 2061-2079

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Abstract

To address the issue of reduced detection performance due to the impaired separation mechanism affected by noise, this paper proposes a blind source separation (BSS) detection method based on Wavelet Transform (WT) and Singular Spectrum Analysis (SSA). Firstly, the input signal is denoised using WT. Then, SSA is employed to denoise and reduce the dimension of the processed signal. Subsequently, the independent component analysis (ICA) based BSS algorithm is employed to separate the mixed signal preprocessed by the previous two ways. Finally, the proposed algorithm and the BSS detection method based on WT are compared in terms of spectrum analysis and separation performance. Simulation results show that the blind source separation detection method based on WT-SSA has a better signal detection performance.

Item Type: Article
Uncontrolled Keywords: blind source separation; wavelet transform; singular spectrum sensing; independent component analysis
Subjects: T Technology / alkalmazott, műszaki tudományok > T2 Technology (General) / műszaki tudományok általában
SWORD Depositor: MTMT SWORD
Depositing User: MTMT SWORD
Date Deposited: 28 Jan 2026 15:20
Last Modified: 28 Jan 2026 15:20
URI: https://real.mtak.hu/id/eprint/232836

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