Qian Hu, Zhongqiang Luo, and Wenshi Xiao
Blind Source Separation Spectrum Detection Method Based on Wavelet Transform and Singular Spectrum Analysis
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.
Reference:
DOI: 10.36244/ICJ.2025.4.6
Please cite this paper the following way:
Qian Hu, Zhongqiang Luo, and Wenshi Xiao "Blind Source Separation Spectrum Detection Method Based on Wavelet Transform and Singular Spectrum Analysis", Infocommunications Journal, Vol. XVII, No 4, December 2025, pp. 41-48., https://doi.org/10.36244/ICJ.2025.4.6