基于PSR-fastICA的谱致极化降噪方法

Wei Cen, Zhihua Li
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摘要

谱致极化(SIP)是一种广泛应用的地球物理勘探方法,但它容易产生噪声。针对这一问题,本文提出了相空间重构(PSR)和快速独立分量分析(fastICA)相结合的降噪方法。该方法通过有效地去除噪声,提高了SIP数据的信噪比。实验结果表明,PSR-fastICA方法能显著降低SIP信号中的噪声。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A noise reduction method based on PSR-fastICA for spectrum-induced polarization data
Spectrum-induced polarization (SIP) is a widely used geophysical exploration approach, but it is prone to noise. To address this issue, this paper proposes a noise reduction method that combines phase space reconstruction (PSR) and fast independent component analysis (fastICA). The proposed approach enhances the signal-to-noise ratio of SIP data by effectively removing noise. Experimental results show that the PSR-fastICA method significantly reduces noise in SIP signals.
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