An algorithm for ²⁵²Cf-Source-Driven neutron signal denoising based on Compressive Sensing

分类： 核科学技术 >> 核探测技术与核电子学 提交时间： 2023-06-18 合作期刊: 《Nuclear Science and Techniques》

LI Peng-Cheng WEI Biao FENG Peng HE Peng MI De-Ling

摘要： As photoelectrically detected 252Cf-source-driven neutron signals always contain noise, a denoising algorithm is proposed based on compressive sensing for the noised neutron signal. In the algorithm, Empirical Mode Decomposition (EMD) is applied to decompose the noised neutron signal and then find out the noised Intrinsic Mode Function (IMF) automatically. Thus, we only need to use the basis pursuit denoising (BPDN) algorithm to denoise these IMFs. For this reason, the proposed algorithm can be called EMDCSDN (Empirical Mode Decomposition Compressive Sensing Denoising). In addition, five indicators are employed to evaluate the denoising effect. The results show that the EMDCSDN algorithm is more effective than the other denoising algorithms including BPDN. This study provides a new approach for signal denoising at the front-end.

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