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Kanjilal, P.P. and Palit, S. (1995) On Multiple Pattern Extraction Using Singular Value Decomposition. IEEE Transactions on Signal Processing, 43, 1536-1540. https://doi.org/10.1109/78.388873

has been cited by the following article:

• TITLE: Singular Value Noise Reduction Method for Full-Spectrum Input Gamma Energy Spectrum

  AUTHORS: Quan Yuan, Guangming Dai, Dashun Yan, Zhiquan Zhou

  KEYWORDS: Noise Reduction, Gamma-Ray Spectrometry, Spectral Smoothing, NASVD

  JOURNAL NAME: Open Access Library Journal, Vol.9 No.9, August 30, 2022

  ABSTRACT: The traditional smoothing method is complicated to use when the number of road sites is large, and multiple smoothing is required in the case of large noise, aiming at this problem, this paper uses the singular value decomposition denoising method to smooth the gamma energy spectrum. This paper expounds the basic principle of the singular value decomposition method, and the mathematical models of different reconstruction matrices and compares the effects of different reconstruction matrices on full-spectrum noise reduction. The results show that the signal-to-noise ratio is improved by 4.27% compared with the traditional method after the singular value decomposition, selection, reconstruction and reduction after using the Hankel matrix for energy spectrum allosteric.