2021•Unpublished venueOpen access

APPROXIMATION OF PEAKS IN γ-SPECTRA BY GAUSSIAN-LIKE ANALYTIC FUNCTIONS

A.Yu. Berezhnoy

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Abstract

The program processing γ-spectra named “GAMMAPEAKS”, was elaborated. This program can approximate peaks in γ-spectra with different Gaussian-like functions. The common Gaussian, the variable variance Gaussian and the sectionally defined Gaussian-like function were used as approximative functions. The contrastive analysis of quality of peaks approximating using no more than three approximative functions for one extremum in γ-spectra was performed. The quantitative and qualitative data determining the precision of approximating of γ-spectra peaks by different Gaussian-like functions are shown.

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The program processing γ-spectra named “GAMMAPEAKS”, was elaborated. This program can approximate peaks in γ-spectra with different Gaussian-like functions. The common Gaussian, the variable variance Gaussian and the sectionally defined Gaussian-like function were used as approximative functions. The contrastive analysis of quality of peaks approximating using no more than three approximative functions for one extremum in γ-spectra was performed. The quantitative and qualitative data determining the precision of approximating of γ-spectra peaks by different Gaussian-like functions are shown.

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Available abstract

The program processing γ-spectra named “GAMMAPEAKS”, was elaborated. This program can approximate peaks in γ-spectra with different Gaussian-like functions. The common Gaussian, the variable variance Gaussian and the sectionally defined Gaussian-like function were used as approximative functions. The contrastive analysis of quality of peaks approximating using no more than three approximative functions for one extremum in γ-spectra was performed. The quantitative and qualitative data determining the precision of approximating of γ-spectra peaks by different Gaussian-like functions are shown.

Key concepts: Gaussian, Gaussian function, Spectral line, Gaussian random field, Function (biology), Gaussian network model, Gaussian process, Mathematics

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