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IDENTIFICATION OF ONE OR MORE SPECTRAL FEATURES IN A SPECTRUM OF A SAMPLE FOR A CONSTITUENT ANALYSIS

机译:识别用于组成分析的样本的光谱中的一种或多种光谱特征

摘要

The invention relates to a method for identifying one or more spectral features in a spectrum (4, 5) of a sample for a constituent analysis of the sample, comprising providing the spectrum (4, 5), predefining an approximation function (6), which is a continuously differentiable mathematical function, respectively forming an (n−1)-th order derivative (7, 8, 9) of the spectrum (4, 5) and of the approximation function (6), wherein the number n>1, generating a correlation matrix (10) from the two (n−1)-th order derivatives (7, 8, 9), and respectively identifying the spectral feature or one of the spectral features in each case as a function of a local extremum (i) of the correlation matrix (10) for at least one extremum (i) of the correlation matrix (10) in order to simplify the constituent analysis of the sample.
机译:本发明涉及一种用于鉴定样品的样品的光谱( 4,5 )中的一种或多种光谱特征的方法,用于样品的组成分析,包括提供光谱( 4,5 ),预定义近似函数( 6 ),其是一种连续可差的数学函数,分别形成(n-1)阶衍生物( 7,8,9频谱( 4,5 )和近似函数( 6 )的,其中,n个n> 1,产生相关矩阵( 10(n-1)阶衍生物( 7,8,9 ),并分别识别频谱特征或每种情况下的一个光谱特征用于相关矩阵( 10 )的局部极值(i)的函数,以简化样品的组成分析。

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