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Kernel and device types How to use the spectroscopic data, to quantify the characteristics of the materials or chemicals in the mixture and the classification of materials or chemicals
Kernel and device types How to use the spectroscopic data, to quantify the characteristics of the materials or chemicals in the mixture and the classification of materials or chemicals
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机译:内核和设备类型如何使用光谱数据,量化混合物中材料或化学物质的特性以及材料或化学物质的分类
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摘要
A kernel-based method determines the similarity of a first spectrum and a second spectrum. Each spectrum represents a result of spectral analysis of a material or chemical and comprises a set of spectral attributes distributed across a spectral range. The method calculates a kernel function which makes use of the shape of the spectral response surrounding a spectral point. This is achieved by calculating the difference between the value of an spectral attribute in a spectrum and each of a set of neighbouring spectral attributes within a window around the spectral attribute. Weighting values can be applied to calculations when deriving the kernel function. The weighting values can assign different degrees of importance to different regions of the spectrum. The method can be used to: classify unknown spectra; predict the concentration of an analyte within a mixture; database searching for the closest match using a kernel-derived distance metric; visualisation of high-dimensional spectral data in two or three dimensions.
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