首页> 外国专利> A KERNEL-BASED METHOD AND APPARATUS FOR CLASSIFYING MATERIALS OR CHEMICALS AND FOR QUANTIFYING THE PROPERTIES OF MATERIALS OR CHEMICALS IN MIXTURES USING SPECTROSCOPIC DATA.

A KERNEL-BASED METHOD AND APPARATUS FOR CLASSIFYING MATERIALS OR CHEMICALS AND FOR QUANTIFYING THE PROPERTIES OF MATERIALS OR CHEMICALS IN MIXTURES USING SPECTROSCOPIC DATA.

机译:一种基于核的方法和装置,用于通过光谱数据对材料或化学物质进行分类,以及对混合物中的材料或化学物质进行定量。

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.
机译:基于核的方法确定第一光谱和第二光谱的相似性。每个光谱代表对材料或化学物质进行光谱分析的结果,并且包括分布在整个光谱范围内的一组光谱属性。该方法计算核函数,该核函数利用围绕光谱点的光谱响应的形状。这是通过计算光谱中光谱属性的值与光谱属性周围的窗口内一组相邻光谱属性中的每个之间的差来实现的。导出内核函数时,可以将加权值应用于计算。加权值可以将不同的重要程度分配给频谱的不同区域。该方法可用于:对未知光谱进行分类;预测混合物中分析物的浓度;数据库使用核派生的距离度量来搜索最接近的匹配;可视化二维或三维高光谱数据。

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