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Multivariate analysis and classification of two-dimensional angular optical scattering patterns from aggregates

机译:聚集体二维角光散射图的多元分析和分类

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Two-dimensional light-scattering patterns from aggregates have undergone feature extraction followed by multivariate statistical analysis. The aggregates are comprised of primary particles of varying shape and size. Morphological descriptors (features) were extracted by a nonlinear filtering algorithm (spectrum enhancement) and then processed by principal component analysis and discriminant function analysis. The analysis was performed on two data sets, one in which the aggregates had a fixed primary particle size but varied in overall dimension and another in which the aggregate size was fixed but the primary particle size varied. Classification of the samples was performed adequately, providing some distinction among the limited classes that were analyzed.
机译:来自聚集体的二维光散射图案已经进行了特征提取,然后进行了多元统计分析。聚集体由形状和大小变化的初级颗粒组成。通过非线性滤波算法(频谱增强)提取形态学描述符(特征),然后通过主成分分析和判别函数分析进行处理。对两个数据集进行了分析,一个数据集的聚集体具有固定的初级粒径,但总体尺寸有所变化,另一个数据集的聚集体尺寸固定,但初级粒径却有所变化。适当地对样本进行了分类,从而在所分析的有限类别之间提供了一些区别。

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