And in the feature extraction process, a new face recognition method based on CSVD and non Negative Matrix Factorization (NMF) is presented.

并在特征提取环节，提出CSVD算法与非负矩阵因子算法特征数据相融合的人脸识别算法。

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Aim: to study the feasibility and influential factors for the resolution of HPLC-DAD data of chiral drugs by non-negative matrix factorization (NMF) algorithm.

目的：研究非负矩阵因子分解算法(NMF)用于手性药物HPLC - DAD二维数据解析的可行性及其影响因素。

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Absrtact: Non - negative matrix factorization (NMF) is a method of parts - based feature extraction, it has been already applied to face recognition successfully.

摘要：非负矩阵分解方法是基于局部特征的特征提取方法，已经成功用于人脸识别。

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