近红外透射光谱结合规范变量分析用于化学模式分类

应用近红外透射光谱，实施规范变量提取-线性判别分析(CVA-LDA)技术，对其分属不同药物剂量类型进行鉴别。针对药物近红外透射光谱频道变量个数多，彼此间存在严重的复共线性，富有冗余信息，样本类(模式)内的离散度矩阵为奇异，由传统CVA方法提取规范变量的计算不稳健，提出了改进的规范变量分析ICVA方法。它通过嵌入偏最小二乘(PLS)算法，完成规范权矢量的稳健估计，进而用于提取出若干个规范变量。而后，基于规范变量张成的低维空间，构造样本类别的线性判别函数，负责各样本个体类别的判定。实验结果表明，改进的ICVA-LDA方法，克服了LDA对高维小样本数据建模的局限性，模型的判别能力明显优于其他方法。

Classification of Pharmaceutical Tablet with Canonical Variates Analysis Method in Spectra Analysis

A novel classifier was constructed in the present paper by combination of an improved canonical variates analysis(ICVA) with Fish linear discriminant analysis(LDA).The resulting discrimination model based on this proposed approach(ICVA-LDA) was divided into two parts: the inner part that estimated the robust weight vector of canonical variates by linear partial least square algorithm and the outer part that built the LDA discrimination model by making use of the extracted canonical variates.The method utili...