SIMCA方法是建立在主成分分析基础上的一种有监督模式识别方法。该算法的基本思路是对训练集中每一类样本的光谱矩阵分别进行主成分分析，建立每一类的主成分分析数学模型，然后在此基础上对未知样本进行识别，即分别试探该未知样本与各类模型进行拟合，以确定其属于哪一类或不属于任何一类。-SIMCA method is based on principal component analysis of a supervised pattern recognition method.The basic idea of this algorithm is the training focus spectrum to each type of sample matrix principal component analysis, respectively, set up each kind of mathematical model of principal component analysis and then on this basis, which can identify the unknown sample is respectively to test the fitting of unknown samples and all kinds of model, to determine its what kind or does not belong to any category.