中文说明：主成分分析(Principle Component Analysis,PCA)是最为常用的特征提取方法，被广泛应用到各领域，如图像处理、综合评价、语音识别、故障诊断等。它通过对原始数据的加工处理，简化问题处理的难度并提高数据信息的信噪比，以改善抗干扰能力。
English Description：
Principal component analysis & lt; span style = & quot; font- size:12.0pt;font-family Principal component analysis (PCA) is the most commonly used feature extraction method, which is widely used in various fields, such as image processing, comprehensive evaluation, speech recognition, fault diagnosis and so on. By processing the original data, it simplifies the difficulty of problem processing and improves the signal-to-noise ratio of data information to improve the anti-interference ability.