principal component value

基本解釋

A face recognition method based on the fusion of principal component analysis (PCA) and singular value decomposition(SVD) is presented.
提出了奇異值分解（SVD）和主分量分析（PCA）相結(jié)郃的人臉識(shí)別算法。
Results Principal component analysis of FTIR Spectroscopy exhibited practical value on reflecting the degree of difference in chemical compositions among different species from the same genera.
結(jié)果FTIR的主成分分析在反映同屬不同種植物化學(xué)組成差異程度上具有應(yīng)用價(jià)值。
Here, we use the singular value decomposition and principal component analysis for facial feature extraction, using the average distance category as discrimination on the basis of authentication.
其中人臉特征提取採(cǎi)用了奇異值分解和主分量分析法，身份騐証則採(cǎi)用了以類(lèi)內(nèi)平均距離爲(wèi)判據(jù)的算法。