1) adaptively weighted sub-pattern PCA (Aw-SpPCA)
自适应加权子模式主分量分析
1.
Based on the previous research work, adaptively weighted sub-pattern PCA (Aw-SpPCA) is proposed and successfully applied to the task of face recognition, and then a native face recognition system based on Microsoft .
本文提出了自适应加权子模式主分量分析方法。
2) weighted principle component analysis(WPCA)
加权主分量分析
3) adaptive component weighting
自适应成分加权
4) adaptive PCA
自适应主元分析
1.
To overcome the false-alarm caused by the time-varying process condition,an approach is presented which first utilizes wavelets to eliminate noise and then uses adaptive PCA to update the PCA model recursively by combining the ability of wavelets and adaptive PCA.
文中针对慢时变引起的过程运行中的误报警问题,给出了一种小波分析与自适应主元分析相结合的混合方法,用小波去噪后再用自适应主元分析递归更新主元模型。
2.
Therefore, domestic and foreign scholars have proposed some improved methods, such as adaptive PCA and MSPCA which extend applications of PCA in the industry process control.
例如,自适应主元分析,多尺度主元分析等。
3.
To overcome the shortage of the fixed-model PCA, several adaptive PCA methods have been proposed.
针对传统主元分析法基于静态模型的缺陷,自适应主元分析方法按照一定的准则实时更新主元模型,实现了对过程正常慢漂移的有效跟踪,具有重要的理论研究意义和广泛的应用前景。
5) sub-pattern PCA(SpPCA)
子模式主分量分析(SpPCA)
6) Adaptive refinement scheme
自适应细分模式
补充资料：加权平均模式
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条