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- 2DPCA算法2DPCA algorithm
- 兩級2DPCATwo-stage 2DPCA
- 2DPCA方法2DPCA
- 分塊2DPCAmodular 2DPCA
- 算法設計algorithm design
- 模塊2DPCAmodular two-dimensional principal component analysis
- 模塊化2DPCAmodular 2DPCA
- 算法設計與分析The Design and Analysis of Algorithm
- 模塊C-2DPCAmodular complete two dimensional principal component analysis
- 控制算法control algorithm
- 二維主成分分析（2DPCA）Two Dimensional Principal Component Analysis (2DPCA)
- 聚類(lèi)算法clustering algorithm
- 二維主分量分析（2DPCA）2DPCA
- 啟發(fā)式算法heuristic algorithm
- 迭代算法iterative algorithm
- 最優(yōu)控制算法algorithm for optimal control
- 漸縮算法knapsack algorithm
- 在ORL,Yale和AR等人臉數據集上的實(shí)驗表明,該類(lèi)方法的識別率高于相應的基于歐氏距離的PCA,2DPCA,M atPCA和(2D)2PCA等方法。Experimental results on ORL,Yale and AR face datasets show that pseudo-PCA,-2DPCA,-MatPCA and-(2D)~2PCA based on the correlation metric outperform PCA,2DPCA,MatPCA and(2D)~2PCA based on the Euclidian distance.
- 調度算法scheduling algorithm
- Ｋ－Ｐ算法K-P calculation
