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| Kernel-Based Dual-Space Method and Its Fast Solution Algorithm |
| ZHOU Xiao-Yan1,2,ZHENG Wen-Ming3,ZOU Cai-Rong2,ZHAO Li2 |
1.College of Electronic and Information Engineering,Nanjing University of Information Science and Technology,Nanjing 210044
2.Key Laboratory of Underwater Acoustic Signal Processing of Ministry of Education,School of Information Science and Engineering,Southeast University,Nanjing 210096
3.Research Center for Learning Science,Southeast University,Nanjing 210096 |
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Abstract To overcome the drawbacks of the dual-space linear discriminant analysis method, a kernel-based dual-space discriminant analysis method, namely KDS-DA is proposed. A fast algorithm based on the inverse operator of bordered matrix is also proposed for solving the discriminant vectors of KDS-DA. The algorithm utilizes the fact that the inverse computation of higher order bordered matrix can be converted to the inverse computation of a lower order matrix. To solve the (r+1)-th discriminant vector in the principal subspace of the within-class scatter matrix, the computational results obtained in computing the r-th discriminant vector are fully used, which significantly reduces the computational cost. The experimental results on ORL and AR face databases demonstrate the effectiveness of the proposed methods.
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Received: 22 June 2009
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2010, Vol. 23 
