KPCA Based on LS-SVM for Face Recognition

  • Xie Jianhong
  • Published 2008 in
    2008 Second International Symposium on…


Kernel principal component analysis (KPCA) is an improved PCA, which possesses the property of extracting optimal features by adopting a nonlinear kernel function method. Based on the duality between least square support vector machine (LS-SVM) and KPCA, the optimization problem of KPCA can be transformed into the solving of quadratic equations by means of… (More)


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