[1]Bro R,Smilde A K.Principal component analysis [J].Analytical Methods,2014,6(9):28122831.
[2]Izenman A J. Linear discriminant analysis.Modern multivariate statistical techniques [M].New York:Springer,2013:237280.
[3]Belkin M, Niyogi P.Laplacian eigenmaps and spectral techniques for embedding and clustering [C]∥Proc of NIPS,2001:585591.
[4]Roweis S T,Saul L K.Nonlinear dimensionality reduction by locally linear embedding [J].Science,2012,290(5):23232326.
[5]Niyogi X.Locality preserving projections[C]∥Proc of Neural Information Processing Systems,2004:153.
[6]Qiao L,Chen S,Tan X.Sparsity preserving projections with applications to face recognition [J].Pattern Recognition,2010,43(1):331341.
[7]Wright J,Yang A Y,Ganesh A,et al.Robust face recognition via sparse representation [J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2009,31(2):210227.
[8]Yang J, Chu D. Sparse representation classifier steered discriminative projection [C]∥Proc of 2010 International Conference on Pattern Recognition,2010:694697.
[9]Mairal J,Sapiro G,Elad M.Learning multiscale sparse representations for image and video restoration[J].Multiscale Modeling & Simulation,2008,7(1):214241.
[10]Mairal J,Elad M,Sapiro G.Sparse representation for color image restoration [J].IEEE Transactions on Image Processing,2008,17(1):5369.
[11]Ye J,Wang H,Yang W.Image reconstruction for electrical capacitance tomography based on sparse representation [J].IEEE Transactions on Instrumentation & Measurement,2015,64(1):89102.
[12]Weisheng D,Lei Z,Guangming S,et al.Nonlocally centralized sparse representation for image restoration [J].IEEE Transactions on Image Processing,2013,22(4):16201630.
[13]Hui K.H,Li C L,Zhang L.Sparse neighbor representation for classification [J].Pattern Recognition Letters,2012,33(5):661669.
[14]Ma Xiaohu, Tan Yanqi. Face recognition based on discriminant sparsity preserving embedding[J].Acta Automatica Sinica,2014,40(1):7382.(in Chinese)
附中文参考文献:
[14]马小虎,谭延琪.基于鉴别稀疏保持嵌入的人脸识别算法 [J].自动化学报,2014,40(1):7382.