[1] [1] YIN J S,XIAO J,ZHOU Z T,et al..Analysis and application of non-linear manifold learning method[J]. Progress in Natural Science, 2007,17(8):1015-1025.(in Chinese)

[2] [2] ZHAO L W, LUO S W, ZHAO Y CH, et al.. Study on the low-dimensional embedding and the embedding dimensionality of manifold of high-dimensional data [J]. Journal of Software, 2005,16(8):1423-1430.(in Chinese)

[3] [3] LI F L, XU K X. An algorithm applied in frontal-view face images for automatically localizing eyes [J]. Opt. Precision Eng.,2006,14(2):320-326. (in Chinese)

[4] [4] LI F L, TANG W Y, DUAN H F, et al.. Application of fractional power polynomial kernel function to kernel direct discriminant analysis [J]. Opt. Precision Eng., 2007,15(9):1410-1414.(in Chinese)

[5] [5] TENENBAUM J B,SILVA V D,LANGFORD J C. A global geometric framework for nonlinear dimensionality reduction [J]. Science, 2000,290(5500):2319-2323.

[6] [6] ROWEIS S T,SAUL L K. Nonlinear dimensionality reduction by locally linear embedding [J]. Science, 2000,290(5500):2323-2326.

[7] [7] BELKIN M,NIYOGI P. Laplacian eigenmaps and spectral techniques for embedding and clustering [C]. In Advances in Neural Information Processing Systems, Cambridge, MA, USA, 2002(14):585-591.

[8] [8] ZHANG Z Y, ZHA H Y. Principal manifolds and nonlinear dimensionality reduction via local tangent space alignment [J]. SIAM Journal of Scientific Computing, 2004,26(1):313-338.

[9] [9] HE X F,NIYOGI P. Locality preserving projections[C]. In Proceedings of Neural Information Processing System, Vancouver, Canada,2003:153-160.

[10] [10] ZENG X H, LUO S W. A dynamically incremental manifold learning algorithm [J]. Journal of Computer Research and Development, 2007,44(9):1462-1468.(in Chinese)

[11] [11] CAO SH M, YE SH W. A manifold learning algorithm in a state of sparse source data [J]. Computer Simulation, 2007,24(3):104-106.(in Chinese)

[12] [12] XUE H, CHEN S C. Alternative robust local embedding[C]. In Proceedings of International Conference on Wavelet Analysis and Pattern Recognition, Beijing, China, 2007:591-596.

[13] [13] LIANG Y X, GONG W G, PANG Y J, et al.. Singular value decomposition-based approach for face recognition [J]. Opt. Precision Eng., 2004,12(5):543-549.(in Chinese)