参考文献

[1] Fukunaga K. Introduction to Statistical Pattern Recognition [M]. New York: Academic Press, 1990.

[2] Fisher R A. The use of multiple measurements in taxonomic problems [J]. Annals of Human Genetics, 1936, 7 (7): 179-188.

[3] Wilks S S. Mathematical Statistics [M]. New York: John Wiley & Sons, Inc., 1962: 577-578.

[4] Duda R O, Hart P E. Pattern Classification and Scene Analysis [M]. New York: John Wiley & Sons, Inc., 1973.

[5] Jin Z, Yang J Y, Tang Z M, et al. A theorem on the uncorrelated optimal discriminant vectors [J]. Pattern Recognition, 2001, 34 (10): 2041-2047.

[6] Longstaff I D. On extensions to Fisher's linear discriminant function [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1987, 9 (2): 321-324.

[7] Yang J, Frangi A F, Yang J Y, et al. KPCA plus LDA: a complete kernel fisher discriminant framework for feature extraction and recognition [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005, 27 (2): 230-244.

[8] Yang J, Zhang D, Frangi A F, et al. Two dimensional PCA: a new approach to appearance-based face representation and recognition [J]. IEEE Pattern Analysis and Machine Intelligence, 2004, 26 (1): 131-137.

[9] Seung H S, Lee D D. The manifold ways of perception [J]. Science, 2000, 290: 2268-2269.

[10] Roweis S T, Saul L K. Nonlinear dimensionality reduction by locally linear embedding [J]. Science, 2000, 290: 2323-2326.

[11] Vinje W E, Gallant J L. Sparse coding and decorrelation in primary visual cortex during natural vision [J]. Science, 2000, 287 (5456): 1273-1276.

[12] Olshausen B A, Field D J. Sparse coding of sensory inputs [J]. Current Opinion in Neurobiology, 2004, 14 (4): 481-487.

[13] Candès E J, Tao T. The power of convex relaxation: Near-optimal matrix completion [J]. IEEE Transactions on Information Theory, 2010, 56 (5): 2053-2080.

[14] Candès E J, Li X, Ma Y, et al. Robust principal component analysis? [J] Journal of the ACM, 2011, 58 (3): 1-37.

[15] Rumelhart D E, Hinton G E, Williams R J. Learning representations by back-propagating errors [J]. Nature, 1986, 323 (6088): 533-536.

[16] Rumelhart D E, Hinton G E, Williams R J. Learning internal representations by error propagation [M] // Rumelhart D E, McClelland J L, Parallel distributed processing: Explorations in the microstructure of cognition, Vol.1: Foundations. Cambridge, MA: The MIT Press, 1986: 318-364.

[17] Vapnik V, Lerner A. Pattern recognition using generalized portrait method [J]. Automation and Remote Control, 1963, 24: 774-780.

[18] Vapnik V, Golowich S E, Smola A. Support vector method for function approximation, regression estimation,and signal processing [M] // Mozer M C, Jordan M, Petsche T, Advances in Neural Information Processing Systems 9, Cambridge, MA: The MIT Press, 1997: 281-287.

[19] Kittler J, Hatef M, Duin R P W, et al. On combining classifiers [J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 1998, 20 (3): 226-239.

[20] Jin Z, Yang J Y, Tang Z M, et al. A theorem on the uncorrelated optimal discriminant vectors [J]. Pattern Recognition, 2001, 34 (10): 2041-2047.

[21] Liao S X, Pawlak M. On image analysis by moments [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1996, 18 (3): 254-266.

[22] Chellappa R, Wilson C L, Sirohey S. Human and machine recognition of faces: A survey [J]. Proceedings of the IEEE, 1995, 83 (5): 705-740.

[23] Samaria F, Harter A. Parameterisation of a stochastic model for human face identification [C]. In Proceedings of 2nd IEEE Workshop on Applications of Computer Vision, Sarasota FL, December, 1994.