[1] KAPLAN L M. Analysis of multiplicative speckle models for template-based SAR ATR[J]. IEEE Transactions on Aerospace and Electronic Systems, 2001, 37(4):1424-1432.[2] WANG J, SUN L J. Research on supervised manifold learning for SAR target classification[C]//IEEE International Conference on Computational Intelligence for Measurement Systems and Applications, CIMSA'09. Hong Kong, China:IEEE, 2009:140-142.[3] BERISHA V, SHAH N, WAAGEN D, et al. Sparse manifold learning with applications to SAR image classification[C]//IEEE International Conference Acoustics, Speech and Signal Processing. Honolulu, HI, USA:IEEE, 2007:1086-1089.[4] SCHERBAKOV A, HANSSEN R, VOSSELMAN G, et al. Ship wake detection using radon transforms of filtered SAR imagery[C]//Proceedings of the European Symposium on Satellite Remote Sensing:Microwave Sensing and Synthetic Aperture Radar. Taormina, Italy:International Society for Optics and Photonics, 1996:96-106.[5] 种劲松, 朱敏慧. 高分辨率合成孔径雷达图像舰船检测方法[J]. 测试技术学报, 2003, 17(1):15-18.ZHONG J S, ZHU M H. Ship detection method of high-resolution SAR imagery[J]. J Test & Measurement Technology, 2003, 17(1):15-18. (in Chinese)[6] CHAPELLE O, SCHLKOPF B, ZIEN A. Semi-supervised learning[J]. J Royal Stat Society, 2013, 49(2):215-239.[7] 刘建伟, 刘媛, 罗雄麟. 半监督学习方法[J]. 计算机学报, 2015, 38(8):1592-1617.LIU J W, LIU Y, LUO X L. Semi-supervised learning methods[J]. Chinese J Computers, 2015, 38(8):1592-1617. (in Chinese)[8] KINGMA D P, REZENDE D J, MOHAMED S, et al. Semi-supervised learning with deep generative models[J]. Advances in Neural Information Processing Systems, 2014, 4:3581-3589.[9] SHINOZAKI T. Semi-supervised learning for convolutional neural networks using mild supervisory signals[C]//International Conference on Neural Information Processing. Kyoto, Japan:Springer International Publishing, 2016:381-388.[10] PAPANDREOU G, CHEN L C, MURPHY K P, et al. Weakly and semi-supervised learning of a deep convolutional network for semantic image segmentation[C]//IEEE International Conference on Computer Vision. Santiago, Chile:IEEE, 2015:1742-1750.[11] BLUM A. Semi-supervised learning[M]. New York:Springer, 2016:1936-1941.[12] GUO G D, DYER C R. Learning from examples in the small sample case:Face recognition[J]. IEEE Trans on Systems Man & Cybernetics, 2005, 35(3):477-488.[13] YAN H B, LU J W, ZHOU X Z, et al. Multi-feature multi-manifold learning for single-sample face recognition[J]. Neurocomputing, 2014, 143(16):134-143.[14] LU J W, TAN Y P, WANG G. Discriminative multimanifold analysis for face recognition from a single training sample per person[C]//International Conference on Computer Vision. Barcelona, Spain:IEEE, 2011:1943-1950.[15] TAN X Y, CHEN S C, ZHOU Z H, et al. Face recognition from a single image per person:A survey[J]. Pattern Recognition, 2006, 39(9):1725-1745.[16] 陈维桓. 微分几何初步[M]. 北京:北京大学出版社, 1990.CHEN W H. Differential geometry preliminary[M]. Beijing:Peking University Press, 1990. (in Chinese)[17] HUO X M, SMITH A K. A survey of manifold-based learning methods[C]//Recent Advances in Data Mining of Enterprise Data:Algorithms and Applications. Singapore:World Scientific Publishing Co. Inc., 2008:691-745.[18] BENGIO Y, COURVILLE A, VINCENT P. Representation learning:A review and new perspectives[J]. IEEE Trans on Pattern Analysis & Machine Intelligence, 2013, 35(8):1798-1828.[19] RIFAI S, VINCENT P, MULLER X, et al. Contractive auto-encoders:Explicit invariance during feature extraction[C]//International Conference on Machine Learning. Bellevue, WA, USA:Omnipress, 2011:833-840.[20] ALAIN G, BENGIO Y. What regularized auto-encoders learn from the data-generating distribution[J]. J Machine Learning Research, 2014, 15(1):3563-3593.[21] RIFAI S, MESNIL G, VINCENT P, et al. Higherorder contractive auto-encoder[C]//Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Berlin, Heidelberg, Germany:Springer, 2011:645-660.[22] YANG Q W, SUN F C. Small sample learning with high order contractive auto-encoders and application in SAR images[J]. arXiv preprint, 2017.[23] 汪洪桥, 孙富春, 蔡艳宁, 等. 基于局部多分辨特征的SAR图像自动目标识别[J]. 清华大学学报(自然科学版), 2011, 51(8):1049-1054.WANG H Q, SUN F C, CAI Y N, et al. Automatic target recognition of SAR images based on local multi-resolution features[J]. J Tsinghua University (Science and Technology), 2011, 51(8):1049-1054.(in Chinese)