[1] Wang Ganchang. A breif review of the progress of laser inertial confinement fusion in recent years [J]. China National Nuclear Corporation, 1997, 17(3):266～269

[2] CCortes,V VaPnik.Support vector networks [J]. Machine Learning, 1995,20:273～295

[3] Chen Quansheng, Zhao Jiewen, Zhang Haidong et al.. Indentification of authenticity of tea with near infrared spectroscopy based on support vector machine [J]. Acta Optica Sinica, 2006, 26(6):933～936

[4] Jianfeng Sun, Qi Li, Wei Lu et al.. Image recognition of laser radar using linear SVM correlation filter [J]. Chinese Optics Letters, 2007, 5(9):549～551

[5] Liu Fei, He Yong, Wang Li. Methods for the prediction of sugar content of rice wine using visible near-infrared spectroscopy [J]. Acta Optica Sinica, 2007, 27(11):2054～2058

[6] Michael E. Tipping. Sparse bayesian learning and the relevance vector machine [J]. Journal of Machine Learning Research, 2001, 1： 211～244

[7] Michael E. Tipping. Bayesian inference: an introduction to principles and practice in machine learning [M]. Heidelberg: springer Barlin, 2004,41～62

[8] Chen Shizhe. Research on the key techniques of microelectronic products vision inspection [D]. Harbin: Harbin Institute of Technology, 2006. 93～95

[9] Tang Faming. Study of support vector machines algorithm based on statistical learning theory [D]. Wuhan: Huazhong University of Science and Technology, 2005. 73～86

[10] M.Turk, A.Pentland. Face recognition using eigenfaces [C]. IEEE Conference on Computer Vision and Pattern Recognition, 1994, 586～591

[11] A.Pentland, B.Moghaddam, T.Starner. View-based and modular eigenspaces for face recognition [C].IEEE Conference on Computer Vision and Pattern Recognition, 1994, 84～91

[12] Begüm Demir, Sarp Ertürk. Hyperspectral image classification using relevance vector machines [J]. IEEE Geosciences And Remote Sensing Letters, 2007, 4(4):586～590

[13] D.Datcu L, J.M.Rothkrantz. Facial expression recognition with relevance vector machines [C]. IEEE International Conference on Multimedia and Expo, 2005,193～196

[14] Liangyu Lei, Qing Zhang. Relevance vector machine based bearing fault diagnosis [C]. IEEE International Conference On Machine Learning And Cybernetics, 2006, 3492～3496

[15] Jin Yuan, Kesheng Wang, Tao Yu et al.. Integrating relevance vector machines and genetic algorithms for optimization of seed-separating process [J]. Engineering Applications of Artificial Intelligence, 2007, 20(7):970～979

[16] Bo Yu, Zongben Xu. A comparative study for content-based dynamic spam classification using four machine learning algorithms [J]. Knowledge-Based System, 2008, 21(4):355～362