V. N. Vapnik, “The Nature of Statistical Learning Theory,” Springer, New York, 1995. http://dx.doi.org/10.1007/978-1-4757-2440-0
 J. T. Chien and C. P. Liao, “Maximum Confidence Hidden Markov Modeling for Face Recognition,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 30, No. 8, 2008, pp. 606-616. http://dx.doi.org/10.1109/TPAMI.2007.70715
 G. B. Singh and H. Song, “Using Hidden Markov Models in Vehicular Crash Detection,” IEEE Transactions on Vehicular Technology, Vol. 58, No. 3, 2009, pp. 1119-1128. http://dx.doi.org/10.1109/TVT.2008.928904
 S. Sunny and P. S. David, “Feature Extraction Methods Based on Linear Predictive Coding and Wavelet Packet Decomposition for Recognizing Spoken Words in Malayalam,” 2012 International Conference on Advances in Computing and Communications (ICACC), Cochin, Kerala, 2012, pp. 27-30. http://dx.doi.org/10.1109/ICACC.2012.7
 T. Stutz and A. Uhl, “Efficient and Rate-Distortion Optimal Wavelet Packet Basis Selection in JPEG2000,” IEEE Transactions on Multimedia, Vol. 14, No. 2, 2012, pp. 264-277. http://dx.doi.org/10.1109/TMM.2011.2177644
 J. F. Al-Asad, A. Moghadamjoo and Y. Leslie, “Ultrasound Image Denoising through Karhunen-Loeve (K-L) Transform with Overlapping Segments,” IEEE International Symposium on Biomedical Imaging: From Nano to Macro, (ISBI’09), 2009, pp. 318-321.
 D. Xie and J. Q. Zhu, “Research on Method of Main Reducer Assembly Quality Evaluation Based on K-L Transform and Support Vector Machine,” 2011 International Conference on Electric Information and Control Engineering (ICEICE), 2011, pp. 677-680.
 Q. Zhao, J. L. Cao and Y. L. Hu, “Joint Optimization of Feature Selection and Parameters for Multi-class SVM in Skin Symptomatic Recognition,” International Conference on Artificial Intelligence and Computational Intelligence, 2009, pp. 407-411.
 C.-C. Chang and C.-J. Lin, “LIBSVM: A Library for Support Vector Machines”. http://www.csie.ntu.edu.tw/~cjlin/libsvm