文献类型：期刊文献

英文题名：Research and application of non-negative matrix factorization with sparseness constraint in recognition of traditional Chinese medicine pulse condition

作者：Guo, Rui[1]; Wang, Yiqin[1]; Yan, Haixia[1]; Li, Fufeng[1]; Xu, Zhaoxia[1]; Yan, Jianjun[2]

机构：[1] Laboratory of Information Access and Synthesis of TCM Four Diagnosis, Shanghai University of Traditional Chinese Medicine, Shanghai, China; [2] Center for Mechatronics Engineering, East China University of Science and Technology, Shanghai, China

年份：2010

起止页码：682

外文期刊名：2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2010

收录：EI(收录号：20110913708927)

语种：英文

外文关键词：Time domain analysis - Biomedical signal processing - Non-negative matrix factorization - Extraction - Matrix algebra - Medicine - Feature extraction

摘要：n this paper, the recognition method based on non-negative matrix factorization with sparseness constraint (NMFs) combined with the support vector machine (SVM) was proposed to identify the type of the common pulse condition of Chinese Traditional Medicine (TCM). First, pulse data were factorized by NMFs to obtain projection coefficients as training sample set to build recognition mode with SVM. Then the method proposed was compared with the classical time-domain method of pulse feature extraction. And time-domain features were extracted to identify the type of pulse with the same SVM classifier. Finally, the results showed that projection coefficients obtained by NMFs more use of recognition of TCM pulse. ?2010 IEEE.