基于短时傅立叶变换的脉象信号的模式识别方法  

The Pulse Signals Pattern Identification Method Based on Short-time Fourier Transform

作　　者：周丹[1] 蔡坤宝[1] 

机构地区：[1]重庆大学,重庆400044

出　　处：《重庆科技学院学报（自然科学版）》2007年第3期49-52,共4页Journal of Chongqing University of Science and Technology：Natural Sciences Edition

基　　金：重庆市自然科学基金项目(CST2004BB5061)

摘　　要：针对脉象信号的非平稳特性,采用全极点滑动窗递归算法,对15例吸毒者和15例正常人脉象信号的离散短时功率谱进行了分析。在得到每一例脉搏波的短时功率谱后,应用奇异值分解有效地提取特征矢量,然后进行模糊c-均值聚类,受测者全部予以正确识别。研究结果表明,基于短时傅立叶变换的奇异值分解方法是一种稳定、有效的特征提取方法;同样,运用模糊c-均值聚类算法不需要模式的先验知识,分类结果正确率较高,简便实用。To fully utilize the nonstationary character of pulse signal,an efficient recursive algorithm with all-pole moving-windows is used to analyze the discrete short-time power spectra of pulse signals for 15 heroin addicts and 15 healthy persons.After obtaining a short-time power spectra of every pulse wave,singular value decomposition is then used to extract feature vector for pattern identification,then the fuzzy c-means cluster algorithm is also used.All subjects characterized by the feature vectors are iden...

关 键 词：脉象信号 短时傅立叶变换 奇异值分解 模糊C-均值聚类 

分 类 号：R318[医药卫生—生物医学工程]