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中医脉象信号的参数化双谱估计及其切片分析 被引量:4

Parametric Bispectrum Estimation and Slice Analysis for Pulse Signals
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摘要 将双谱估计的参数化方法应用于脉象信号的分析中.采用非高斯AR模型分析方法,对15例吸毒者和15例正常人脉象信号进行了参数化双谱估计.选取双谱幅值水平切片提取脉象信号的双谱幅值特征,选取双谱相位主值水平切片提取脉象信号的双谱相位主值特征.并根据这些特征,分别给出了吸毒者和正常人脉象信号的判别依据.根据这2种判别依据,识别率分别达93.3%和90%.实验结果表明,双谱估计的参数化方法能较好地分析吸毒者和正常人脉象信号的差异,是一种分析脉象信号的有效方法. Higher-order statistics method is an overhead subject in the fields of signal processing in the world in recent years. The pulse signals are analyzed by applying parametric bispectrum estimation. Non-Gaussian AR model is for calculating the bispectrum of pulse signals for 15 heroin addicts and 15 healthy persons. Characteristic parameters of magnitude bispectrum of the pulse signals are obtained by using horizontal slices of magnitude bispectrum. Characteristic parameters of bispectrum phase of the pulse signals are obtained by using horizontal slices of bispeetrum phase. Moreover,two primary criterions are also obtained by using the characteristic parameters. Exactness ratios of two pnmary criterions reach 93.3% and 90%, respectively. The research result shows that parametric bispectmm estimation for analyzing pulse signals of heroin addicts is really an effective method.
出处 《重庆大学学报(自然科学版)》 EI CAS CSCD 北大核心 2006年第6期47-50,74,共5页 Journal of Chongqing University
基金 重庆市自然科学基金资助项目(CSTC2004BB5061)
关键词 脉象信号 非高斯AR模型 双谱 水平切片 pulse signal non-Gaussian AR model bispectrum horizontal slices
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