摘要
采用AR模型参数化双谱估计法对15例吸毒者和15例正常人的脉象信号进行了参数化双谱估计,在得到每一例脉搏波的归一化双谱幅值对角切片后,应用K-L变换得到30个样本特征矢量,利用这些特征矢量和BP神经网络对两类脉象数据进行分类,得到平均的正确识别率高达96.7%,研究结果表明应用双谱对角切片作为脉象信号特征矢量,利用BP神经网络对海洛因吸毒者和正常人的脉象信号进行分类,具有很高的识别率。
An AR model parameterized bispectrum estimation method is proposed to estimate the bispectra of the pulse signals for 15 heroin addicts and 15 healthy persons. The diagonal slice of the normalized bispectrum magnitude for every pulse wave is used to get 30 samples of the feature vector by using the K-L transform. The pulse signals are then identified by using these feature vectors and BP neural networks, the average identification rate of the trained networks reaches 96.7%.
出处
《自动化技术与应用》
2007年第11期33-35,共3页
Techniques of Automation and Applications
基金
重庆市自然基金科学项目(CST2004BB5061)
