小波变换和支持向量机相融合的ECG身份识别算法  

A Method Based on Wavelet Transform and SVM of ECG Human Identification

作　　者：彭辉[1,2] 

机构地区：[1]浙江大学计算机学院,浙江杭州310018 [2]浙江警官职业学院,浙江杭州310018

出　　处：《微电子学与计算机》2013年第3期152-155,共4页Microelectronics & Computer

摘　　要：心电图信号(ECC)受到设备、检测者心情等影响,含有噪声且特征具有高维性,为了提高了身份识别的正确率,提前出一种小波变换和支持向量机相融合的ECG身份识别算法.首先小波变换对采集的心电图信号进行预处理,消除各种噪声;然后采用相关分析对ECG特征进行降维处理,消除冗余特征;最后将特征向量输入到支持向量机进行训练,建立基于ECG的身份识别模型.仿真结果表明,该方法提高了身份识别正确率和速度,有一种有效的身份识别算法.The electrocardiography signal includes noise and has high dimension due to the acquisition of equipment, testing the mood, in order to improve the identification accuracy, this paper proposes a new ECG signal identification method based on wavelet transform and support vector machine. Firstly, wavelet transform is used to eliminate the nose of ECG signal, and then the correlation analysis method is used to reduce the feature dimension; lastly, support vector machine is used to build ECG signal identification model. The simulation results show that the method improves the identification accuracy and speed, it is efficient identification algorithm.

关 键 词：心电图信号 身份识别 小波变换 相关分析 支持向量机 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]