基于Teager边界谱心音身份识别的特征提取算法

Based on Teager boundary spectrum feature extraction of heart sounds identification algorithm

心音信号是一种典型的非平稳信号,传统信号处理方法的应用受到很大限制。该文提出通过双自适应提升小波对心音信号去噪处理和提取心音信号的Teager-Huang边界谱作为特征参数用于身份的识别。双自适应提升小波采用自适应更新和自适应预测构造小波函数,通过将传统的硬阈值和软阈值函数相结合,构造了一个改进的阈值函数进行心音信号去噪处理,表现出良好的去噪效果,并增强了信号的局部特征。Teager能量算子能对单分量IMF的幅值和频率进行解调,并以此追踪到信号的瞬时幅值和瞬时频率,而且基于EEMD和Teager-Huang变换的THT谱比HHT谱具有较高的时频分辨率,且计算量少,优于HHT谱。

Heart sound signal is a kind of typical nonstationary signal , so application is limited by a lot of traditional signal processing method .This paper puts forward using double adaptive lifting wavelet of heart sound signals denoising processing and extraction of heart sounds signal Teager -Huang bound-ary spectrum as characteristic parameters used for identity recognition .Double adaptive lifting wavelet as-cension adopts adaptive update and adaptive prediction structure wavelet function , through the traditional hard threshold and soft threshold function , constructing an improved threshold function of heart sounds signal denoising processing , showing good denoising effect , and enhanceing the local characteristics of the signal .Teager energy operator to the amplitude and frequency of single component of the IMF demod-ulation to track the signal instantaneous amplitude and instantaneous frequency , and transformable spec-trum based on the EEMD and Teager THT -Huang than HHT has higher time -frequency resolution , and less amount of calculation and is better than that of HHT spectra .