|本期目录/Table of Contents|

[1]李战明,张晓东.基于Teager边界谱心音身份识别的特征提取算法[J].工业仪表与自动化装置,2015,(05):3.
　LI Zhanming,ZHANG Xiaodong.Based on Teager boundary spectrum feature extraction of heart sounds identification algorithm[J].Industrial Instrumentation & Automation,2015,(05):3.
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基于Teager边界谱心音身份识别的特征提取算法(PDF)

《工业仪表与自动化装置》[ISSN:1000-0682/CN:61-1121/TH]

卷:
期数:
2015年05期
页码:
3
栏目:
出版日期:
2015-10-15

文章信息/Info

Title:
Based on Teager boundary spectrum feature extraction of heart sounds identification algorithm
文章编号:
1000-0682(2015)05-0000-00
作者:
李战明; 张晓东
（兰州理工大学 电气工程与信息工程学院，兰州 730050）
Author(s):
LI Zhanming; ZHANG Xiaodong
(College of Electrical Engineering and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China)
关键词:
心音信号; 双自适应提升小波; 去噪; 边界谱
Keywords:
heart sound signal;  double adaptive lifting wavelet;  denoising;  boundary spectrum
分类号:
O236
DOI:
-
文献标志码:
A
摘要:
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。
Abstract:
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 boundary spectrum as characteristic parameters used for identity recognition. Double adaptive lifting wavelet ascension 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 demodulation to track the signal instantaneous amplitude and instantaneous frequency, and transformable spectrum 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.

参考文献/References:

[1] Maragos P,kaiser J F, Quatieri T F. Energy seperation in modulations with application to speech to speech analysis[J].IEEE Transactions on Signal Processing,1993, 41(10):3024-3051.[2] Teager H M. Some observations on oral air flow during phonation[J].IEEE Transactions on Acoustics, speech, and signal Processing,1980,28(5):599-601.[3] 樊新海,何嘉武,王战军,等.基于Teager能量算子的解调方法[J].装甲兵工程学院学报,2009(4):60-63.[4] 高慧,苏广川,陈善广.基于Teager能量算子(TEO)非线性特征的语音情绪识别[J].航天医学与医学工程,2005, 18(6):427-431.[5] 楼红伟,胡光锐.基于Teager能量算子和频率弯折小波变换的语音识别特征参数[J].上海交通大学学报,2003(2): 79-82.[6] 庞春颖,韩立喜,刘记奎.基于双自适应提升算法的心音信号去噪研究[J].震动与冲击,2013,32(19):183-186.[7] Cemma Piella, Henk J A M. Heijmans. Adaptive lifting schemes with perfect reconstruction[J]. IEEE Trans. On signal processing, 2002,50(7):1620-1630.[8] 王凤利,赵德友.基于提升小波和局域波的故障特征提取[J].仪器仪表学报,2010,4(31):789-793.[9] 陈晓曦,王延杰,刘恋.小波阈值去噪法的深入研究[J].激光与红外,2012,1(42):105-110.[10] 向磊,熊卫华,李俊峰,等.EEMD和Hilbert边际谱在语音情感特征提取中的应用[R]. Hefei,China.Proceeding of the 31st Chinese Control Conference, 2012: 25-27.[11] ZHAOHUA WU, NORDEN EHUANG. Ensemble empirical mode decomposition: A noise-assisted data analysis method. Center for Ocean-Land-Atmosphere Studies,2005.[12] Shen Zhiyuan, Wang Qiang,Shen Yi.Accent extraction of emotional speech based on modified ensemble empirical mode decomposition[C]. 2010 IEEE International Instru- mentation and Measurement Technology Conference, 2010: 600-604.[13] 张卫,张雪英,孙颖.EMD结合Teager能量用于语音情感识别[J].科学技术与工程,2013,13(24):7240-7243.[14] 刘敏,赵治栋.基于Teager-Huang边界谱的心音身份识别确认.杭州电子科技大学学报,201333(5):86-89.[15] 李辉,郑海起,唐力伟.Tegea-Huang变换在齿轮裂纹故障诊断中的应用[J].振动、测试与诊断,2010(1):1-5.

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更新日期/Last Update: 1900-01-01