Hybrid Fourier-Wavelet Heart Magnetic Field Signal Denoising Based on Sparse Representation

被引:5
作者
Bing, Lu [1 ]
Han, Xiaolei [1 ]
Si, Wen [1 ]
Liu, Fuqiang [1 ]
Tan, Rong [1 ]
Yu, Jiang [1 ]
机构
[1] Shanghai Business Sch, Sch Informat & Comp Sci, Shanghai 201400, Peoples R China
来源
2019 3RD INTERNATIONAL CONFERENCE ON DATA SCIENCE AND BUSINESS ANALYTICS (ICDSBA 2019) | 2019年
基金
上海市自然科学基金;
关键词
MCG; Denoising; Fourier wavelet; Sparse representation;
D O I
10.1109/ICDSBA48748.2019.00062
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In order to effectively remove the magnetocardiography (MCG) signal noise and improve the accuracy of heart disease diagnosis, a cardiac Fourier-wavelet denoising method based on sparse representation is used to process the cardiac magnetic signal. The noise reduction method combines the advantages of Fourier and wavelet. The initial denoising process is performed in Fourier domain, and then the residual noise is removed in the wavelet domain. Based on the theory of sparse representation, the wavelet denoising is transformed into an optimization problem, and a denoising model based on sparse representation is established. By eliminating the sparsity of wavelet coefficients, the purpose of noise removal is achieved. The experimental results verify that the method of the paper can effectively improve the denoising effect of the cardiac magnetic signal.
引用
收藏
页码:266 / 268
页数:3
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