基于稀疏表示的混合傅立叶-小波心脏磁场信号去噪

L. Bing, Wen Si, Rong Tan, Xiaolei Han, Fuqiang Liu, Jiang Yu
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引用次数: 0

摘要

为了有效去除心脏磁图(MCG)信号噪声,提高心脏病诊断的准确性,采用基于稀疏表示的心脏傅里叶-小波去噪方法对心脏磁信号进行处理。该降噪方法结合了傅里叶和小波的优点。在傅里叶域进行初始去噪处理,然后在小波域去除残余噪声。基于稀疏表示理论,将小波去噪转化为优化问题,建立了基于稀疏表示的去噪模型。通过消除小波系数的稀疏性,达到去噪的目的。实验结果验证了本文方法能有效提高心磁信号的去噪效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hybrid Fourier-Wavelet Heart Magnetic Field Signal Denoising Based on Sparse Representation
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.
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