改进阈值函数的小波去噪算法

Wavelet denoising algorithm with improved threshold function

针对小波软、硬阈值函数去噪后信号存在局部震荡和边缘模糊导致去噪效果不佳的问题,研究了小波去噪原理和优化阈值函数的规则,设计了一种具有连续性、灵活性和恒定偏差小的可调阈值函数,提出了一种基于改进阈值函数的小波去噪算法,将其应用于含有高斯白噪声的信号中进行去噪。实验表明,相较于传统方法,所提方法对仿真信号和心电信号都具有灵活性和适用性,并且去噪后信号的信噪比提升了16.21%,皮尔逊相关系数增大了1.62%。因此,本文所提算法具有可行性,可有效保留特征信息,去噪效果更加理想。

The principle of wavelet denoising and the rule of optimizing threshold function are studied,aiming at the problem that local oscillation and edge blur of signal after wavelet soft and hard threshold function denoising lead to poor denoising effect.An adjustable threshold function with continuity,flexibility and small constant deviation is designed.A wavelet denoising algorithm based on improved threshold function is proposed,which is applied to denoising signals containing Gaussian white noise.Experimental results show that compared with traditional methods,the proposed method has flexibility and applicability to simulated signals and ECG signals,and the signal-to-noise ratio of the signal after denoising is improved by 16.21%,and the Pearson correlation coefficient is increased by 1.62%.Therefore,the algorithm is feasible,which can effectively retain feature information,and the denoising effect is more ideal.