基于小波变换的信号去噪方法研究

Study of signal denoising methods based on wavelet transform

对小波阈值去噪方法进行了研究,阐述了小波变换和小波去噪的基本原理和方法,利用四种自适应阈值规则对含噪信号分别进行去噪处理,并比较了去噪效果。以采集到的语音信号为例,采用不同的阈值去噪方法去噪,在MATLAB下进行仿真,结果表明小波变换既能有效地去除信号噪声,又能较好地保留原信号中的突变信息。

Wavelet threshold denoising methods are studied in this paper, then the basic principles and methods of wavelet transform and wavelet denoising are expounded, four types of adaptive threshold rules are used to denoise the noisy signal, and the denoising effects are compared respectively. Taking the collected speech signal as an example. This paper not only denoised the signal with different methods of threshold denoising, but also simulated in the MATLAB, the results show that wavelet transform can effectively remove the signal noise, and retain the original abrupt signal information well.