非平稳环境下基于小波变换的信号去噪

传统的信号去噪算法往往仅对平稳噪声或缓慢变化的噪声有效,且残留的信号噪声较大。对此,本文研究了一种非平稳环境下基于小波变换的信号去噪算法。该算法对传统的小波阈值法进行了改进,根据信号与噪声在小波域的分布特性以及信号和噪声小波变换模极大值随尺度的变化快慢不同。得到噪声在小波域中的位置以及小波系数大小。实验结果表明:该算法对平稳和非平稳的噪声都能进行较好的去噪。

Noise Reduction based on Wavelet Transform under Non-stationary Environments

This paper addresses the problem of noise reduction under stationary and non-stationary environments, which based on the wavelet transform. This algorithm can overcome the deficiency of the conventional algorithms of noise reduction, which were only efficient for stationary environments and have large level of signal residual noise. The algorithm is based on the different amplitude value change of signal and noise and their distributing character in the wavelet domain, by this way, we can find the site and the value of the noise in the wavelet domain. Experiments confirm that the noise reduction by proposed algorithm is effective to reduce the noise under stationary and non-stationary environments.