An Improved Wavelet Denoising Algorithm Based on Principal Component Analysis

Abstract

In order to eliminate the noise of nonlinear non-stationary signal and restore the pure signal, an improved wavelet denoising algorithm based on principal component analysis is provided in this paper. This novel algorithm improves the threshold function of the commonly used denoising algorithm and can eliminate noise based on useful signal energy ratio. The experimental results show that the improved algorithm can effectively improve the signal-to-noise ratio of the denoising signal and reduce the difference of variance, and then it can achieve a better effect of eliminating noise.