Improved Signal Processing Algorithm Based on Wavelet Transform

Abstract

Wavelet analysis is a rapidly developing emerging discipline, at present; it has been widely used in practice. Study wavelet’s new theory, new method and new application have important theoretical significance and practical value. Based on the problem of poor performance of using traditional wavelet transformation algorithm in signal denoising, this paper puts forward a improved scheme based on tradeoff between soft and hard threshold, the scheme is established on the basis of traditional soft threshold, hard threshold, and the obtained estimated wavelet coefficients value of this scheme are between soft threshold and hard threshold methods, so call it the tradeoff between soft and hard threshold method. Implementation steps of the improved scheme based on soft and hard threshold tradeoff are, firstly establishing wavelet coefficient estimator of soft and hard threshold tradeoff method, and adding factor in threshold estimator, so as to adjust the size of the estimated wavelet coefficients. Simulation experiments show that the proposed soft, hard threshold tradeoff based signal threshold improved deniosing method shows a strong effect of the practical signal denoising, the obtained reconstructed signal SNR has been tremendously improved than the traditional denoising method.