A method for choosing the wavelet decomposition level in structural fault analysis

Adaptive selection and simulation of optimal decomposition level in threshold de-noising algorithm based on wavelet transform

selection of wavelet decomposition level have a direct effect on the quality of image fusion.

Threshold de-noising based on wavelet transform which is proposed to determine the decomposition order adaptively is an efficient method to reduce the white noise in the digital signal.

In this method,the determination of the threshold,the decomposition order and the threshold estimation model are three key problems that need to be solved.

In this paper,which is based on the analysis of the characteristic of noisy signal s wavelet transform,a self-adaptive method to determine a proper decomposition order is proposed according to the white noise verification based on self-correlation function.

According to the law that the contour fuzziness of the low-frequency sub-band and the detail information of the high-frequency sub-band increase with the growth of the wavelet decomposition levels,an effect selection method of the optimal decomposition level is proposed.

Preparation of a nano-composite LDA/MMT by novel intercalation-decomposition process;