A determination method of optimal decomposition level in wavelet threshold de-noising algorithm based on moving average model
Lin Jiang, Chuanchuan Wang, Yonghu Zeng, Liandong Wang · 2017
The wavelet threshold de-noising algorithm is an effective method for removing noise from the noised signal. The decomposition level has a great influence on the wavelet de-noising effect. If the wavelet decomposition level is not properly set, the filtering effect may not be reached, or some useful information may be filtered. Based on the signal to noise ratio of the noised signal under different wavelet decomposition level, a method of determining the wavelet decomposition level based on the moving average model (MA) is proposed. Through the simulation experiment, it is proved that the method can efficiently determine the optimal decomposition level. The research in present paper may be referenced for the application of wavelet threshold de-noising algorithm.