多指标融合的小波去噪最佳分解尺度选择方法1

借助最小均方根误差、信噪比及光滑度变化随小波分解尺度增加的收敛特性，提出了一种多指标融合的小波去噪最佳分解尺度选择方法。该方法利用信息熵来融合小波去噪过程中不同方面的变化特征，能够更全面地反映小波去噪结果与分解尺度间的对应关系；通过定量识别融合指标变化的拐点，能够有效识别小波去噪的最佳分解尺度。针对不同类型的去噪信号进行实验分析并与现有方法进行比较，验证了本文提出方法的有效性与优越性。

A Hybrid Indicator for Determining the Best Decomposition Scale of Wavelet Denoising

In this paper, a hybrid indicator is proposed to determine the best grading scale of wavelet de-noising. The variation rule of the root mean square error, signal to noise ratio and smoothness with regard to the decomposition scale is employed to develop the hybrid indicator. Different characteristics in the process of wavelet de-noising are considered to define the hybrid indicator, and the best decomposition scale can be determined by identifying the inflection point of the hybrid indicator. A series of experiments on different signals are utilized to test the effectiveness of the hybrid indictor. The comparisons with current methods are further used to demonstrate the advantages of the hybrid indictor.