为了克服 MSE 存在的缺陷，论文提出了复合多尺度模 糊 熵 ( CM

In order to overcome the shortcomings of MSE, the paper proposes a compound multi-scale fuzzy entropy (CMFE) algorithm. In the CMFE algorithm, FuzzyEn is first used to <br>replace the sample entropy, which overcomes the similarity measure mutation. Secondly, for <br>the effect of the fuzzy entropy calculation due to the shortened time series during the coarse-graining process, different coarseness under the same scale factor is used. The average value of the fuzzy entropy of the granulation sequence is taken as the fuzzy entropy value under this scale factor. The specific calculation steps of CMFE are as follows

In order to overcome the defects of MSE, the paper proposes the compound multiscale paste entropy ( CMFE ) calculation. CMFE calculation method, first use<br>FuzzyEn replaced sample entropy and overcame the mutation of similarity measurement. Secondly, for the fuzzy entropy calculation due to the shorter time series in the process of coarse granulation,<br>The effect is used to use the mean of the mold entropy of different coarse granulation sequences under the same scale factor as the mold entropy value under the scale of the factor. The steps for the specific calculation of CMFE are as follows

In order to overcome the shortcomings of MSE, a compound multi-scale fuzzy entropy (CMFE) algorithm is proposed. In CMFE algorithm, the first step is to use<br>Fuzzy en replaces sample entropy and overcomes the mutation of similarity measurement. Secondly, fuzzy entropy is calculated in the process of coarse-grained due to the shorter time series<br>The mean value of fuzzy entropy of different coarse-grained sequences under the same scale factor is used as the fuzzy entropy value under the scale factor. The specific calculation steps of CMFE are as follows<br>