如何计算python中select最佳母离散小波的小波能量-香农熵比？

Question

我正在对传感器数据进行小波分析，但是，我意识到 select 有很多小波族。我读过一篇文章，上面写着："The method firstly uses a criterion of maximum energy-to-Shannon entropy ratio to select the appropriate wavelet base for signal analysis."。所以，我想知道如何计算python?

中传感器信号的能量-香农熵比

Answer 1

假设文本的最佳猜测：np.max（总 Energy/Total 熵）|wavelet

import pywt
import numpy as np

#series - input data
#wave   - current wavelet
data=pywt.wavedec(series,wave)
S=0
Etot=0
for d in data:
    E=d**2
    P=E/np.sum(E)
    S+=-np.sum(P*np.log(P))
    Etot+=np.sum(E)
ratio=Etot/S

然后对每个候选小波重复

如何计算python中select最佳母离散小波的小波能量-香农熵比？

How to calculate wavelet energy-to-Shannon entropy ratio to select best mother discrete wavelet in python?

python

wavelet