谱熵法进行端点检测的python函数
时间: 2024-05-14 22:12:51 浏览: 13
以下是使用谱熵法进行端点检测的Python函数:
```python
import numpy as np
def spectral_entropy(signal, sf, method='fft', nperseg=None, normalize=False):
"""Compute the spectral entropy of a signal.
Args:
signal (array): Input signal.
sf (float): Sampling frequency of the signal.
method (str): {'fft', 'welch'} Method to use in the spectral estimation.
nperseg (int): Length of each segment for Welch method.
normalize (bool): If True, divide by log2(psd_size) to normalize the entropy between 0 and 1.
Returns:
float: Spectral entropy.
"""
from scipy.signal import welch, periodogram
# Compute the power spectral density
if method == 'fft':
_, psd = periodogram(signal, sf)
elif method == 'welch':
_, psd = welch(signal, sf, nperseg=nperseg)
# Normalize the PSD
psd_norm = psd / psd.sum()
# Compute the spectral entropy
se = -np.sum(psd_norm * np.log2(psd_norm))
# Normalize the spectral entropy
if normalize:
se /= np.log2(psd.size)
return se
```
该函数接受一个输入信号,采样频率,以及用于估计功率谱密度的方法(FFT或Welch)和相应的参数(如果使用Welch方法)。如果指定“normalize”标志,则函数将在0和1之间归一化谱熵值。
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