scales:表示尺度序列,CWT本质上是将你的信号与不同尺度的小波进行相关,scales 参数确定尺度范围; coefficients:表示信号变换后的小波系数; frequencies :表示对应的频率信息 2.2 参数介绍和选择策略 2.2.1 尺度长度: 在连续小波变换(CWT)中,尺度参数是一个关键的选择,因为它决定了小波函数的宽度,从而影响了频率分辨率。
在Python 中,使用 pywt 库来实现连续小波变换(CWT) 2.1 代码示例 importnumpy as npimportmatplotlib.pyplot as pltimportpywt# 生成三个不同频率成分的信号 3000个点fs=1000# 采样率time= np.linspace(0,1, fs, endpoint=False) # 时间# 第一个频率成分signal1= np.sin(2* np.pi*30* time)# 第二个...
cwt = pywt.ContinuousWavelet('morl') print(cwt) > ContinuousWavelet morl > Family name: Morlet wavelet > Short name: morl > Symmetry: symmetric > DWT: False > CWT: True > Complex CWT: False 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 对象属性: symmetry:对称性 orthogonal:正交性 biorthogon...
transition_steps = 100 n_cycles = 64 fw = np.linspace(1,int(fs/2),transition_steps) # Performing wavelet analysis cwtm = wl.morlet(signal[1], fs, n_cycles = n_cycles, fw = fw, review = [8,9], units = 'mm') # Visualise morlet CWT fig,ax = plt.subplots(figsize=(20,10))...
连续小波变换(Continuous Wavelet Transform,CWT)的数学公式为: 其中, 是连续小波变换的结果, 和 是小波基函数的缩放因子和平移因子, 复共轭小波基函数是小波变换中的一个重要概念。在小波变换中,我们通常使用两类小波基函数:一个是正向小波基函数(Mother Wavelet),另一个是复共轭小波基函数(Complex Conjugate Wavelet...
双树复小波变换(Dual-Tree Complex Wavelet Transforms, DT-CWT)由实部树和虚部树的两个并行的实小波变换构成[1]。复小波表示为: 式中,h(t)和g(t)分别表示复小波的实部和虚部,两个函数均为实函数[2]。双树复小波变换包含两个平行的分解树,分别定义为树A和树B,树A给出双树复小波变换的实部,树B给出虚部,...
tsfresh.feature_extraction.feature_calculators.cwt_coefficients(x, param) 2 3 a π 1 4 ( 1 − x 2 a 2 ) e x p ( − x 2 2 a 2 ) \frac{2}{\sqrt{3a} \pi^{\frac{1}{4}}} (1 - \frac{x^2}{a^2}) exp(-\frac{x^2}{2a^2}) ...
tsfresh.feature_extraction.feature_calculators.cwt_coefficients(x, param) tsfresh.feature_extraction.feature_calculators.energy_ratio_by_chunks(x, param) Calculates the sum of squares of chunk i out of N chunks expressed as a ratio with the sum of squares over the whole series. ...
csd = x_cwt[idx_map[0][con_idx]]\ * np.conjugate(x_cwt[idx_map[1][con_idx]]) csd = x_cwt[idx_map[0][con_idx]] * \ np.conjugate(x_cwt[idx_map[1][con_idx]]) for method in con_methods: method.accumulate(con_idx, csd) @@ -705,8 +706,8 @@ def spectral_connectivity...
Development of thedtcwtlibrary is now taking place inanother repository. Dual-Tree Complex Wavelet Transform library for Python This library provides support for computing 1D, 2D and 3D dual-tree complex wavelet transforms and their inverse in Python.Full documentationis available online. ...