Difference between revisions of "Time–frequency representation"
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(adding hht) 
(library) 

Line 42:  Line 42:  
 1980s   1980s  
    
−   <code>scipy.cwt</code>  +   <code>scipy.signal.cwt</code> 
    
   
Latest revision as of 14:09, 7 May 2018
Some methods for making time–frequency representations of seismic or other time series data.
Name  Year  Note  Python module  Key parameters  

FFT  Fast Fourier transform  1965  aka Discrete Fourier transform  numpy.fft.fft , scipy.fftpack.fft


SFFT  Sparse fast Fourier transform  2013  sfft


STFT  Shorttime Fourier transform  1960s  scipy.signal.stft , scipy.signal.spectrogram , matplotlib.pyplot.specgram

NFFT, noverlap, taper  
ST  Stransform  1994  aka Stockwell transform  PyGFT


CWT  Continuous wavelet transform  1980s  scipy.signal.cwt


DWT  Discrete wavelet transform  1980s  pywt , wavelets.py


SST  Synchrosqueezing transform  Includes reassignment step; aka synchrosqueezed wavelet transform or SSWT.  
MP  Matching pursuit  
OMP  Orthogonal MP  sklearn.linear_model.OrthogonalMatchingPursuit


BP  Basis pursuit  
DMD  Dynamic mode decomposition  
AR  Autoregressive method  
STAR  Shorttime autoregressive method  
KS  Kalman smoother  
EMD  Empirical mode decomposition  1998  PyEMD


EEMD  Ensemble EMD  2009  PyEMD


CEEMD  Complete EEMD  PyEMD


HHT  Hilbert–Huang transform  late 1990s  aka Hilbert spectral analysis; extracts frequencies from EMD IMFs  
FD  Fourier decomposition  2015  See MATLAB code 
Notes
 Several of the Python implementations require the fftw library.
 There is a Python module for reassignment by Dan Meliza called
libtfr
.