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Time-Frequency Analysis

Spectrogram, synchrosqueezing, reassignment, Wigner-Ville, time-frequency marginals, data-adaptive methods

Signal Processing Toolbox™ provides functions and apps that enable you to visualize and compare time-frequency content of nonstationary signals. Compute the short-time Fourier transform and its inverse. Obtain sharp spectral estimates using reassignment or Fourier synchrosqueezing. Plot cross-spectrograms, Wigner-Ville distributions, and persistence spectra. Extract and track time-frequency ridges. Estimate instantaneous frequency, instantaneous bandwidth, spectral kurtosis, and spectral entropy. Perform data-adaptive time-frequency analysis using empirical or variational mode decomposition and the Hilbert-Huang transform.

Apps

Signal Analyzer Visualize and compare multiple signals and spectra
Signal Labeler Label signal attributes, regions, and points of interest

Functions

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fsst Fourier synchrosqueezed transform
ifsst Inverse Fourier synchrosqueezed transform
instbw Estimate instantaneous bandwidth
instfreq Estimate instantaneous frequency
kurtogram Visualize spectral kurtosis
pkurtosis Spectral kurtosis from signal or spectrogram
pentropy Spectral entropy of signal
pspectrum Analyze signals in the frequency and time-frequency domains
spectrogram Spectrogram using short-time Fourier transform
xspectrogram Cross-spectrogram using short-time Fourier transforms
stft Short-time Fourier transform
dlstft Deep learning short-time Fourier transform
stftLayer Short-time Fourier transform layer
stftmag2sig Signal reconstruction from STFT magnitude
iscola Determine whether window-overlap combination is COLA compliant
istft Inverse short-time Fourier transform
tfridge Time-frequency ridges
wvd Wigner-Ville distribution and smoothed pseudo Wigner-Ville distribution
xwvd Cross Wigner-Ville distribution and cross smoothed pseudo Wigner-Ville distribution
emd Empirical mode decomposition
vmd Variational mode decomposition
hht Hilbert-Huang transform

Topics

Time-Frequency Gallery

Examine the features and limitations of the time-frequency analysis functions provided by Signal Processing Toolbox.

Practical Introduction to Continuous Wavelet Analysis(Wavelet Toolbox)

This example shows how to perform and interpret continuous wavelet analysis.

FFT-Based Time-Frequency Analysis

Display the spectrogram of a linear FM signal.

Instantaneous Frequency of Complex Chirp

Compute the instantaneous frequency of a signal using the Fourier synchrosqueezed transform.

Detect Closely Spaced Sinusoids

Compute the instantaneous frequency of two sinusoids using the Fourier synchrosqueezed transform. Determine how separated the sinusoids must be for the transform to resolve them.

Radar and Communications Waveform Classification Using Deep Learning(Phased Array System Toolbox)

This example shows how to classify radar and communications waveforms using the Wigner-Ville distribution (WVD) and a deep convolutional neural network (CNN).

Pedestrian and Bicyclist Classification Using Deep Learning(Radar Toolbox)

Classify pedestrians and bicyclists based on their micro-Doppler characteristics using a deep learning network and time-frequency analysis.

Featured Examples