Wavelet Signal Analyzer
Analyze and compress signals using wavelets
The Wavelet Signal Analyzer app enables visualization, analysis, and compression of 1-D signals using decimated and nondecimated discrete wavelet and wavelet packet transforms. The app plots the decomposition of the signal and its corresponding reconstruction. The app also shows statistics of the decomposition, including the approximate frequency band of each component. With the Wavelet Signal Analyzer app, you can:
Access all single-channel, real- and complex-valued 1-D signals in the MATLAB® workspace.
Compare decompositions from different analyses by varying the wavelet or the decomposition level.
Visualize the time-aligned coefficients.
Extend the signal periodically or by reflection before computing the wavelet transform.
Apply a global threshold or level-dependent thresholds to the decomposition to compress the signal.
Plot the energy for all decomposition levels and display autocorrelations and histograms of the original and compressed coefficients at a specific level.
Export decomposition coefficients, compressed coefficients, and compressed signals to the MATLAB workspace.
Generate MATLAB scripts to reproduce results in your workspace.
The Wavelet Signal Analyzer app supports single- and double-precision data.
Open the Wavelet Signal Analyzer App
MATLAB Toolstrip: On the Apps tab, under Signal Processing and Communications, click the app icon.
MATLAB command prompt: Enter
waveletSignalAnalyzer opens the Wavelet Signal Analyzer
app. Once the app initializes, import a signal from your workspace for analysis and
compression by clicking Import.
waveletSignalAnalyzer( opens the
Wavelet Signal Analyzer app and imports, decomposes, and displays the
nondecimated discrete wavelet transform of
sig using the
modwt function with the
sym4 wavelet and default
sig is a variable in the workspace.
sig can be:
A 1-by-N or N-by-1 real- or complex-valued vector.
Single- or double-precision data.
To decompose one channel of a multichannel signal, import the channel programmatically. For example, decompose the 10th channel of the multichannel Espiga3 EEG data set using these commands.
load Espiga3 waveletSignalAnalyzer(Espiga3(:,10))
To decompose different 1-D signals simultaneously, run multiple instances of Wavelet Signal Analyzer.
Version HistoryIntroduced in R2023a
R2023b: Support for new transforms
Wavelet Signal Analyzer supports these additional transforms:
Decimated discrete wavelet transform
Decimated discrete wavelet packet transform
Maximal overlap discrete wavelet packet transform
R2023b: Plot autocorrelation of wavelet coefficients
For all decomposition methods, you can use Wavelet Signal Analyzer to plot the autocorrelation of the wavelet coefficients at the decomposition level or at the terminal node that you specify. You can vary the order of the moving average filter and the number of lags. The plot includes the upper and lower bounds of the 95% confidence interval.
R2023b: Support added for level- and node-specific thresholds
For all decomposition methods, you can use Wavelet Signal Analyzer to apply different thresholds to individual decomposition levels or terminal nodes.