Wavelet Signal Analyzer

Analyze and compress signals using wavelets

Since R2023a

Description

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.
Visualize statistics of the decomposition and explore how compression impacts them.
- For all decomposition levels, plot the energy. For nondecimated wavelet decompositions, you can also plot the variance of the coefficients.
- For a decomposition level you specify, display the autocorrelations and histograms of the coefficients.
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.

Examples

Programmatic Use

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`waveletSignalAnalyzer`

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(sig)`

waveletSignalAnalyzer(sig) 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 settings.

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.

Tips

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 History

Introduced in R2023a

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R2024a: Plot variance of nondecimated wavelet coefficients

For nondecimated wavelet decompositions, you can use Wavelet Signal Analyzer to plot the variance estimates of the coefficients at all levels. You can visualize how the variance and confidence intervals change as you compress the signal. You can:

Specify a biased or unbiased estimator.
Choose a chi-square or Gaussian distribution to compute the confidence intervals.
Set a confidence level.

For more information, see Explore Signal Decomposition.

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.