Signal Multiresolution Analyzer
Decompose signals into time-aligned components
The Signal Multiresolution Analyzer app is an interactive tool for visualizing multilevel wavelet- and data adaptive-based decompositions of real-valued 1-D signals and comparing results. The app supports single- and double-precision data. With the app, you can:
Access all the real-valued 1-D signals in your MATLAB® workspace.
Generate decompositions using fixed-bandwidth and data-adaptive multiresolution analysis (MRA) methods:
Fixed-bandwidth: Maximal overlap discrete wavelet transform (MODWT) (default), and tunable Q-factor wavelet transform (TQWT)
Data-adaptive: Empirical mode decomposition (EMD), empirical wavelet transform (EWT), and variational mode decomposition (VMD)
Adjust default parameters, and visualize and compare multiple decompositions.
Choose decomposition levels to include in the signal reconstruction.
Obtain frequency ranges of the decomposition levels.
Determine the relative energy of the signal across levels.
Export reconstructed signals and decompositions to your workspace.
Recreate decompositions in your workspace by generating MATLAB scripts.
Open the Signal Multiresolution Analyzer App
MATLAB Toolstrip: On the Apps tab, under Signal Processing and Communications, click the app icon.
MATLAB command prompt: Enter
Wavelet — Orthogonal wavelet family
sym (default) |
Orthogonal wavelet family to use to generate the multiresolution analysis (default), specified as:
db— Daubechies wavelets
fk— Fejér-Korovkin wavelets
Wavelet parameter is applicable only for
generating a multiresolution analysis.
For more information about the wavelets, use the
waveinfo function. For example, to learn more about Daubechies wavelets,
Interpolation — Interpolation method
spline (default) |
Interpolation method to use for envelope construction in empirical mode decomposition, specified as one of the following:
spline— Cubic spline interpolation
pchip— Piecewise cubic Hermite interpolating polynomial method
Interpolation parameter is applicable only for
generating an empirical mode decomposition. You can change other options with the app
when creating empirical mode decompositions. For more information, see
signalMultiresolutionAnalyzer opens the Signal Multiresolution
Analyzer app. Once the app initializes, import a signal for analysis by clicking
signalMultiresolutionAnalyzer( opens the
Signal Multiresolution Analyzer app and imports, decomposes, and plots the
multiresolution analysis of
modwt with the
and default settings.
sig is a variable in the workspace.
sig can be:
A 1-by-N or N-by-1 real-valued vector.
Single- or double-precision data.
By default, the app plots the decomposition levels as functions of sample index. To plot with respect to time, you can set a sample rate or sample period using the app.
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 signalMultiresolutionAnalyzer(Espiga3(:,10))
To decompose different 1-D signals simultaneously, run multiple instances of Signal Multiresolution Analyzer.
For the MODWT and TQWT decomposition methods, the script generated by Signal Multiresolution Analyzer supports
gpuArray(Parallel Computing Toolbox) inputs.
For the fixed-bandwidth methods, MODWT and TQWT, Signal Multiresolution Analyzer reports the theoretical frequency ranges of the decomposition levels. For the data-adaptive methods, EMD, EWT, and VMD, the app reports the measured bandwidth.
 Percival, Donald B., and Andrew T. Walden. Wavelet Methods for Time Series Analysis. Cambridge Series in Statistical and Probabilistic Mathematics. Cambridge ; New York: Cambridge University Press, 2000.
Version HistoryIntroduced in R2018b
R2022a: Support for additional decomposition methods
R2021b: Single-precision support
The Signal Multiresolution Analyzer app supports single-precision data.
R2021a: MATLAB Online support for Signal Multiresolution Analyzer
The Signal Multiresolution Analyzer app is supported in MATLAB Online™.