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featureMatrix

Scattering feature matrix

Syntax

smat = featureMatrix(sf,x)
smat = featureMatrix(sf,s)
smat = featureMatrix(___,Name,Value)

Description

smat = featureMatrix(sf,x) returns the scattering features for the scattering decomposition framework sf and the input signal x. x is a real-valued vector or matrix. If x is a vector, smat is an M-by-N matrix, where M is the number of resolutions across all orders of the scattering transform, and N is the resolution of the scattering coefficients. If x is a matrix, smat is an M-by-N-by-P array, where P is the number of columns in x.

The precision of smat depends on the precision specified in the framework sf.

smat = featureMatrix(sf,s) returns the scattering feature matrix for the cell array of scattering coefficients s. s is the output of scatteringTransform applied to an input signal for the scattering decomposition framework sf.

example

smat = featureMatrix(___,Name,Value) returns the scattering feature matrix with additional options specified by one or more Name,Value pair arguments.

Examples

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This example shows how to obtain the scattering feature matrix for a scattering decomposition framework and how to compare the matrix with scattering coefficients.

Load an ECG signal sampled at 180 Hz. Create a scattering decomposition framework that can be used with the signal.

load wecg
Fs = 180;
sf = waveletScattering('SignalLength',numel(wecg),...
    'SamplingFrequency',Fs);

Calculate the scattering feature matrix using the log transformation. Display the dimensions of the matrix.

smat = featureMatrix(sf,wecg,'Transform','Log');
size(smat)
ans = 1×2

   154     8

Now calculate the scattering transform of the signal. Obtain the scattering coefficients. The output is a cell array with three elements. Each element is a table. Confirm the total number of rows in the tables is equal to the number of rows in the matrix.

S = scatteringTransform(sf,wecg);
t1rows = size(S{1},1);
t2rows = size(S{2},1);
t3rows = size(S{3},1);
disp(['Total Number of Rows: ',num2str(t1rows+t2rows+t3rows)])
Total Number of Rows: 154

Display the base-2 log resolution of the zeroth-order scattering coefficients.

disp(['Resolution: ',num2str(S{1}.resolution(1))])
Resolution: -8

Obtain the natural logarithm of the zeroth-order scattering coefficients. Compare the scattering coefficients with the first row in the feature matrix. The number of coefficients in each equals the absolute value of the base-2 log resolution.

logS = log(sf,S);
logScat = logS{1}.signals{1};
[smat(1,:)' logScat]
ans = 8×2

   -1.2914   -1.2914
   -2.4682   -2.4682
   -1.6368   -1.6368
   -1.2716   -1.2716
   -1.6818   -1.6818
   -4.3701   -4.3701
   -1.3199   -1.3199
   -1.0542   -1.0542

Input Arguments

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Scattering decomposition framework, specified as a waveletScattering object.

Input data, specified as a real-valued vector or matrix. If x is a vector, the number of samples in x must equal the SignalLength value of sf. If x is a matrix, the number of rows in x must equal the SignalLength value of sf.

Data Types: double

Scattering coefficients, specified as a cell array. s is obtained from the scattering transform of the scattering decomposition framework sf. For more information, see scatteringTransform.

Name-Value Pair Arguments

Specify optional comma-separated pairs of Name,Value arguments. Name is the argument name and Value is the corresponding value. Name must appear inside quotes. You can specify several name and value pair arguments in any order as Name1,Value1,...,NameN,ValueN.

Example: smat = featureMatrix(sf,x,'Transform','log','Normalization','parent')

Type of normalization to apply to the scattering coefficients, specified as 'none' or 'parent'. If specified as 'parent', scattering coefficients of order greater than 0 are normalized by their parents along the scattering path.

Type of transformation to apply to the scattering coefficients, specified as 'none' or 'log'.

Output Arguments

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Scattering features for the scattering decomposition framework, sf, returned as a real-valued matrix or array. If x is a vector, smat is an M-by-N matrix, where M is the number of resolutions across all orders of the scattering transform and N is the resolution of the scattering coefficients. If x is a matrix, smat is an M-by-N-by-P array, where P is the number of columns in x.

The precision of smat depends on the precision specified in the framework sf.

Introduced in R2018b