This example shows how to oversample a 1-D wavelet scattering transform.

Load an ECG signal sampled at 180 Hz, and create a wavelet time scattering network to process the signal. To perform a critically downsampled wavelet scattering transform, do not change the value of theOversamplingFactorproperty insf. Return the number of scattering coefficients for the scattering network.

loadwecgFs = 180; sf = waveletScattering('SignalLength',numel(wecg),'SamplingFrequency',Fs); ncf = numCoefficients(sf)

ncf = 8

Return the 1-D wavelet scattering transform ofwecg, and plot the zeroth-order scattering coefficients. Confirm the number of zeroth-order scattering coefficients is equal toncf.

s = scatteringTransform(sf,wecg); display(['Number of zeroth-order scattering coefficients: ',...num2str(numel(s{1}.signals{1}))])

Number of zeroth-order scattering coefficients: 8

plot(s{1}.signals{1},'x-') gridonaxistighttitle('Zeroth-Order Scattering Coefficients')

To oversample the scattering coefficients by a factor of 2, set theOversamplingFactorproperty ofsfequal to 1 (because $${\log }_{2}2=1$$). Return the number of scattering coefficients for the edited network. Confirm the number of scattering coefficients has doubled.

sf.OversamplingFactor = 1; ncf = numCoefficients(sf)

ncf = 16

Return the wavelet scattering transform ofwecgusing the edited network, and plot the zeroth-order scattering coefficients. Since the number of coefficients in the critically sampled transform is equal to 8, confirm that the number of zeroth-order coefficients in the oversampled transform is equal to 16.

s = scatteringTransform(sf,wecg); figure plot(s{1}.signals{1},'x-') gridonaxistighttitle('Zeroth-Order Scattering Coefficients')