Update a covariance object
Degree 2 Expansion
Return a SFA function as a quadratic form.
Load a SFA object.
Preprocessing for SFA classification
Custom Repeater Function
Backslash operator.
Classifier for SFA demos
Execute learned function for input data
Add noisy copies for parametric bootstrap
Save a SFA object.
Perform non-linear regression
Computes the eta value of a signal (slowness)
Load a GAUSS object.
Custom Size Function.
Fix a covariance object
The SFA2 algorithm, SFA with degree 2 expansion.
Check Condition of a matrix for SFA
Parametric Bootstrap
Custom Nonlinear Dimension Calculation
A step in the SFA2 algorithm.
Expand a signal in the for Nonlinear Expansion demo
Save a GAUSS object.
Create a new covariance object.
Improved Principal Component Analysis on a covariance object
Update a step of the SFA algorithm.
Transform a covariance object
Custom repmat Function
Predict Class for SFA classification
The SFA1 algorithm, linear SFA.
Slow Feature Analysis in R
Principal Component Analysis on a covariance object
Create an Gaussian classifier object
Predict Class for SFA classification
Create structured list for linear SFA
Create structured list for expanded SFA
Degree 2 Dimension Calculation
A step in the SFA1 algorithm.
Helper Function of SFA.
Calculates the first derivative of signal data