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