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