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rSFA (version 1.02)

Slow Feature Analysis in R

Description

Slow Feature Analysis in R, ported to R based on the matlab versions SFA toolkit 1.0 by Pietro Berkes and SFA toolkit 2.8 by Wolfgang Konen for matlab.

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Version

Install

install.packages('rSFA')

Monthly Downloads

229

Version

1.02

License

GPL (>= 2)

Maintainer

Martin Zaefferer

Last Published

November 20th, 2012

Functions in rSFA (1.02)

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.

sfaCheckCondition

Check Condition of a matrix for SFA

gaussClassifier

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

sfaClassPredict

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.