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rSFA (version 1.01)

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

1.01

License

GPL (>= 2)

Maintainer

M Zaefferer

Last Published

May 9th, 2012

Functions in rSFA (1.01)

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.

gaussClassifier

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.

sfaCheckCondition

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

sfaClassPredict

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