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rSFA (version 1.00)

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

401

Version

1.00

License

GPL (>= 2)

Maintainer

M Zaefferer

Last Published

January 29th, 2012

Functions in rSFA (1.00)

Add noisy copies for parametric bootstrap

Helper Function of SFA

Custom Nonlinear Dimension Calculation

Load a SFA object.

Custom repmat Function

Computes the eta value of a signal (slowness)

sfaCheckCondition

Check Condition of a matrix for SFA

Improved Principal Component Analysis on a covariance object

Create a new covariance object.

Expand a signal in the for Nonlinear Expansion demo

Update a step of the SFA algorithm.

Predict Class for SFA classification

Save a SFA object.

Create structured list for linear SFA

Backslash operator

Slow Feature Analysis in R

Update a covariance object

Degree 2 Dimension Calculation

Custom Repeater Function

Parametric Bootstrap

A step in the SFA2 algorithm.

gaussClassifier

Classifier for SFA demos

Calculates the first derivative of signal data

Transform a covariance object

Create an Gaussian classifier object

Execute learned function for input data

Fix a covariance object

The SFA2 algorithm, degree 2 expansion.

Return a SFA function as a quadratic form.

Save a GAUSS object.

Custom Size Function

Principal Component Analysis on a covariance object

The SFA1 algorithm, linear SFA.

Load a GAUSS object.

A step in the SFA1 algorithm.

Create structured list for expanded SFA

Perform non-linear regression

Degree 2 Expansion

Preprocessing for sfa classification

sfaClassPredict

Predict Class for SFA classification