The Stationary Subspace Analysis Toolbox

Authors:
Jan Saputra Müller;Paul von Bünau;Frank C. Meinecke;Franz J. Király;Klaus-Robert Müller
Affiliations:
-;-;-;-;-
Venue:
The Journal of Machine Learning Research
Year:
2011

Citing 2
Cited 2

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ICONIP'10 Proceedings of the 17th international conference on Neural information processing: theory and algorithms - Volume Part I
An information geometrical view of stationary subspace analysis

ICANN'11 Proceedings of the 21st international conference on Artificial neural networks - Volume Part II

Algebraic geometric comparison of probability distributions

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Separation of stationary and non-stationary sources with a generalized eigenvalue problem

Neural Networks

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Abstract

The Stationary Subspace Analysis (SSA) algorithm linearly factorizes a high-dimensional time series into stationary and non-stationary components. The SSA Toolbox is a platform-independent efficient stand-alone implementation of the SSA algorithm with a graphical user interface written in Java, that can also be invoked from the command line and from Matlab. The graphical interface guides the user through the whole process; data can be imported and exported from comma separated values (CSV) and Matlab's .mat files.