The stationary subspace analysis toolbox

Jan Saputra Müller, Paul Von Bünau, Frank C. Meinecke, Franz J. Király, Klaus Robert Müller

Research output: Contribution to journalArticle

13 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)3065-3069
Number of pages5
JournalJournal of Machine Learning Research
Volume12
Publication statusPublished - 2011 Oct
Externally publishedYes

Keywords

  • Blind source separation
  • Dimensionality reduction
  • Non-stationarities
  • Unsupervised learning

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Statistics and Probability
  • Artificial Intelligence

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  • Cite this

    Müller, J. S., Von Bünau, P., Meinecke, F. C., Király, F. J., & Müller, K. R. (2011). The stationary subspace analysis toolbox. Journal of Machine Learning Research, 12, 3065-3069.