PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

The Stationary Subspace Analysis toolbox
Jan Saputra Müller, Paul Buenau, Frank Meinecke, Franz Király and Klaus-Robert Müller
Journal of Machine Learning Research Volume 12, pp. 3065-3069, 2011.

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.

PDF - Requires Adobe Acrobat Reader or other PDF viewer.
PDF (Manual of the toolbox.) - Requires Adobe Acrobat Reader or other PDF viewer.
EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:9504
Deposited By:Jan Saputra Müller
Deposited On:16 March 2012