jmlr jmlr2011 jmlr2011-92 jmlr2011-92-reference knowledge-graph by maker-knowledge-mining
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Author: Jan Saputra Müller, Paul von Bünau, Frank C. Meinecke, Franz J. Király, Klaus-Robert Müller
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. Keywords: non-stationarities, blind source separation, dimensionality reduction, unsupervised learning
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