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2011 JMLR JMLR 2011

The Stationary Subspace Analysis Toolbox

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. [abs] [ pdf ][ bib ] [ code ] © JMLR 2011. (edit, beta)

🌉 Interdisciplinary Bridge — Data Science & Analytics and Machine Learning
🧭 Keyword Pioneer — stationary subspace analysis
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Speech & Audio
🐣 Hot Topic Early Bird — time series analysis

Authors

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

Topics

Machine Learning > Core Methods > Representation Learning Machine Learning > Learning Types > Unsupervised Learning Data Science & Analytics > Methods > Time Series Analysis Machine Learning > Core Methods > Dimensionality Reduction

Keywords

time series analysis dimensionality reduction feature extraction matrix factorization signal processing time series stationary subspace analysis linear factorization
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