A2 Review article, Literature review, Systematic review
A review of second‐order blind identification methods (2022)


Pan, Y., Matilainen, M., Taskinen, S., & Nordhausen, K. (2022). A review of second‐order blind identification methods. WIREs Computational Statistics, 14(4), Article e1550. https://doi.org/10.1002/wics.1550


JYU authors or editors


Publication details

All authors or editorsPan, Yan; Matilainen, Markus; Taskinen, Sara; Nordhausen, Klaus

Journal or seriesWIREs Computational Statistics

ISSN1939-5108

eISSN1939-0068

Publication year2022

Publication date07/02/2021

Volume14

Issue number4

Article numbere1550

PublisherJohn Wiley & Sons

Publication countryUnited States

Publication languageEnglish

DOIhttps://doi.org/10.1002/wics.1550

Publication open accessOpenly available

Publication channel open accessPartially open access channel

Publication is parallel published (JYX)https://jyx.jyu.fi/handle/123456789/78633


Abstract

Second order source separation (SOS) is a data analysis tool which can be used for revealing hidden structures in multivariate time series data or as a tool for dimension reduction. Such methods are nowadays increasingly important as more and more high-dimensional multivariate time series data are measured in numerous fields of applied science. Dimension reduction is crucial, as modelling such high-dimensional data with multivariate time series models is often impractical as the number of parameters describing dependencies between the component time series is usually too high. SOS methods have their roots in the signal processing literature, where they were first used to separate source signals from an observed signal mixture. The SOS model assumes that the observed time series (signals) is a linear mixture of latent time series (sources) with uncorrelated components. The methods make use of the second order statistics - hence the name “second order source separation”. In this review we discuss the classical SOS methods and their extensions to more complex settings. An example illustrates how SOS can be performed.


Keywordsstatistical methodsmultivariable methodstime seriestime-series analysissignal processingcomputational science


Contributing organizations


Ministry reportingYes

Reporting Year2022

JUFO rating1


Last updated on 2024-10-03 at 20:06