Utilizing multivariate autoregressive model to reveal internal dependences in multichannel measurement data

Risto Suoranta, Seppo Rantala

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

3 Citations (Scopus)

Abstract

A method based on the estimation of the multivariate autoregressive model (MAR-model) is introduced to analyze multichannel data. Because the MAR-model is a black-box model and can describe systems with feedback-loops, it table for the analysis of complex closed-loop multivariate systems. The authors identify the MAR-model and, based on the model, decompose the multichannel spectral matrix. The proposed method offers a new possibility to analyze systems of which there is no exact prior knowledge of internal structures.
Original languageEnglish
Title of host publicationIEEE Instrumentation and Measurement Technology Conference
PublisherIEEE Institute of Electrical and Electronic Engineers
Pages315-318
ISBN (Print)0-87942-579-2
DOIs
Publication statusPublished - 1991
MoE publication typeA4 Article in a conference publication

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  • Cite this

    Suoranta, R., & Rantala, S. (1991). Utilizing multivariate autoregressive model to reveal internal dependences in multichannel measurement data. In IEEE Instrumentation and Measurement Technology Conference (pp. 315-318). IEEE Institute of Electrical and Electronic Engineers. https://doi.org/10.1109/IMTC.1991.161603