Title :
Utilizing multivariate autoregressive model to reveal internal dependencies in multichannel measurement data
Author :
Suoranta, Risto ; Rantala, Seppo
Author_Institution :
Machine Autom. Lab., Tech. Res. Centre of Finland, Tampere, Finland
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
Keywords :
closed loop systems; feedback; measurement theory; multivariable systems; parameter estimation; random noise; spectral analysis; black-box model; complex closed-loop multivariate systems; feedback-loops; multichannel measurement data; multichannel spectral matrix; multivariate autoregressive model; noise source analysis; Covariance matrix; Feedback loop; Gold; Internet; Laboratories; Matrix decomposition; Noise figure; Signal analysis; Stochastic processes; White noise;
Conference_Titel :
Instrumentation and Measurement Technology Conference, 1991. IMTC-91. Conference Record., 8th IEEE
Conference_Location :
Atlanta, GA
Print_ISBN :
0-87942-579-2
DOI :
10.1109/IMTC.1991.161603