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Separation of Uncorrelated Stationary time series using Autocovariance Matrices




TekijätJari Miettinen, Katrin Illner, Klaus Nordhausen, Hannu Oja, Sara Taskinen, Fabian J. Theis

KustantajaWILEY-BLACKWELL

Julkaisuvuosi2016

JournalJournal of Time Series Analysis

Tietokannassa oleva lehden nimiJOURNAL OF TIME SERIES ANALYSIS

Lehden akronyymiJ TIME SER ANAL

Vuosikerta37

Numero3

Aloitussivu337

Lopetussivu354

Sivujen määrä18

ISSN0143-9782

DOIhttps://doi.org/10.1111/jtsa.12159


Tiivistelmä

In blind source separation, one assumes that the observed p time series are linear combinations of p latent uncorrelated weakly stationary time series. To estimate the unmixing matrix, which transforms the observed time series back to uncorrelated latent time series, second-order blind identification (SOBI) uses joint diagonalization of the covariance matrix and autocovariance matrices with several lags. In this article, we find the limiting distribution of the well-known symmetric SOBI estimator under general conditions and compare its asymptotical efficiencies to those of the recently introduced deflation-based SOBI estimator. The theory is illustrated by some finite-sample simulation studies.



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