A1 Journal article – refereed
Separation of Uncorrelated Stationary time series using Autocovariance Matrices




List of Authors: Jari Miettinen, Katrin Illner, Klaus Nordhausen, Hannu Oja, Sara Taskinen, Fabian J. Theis
Publisher: WILEY-BLACKWELL
Publication year: 2016
Journal: Journal of Time Series Analysis
Journal name in source: JOURNAL OF TIME SERIES ANALYSIS
Journal acronym: J TIME SER ANAL
Volume number: 37
Issue number: 3
Number of pages: 18
ISSN: 0143-9782

Abstract


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.


Last updated on 2019-21-08 at 20:20