TY  - JOUR
AB  - 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.
AU  - Miettinen, J.*
AU  - Illner, K.
AU  - Nordhausen, K.*
AU  - Oja, H.*
AU  - Taskinen, S.*
AU  - Theis, F.J.
C1  - 46806
C2  - 37844
CY  - Hoboken
SP  - 337-354
TI  - Separation of uncorrelated stationary time series using autocovariance matrices.
JO  - J. Time Ser. Anal.
VL  - 37
IS  - 3
PB  - Wiley-blackwell
PY  - 2016
SN  - 0143-9782
ER  -