A more efficient second order blind identification method for separation of uncorrelated stationary time series
Finna-arvio
A more efficient second order blind identification method for separation of uncorrelated stationary time series
1s2.0s0167715216300256main.pdf
(Jyväskylän yliopisto - JYX)
The classical second order source separation methods use approximate joint diagonalization of autocovariance matrices with several lags to estimate the unmixing matrix. Based on recent asymptotic results, we propose a novel unmixing matrix estimator which selects the best lag set from a finite set of candidate sets specified by the user. The theory is illustrated by a simulation study.
Tallennettuna:
Kieli |
englanti |
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Sarja | Statistics and Probability Letters |
Aiheet | |
ISSN |
0167-7152 |