Authors
Sara Taskinen, Jari Miettinen, Klaus Nordhausen
Publication date
2016
Journal
Statistics and Probability Letters
Volume
116
Pages
21-26
Description
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.
Scholar articles
S Taskinen, J Miettinen, K Nordhausen - Statistics & Probability Letters, 2016