| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1154277 | Statistics & Probability Letters | 2016 | 6 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Sara Taskinen, Jari Miettinen, Klaus Nordhausen,