| dc.contributor.author | Taskinen, Sara | |
| dc.contributor.author | Miettinen, Jari | |
| dc.contributor.author | Nordhausen, Klaus | |
| dc.date.accessioned | 2016-05-18T06:35:53Z | |
| dc.date.available | 2018-04-20T21:45:08Z | |
| dc.date.issued | 2016 | |
| dc.identifier.citation | Taskinen, S., Miettinen, J., & Nordhausen, K. (2016). A more efficient second order blind identification method for separation of uncorrelated stationary time series. <i>Statistics and Probability Letters</i>, <i>116</i>, 21-26. <a href="https://doi.org/10.1016/j.spl.2016.04.007" target="_blank">https://doi.org/10.1016/j.spl.2016.04.007</a> | |
| dc.identifier.other | CONVID_25661845 | |
| dc.identifier.other | TUTKAID_69799 | |
| dc.identifier.uri | https://jyx.jyu.fi/handle/123456789/49829 | |
| dc.description.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. | |
| dc.language.iso | eng | |
| dc.publisher | Elsevier BV | |
| dc.relation.ispartofseries | Statistics and Probability Letters | |
| dc.subject.other | affine equivariance | |
| dc.subject.other | asymptotic normality | |
| dc.subject.other | joint diagonalization | |
| dc.subject.other | linear process | |
| dc.subject.other | minimum distance index | |
| dc.subject.other | SOBI | |
| dc.title | A more efficient second order blind identification method for separation of uncorrelated stationary time series | |
| dc.type | article | |
| dc.identifier.urn | URN:NBN:fi:jyu-201605172593 | |
| dc.contributor.laitos | Matematiikan ja tilastotieteen laitos | fi |
| dc.contributor.laitos | Department of Mathematics and Statistics | en |
| dc.contributor.oppiaine | Tilastotiede | fi |
| dc.contributor.oppiaine | Statistics | en |
| dc.type.uri | http://purl.org/eprint/type/JournalArticle | |
| dc.date.updated | 2016-05-17T15:15:02Z | |
| dc.type.coar | http://purl.org/coar/resource_type/c_2df8fbb1 | |
| dc.description.reviewstatus | peerReviewed | |
| dc.format.pagerange | 21-26 | |
| dc.relation.issn | 0167-7152 | |
| dc.relation.numberinseries | 0 | |
| dc.relation.volume | 116 | |
| dc.type.version | acceptedVersion | |
| dc.rights.copyright | © 2016 Elsevier B.V. This is a final draft version of an article whose final and definitive form has been published by Elsevier. Published in this repository with the kind permission of the publisher. | |
| dc.rights.accesslevel | openAccess | fi |
| dc.relation.doi | 10.1016/j.spl.2016.04.007 | |
| dc.type.okm | A1 | |
