dc.contributor.author | Ramírez García, David | |
dc.contributor.author | Romero, Daniel | |
dc.contributor.author | Vía Rodríguez, Javier | |
dc.contributor.author | López Valcarce, Roberto | |
dc.contributor.author | Santamaría Caballero, Luis Ignacio | |
dc.contributor.other | Universidad de Cantabria | es_ES |
dc.date.accessioned | 2018-12-18T14:47:43Z | |
dc.date.available | 2018-12-18T14:47:43Z | |
dc.date.issued | 2018-12-01 | |
dc.identifier.issn | 1053-587X | |
dc.identifier.issn | 1941-0476 | |
dc.identifier.other | TEC2015-69648-REDC | es_ES |
dc.identifier.other | TEC2016-81900-REDT/AEI | es_ES |
dc.identifier.other | TEC2015-69868-C2-1-R | es_ES |
dc.identifier.other | TEC2016-76409-C2-2-R | es_ES |
dc.identifier.other | TEC2016-75067-C4-4-R | es_ES |
dc.identifier.other | TEC2017-86921-C2-1-R | es_ES |
dc.identifier.other | TEC2017-86921-C2-2-R | es_ES |
dc.identifier.uri | http://hdl.handle.net/10902/15182 | |
dc.description.abstract | This paper studies the existence of optimal invariant detectors for determining whether P multivariate processes have the same power spectral density. This problem finds application in multiple fields, including physical layer security and cognitive radio. For Gaussian observations, we prove that the optimal invariant detector, i.e., the uniformly most powerful invariant test, does not exist. Additionally, we consider the challenging case of close hypotheses, where we study the existence of the locally most powerful invariant test (LMPIT). The LMPIT is obtained in the closed form only for univariate signals. In the multivariate case, it is shown that the LMPIT does not exist. However, the corresponding proof naturally suggests an LMPIT-inspired detector that outperforms previously proposed detectors. | es_ES |
dc.description.sponsorship | This work was partly supported by the Spanish MINECO grants COMONSENS Network (TEC2015-69648-REDC) and KERMES Network (TEC2016-81900-REDT/AEI); by the Spanish MINECO and the European Commission (ERDF) grants ADVENTURE (TEC2015-69868-C2-1- R), WINTER (TEC2016-76409-C2-2-R), CARMEN (TEC2016-75067-C4-4- R) and CAIMAN (TEC2017-86921-C2-1-R and TEC2017-86921-C2-2-R); by the Comunidad de Madrid grant CASI-CAM-CM (S2013/ICE-2845); by the Xunta de Galicia and ERDF grants GRC2013/009, R2014/037 and ED431G/04 (Agrupacion Estratexica Consolidada de Galicia accred- ´ itation 2016-2019); by the SODERCAN and ERDF grant CAIMAN (12.JU01.64661); and by the Research Council of Norway grant FRIPRO TOPPFORSK (250910/F20). This paper was presented in part at the 2018 IEEE International Conference on Acoustics, Speech and Signal Processing. | es_ES |
dc.format.extent | 13 p. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | es_ES |
dc.rights | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | es_ES |
dc.source | IEEE Transactions on Signal Processing, 2018, 66(23), 6268-6280 | es_ES |
dc.subject.other | Generalized likelihood ratio test (GLRT) | es_ES |
dc.subject.other | Locally most powerful invariant test (LMPIT) | es_ES |
dc.subject.other | Power spectral density (PSD) | es_ES |
dc.subject.other | Toeplitz matrix | es_ES |
dc.subject.other | Uniformly most powerful invariant test (UMPIT) | es_ES |
dc.title | Testing equality of multiple power spectral density matrices | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.relation.publisherVersion | https://doi.org/10.1109/TSP.2018.2875884 | es_ES |
dc.rights.accessRights | openAccess | es_ES |
dc.identifier.DOI | 10.1109/TSP.2018.2875884 | |
dc.type.version | acceptedVersion | es_ES |