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dc.contributor.authorZubair, Muhammad
dc.contributor.authorAhmed, Sajid
dc.contributor.authorJardak, Seifallah
dc.contributor.authorAlouini, Mohamed-Slim
dc.date.accessioned2019-05-21T13:03:41Z
dc.date.available2019-05-21T13:03:41Z
dc.date.issued2019-03-18
dc.identifier.citationZubair M, Ahmed S, Jardak S, Alouini M-S (2018) OPTIMAL EIGENVALUE DECOMPOSITION BASED FREQUENCY ESTIMATION ALGORITHM FOR COMPLEX SINUSOIDAL SIGNALS. 2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP). Available: http://dx.doi.org/10.1109/GlobalSIP.2018.8646586.
dc.identifier.doi10.1109/GlobalSIP.2018.8646586
dc.identifier.urihttp://hdl.handle.net/10754/652992
dc.description.abstractThe estimation performance of subspace based algorithms depends on the selection of dominant eigenvalues, which is challenging. In this paper, by exploiting the circular transformation, an optimal dominant eigenvalue selection subspace based frequency estimation algorithm is proposed. The proposed algorithm restricts the contribution of signal into fixed number of dominant eigenvalues. The performance of the proposed algorithm is compared with Multiple Signal Classification (MUSIC) and Karhunen-Loeve-transform (KLT) algorithms. The analytical and simulation results show that proposed algorithm outperforms the MUSIC and KLT algorithms.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.urlhttps://ieeexplore.ieee.org/document/8646586
dc.subjectDenoising
dc.subjectFrequency Estimation
dc.subjectKLT.
dc.subjectMUSIC
dc.titleOPTIMAL EIGENVALUE DECOMPOSITION BASED FREQUENCY ESTIMATION ALGORITHM FOR COMPLEX SINUSOIDAL SIGNALS
dc.typeConference Paper
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentElectrical Engineering Program
dc.identifier.journal2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)
dc.conference.date2018-11-26 to 2018-11-29
dc.conference.name2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018
dc.conference.locationAnaheim, CA, USA
dc.contributor.institutionElectrical Engineering Department, Information Technology University (ITU), Lahore, , Pakistan
kaust.personJardak, Seifallah
kaust.personAlouini, Mohamed-Slim
dc.date.published-online2019-03-18
dc.date.published-print2018-11


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