Power adaptation for vector parameter estimation according to Fisher information based optimality criteria
buir.contributor.author | Gezici, Sinan | |
dc.citation.epage | 11 | en_US |
dc.citation.spage | 1 | en_US |
dc.citation.volumeNumber | 192 | en_US |
dc.contributor.author | Gürgünoğlu, Doğa | |
dc.contributor.author | Dülek, Berkan | |
dc.contributor.author | Gezici, Sinan | |
dc.coverage.spatial | Netherlands | en_US |
dc.date.accessioned | 2023-02-22T05:51:24Z | |
dc.date.available | 2023-02-22T05:51:24Z | |
dc.date.issued | 2022-03 | |
dc.department | Department of Electrical and Electronics Engineering | en_US |
dc.description.abstract | The optimal power adaptation problem is investigated for vector parameter estimation according to various Fisher information based optimality criteria. By considering an observation model that involves a linear transformation of the parameter vector and an additive noise component with an arbitrary probability distribution, six different optimal power allocation problems are formulated based on Fisher information based objective functions. Via optimization theoretic approaches, various closed-form solutions are derived for the proposed problems. Also, the results are extended to cases in which nuisance parameters exist in the system model or certain types of nonlinear transformations are applied on the parameter vector. Numerical examples are presented to investigate performance of the proposed power allocation strategies. | en_US |
dc.description.provenance | Submitted by Betül Özen (ozen@bilkent.edu.tr) on 2023-02-22T05:51:24Z No. of bitstreams: 1 Power_adaptation_for_vector_parameter_estimation_according_to_Fisher_information_based_optimality_criteria.pdf: 967672 bytes, checksum: c3df11afbf542bd1cdb54eaaf9f6a353 (MD5) | en |
dc.description.provenance | Made available in DSpace on 2023-02-22T05:51:24Z (GMT). No. of bitstreams: 1 Power_adaptation_for_vector_parameter_estimation_according_to_Fisher_information_based_optimality_criteria.pdf: 967672 bytes, checksum: c3df11afbf542bd1cdb54eaaf9f6a353 (MD5) Previous issue date: 2022-03 | en |
dc.identifier.doi | 10.1016/j.sigpro.2021.108390 | en_US |
dc.identifier.issn | 0165-1684 | |
dc.identifier.uri | http://hdl.handle.net/11693/111595 | |
dc.language.iso | English | en_US |
dc.publisher | Elsevier BV | en_US |
dc.relation.isversionof | https://doi.org/10.1016/j.sigpro.2021.108390 | en_US |
dc.source.title | Signal Processing | en_US |
dc.subject | Cramér-Rao lower bound | en_US |
dc.subject | Estimation | en_US |
dc.subject | Fisher information | en_US |
dc.subject | Power adaptation | en_US |
dc.title | Power adaptation for vector parameter estimation according to Fisher information based optimality criteria | en_US |
dc.type | Article | en_US |
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