Optimal fractional fourier filtering for graph signals
buir.contributor.author | Öztürk, Cüneyd | |
buir.contributor.author | Özaktaş, Haldun M. | |
buir.contributor.author | Gezici, Sinan | |
buir.contributor.author | Koç, Aykut | |
buir.contributor.orcid | Öztürk, Cüneyd|0000-0003-3792-9844 | |
buir.contributor.orcid | Gezici, Sinan|0000-0002-6369-3081 | |
buir.contributor.orcid | Koç, Aykut|0000-0002-6348-2663 | |
dc.citation.epage | 2912 | en_US |
dc.citation.spage | 2902 | en_US |
dc.citation.volumeNumber | 69 | en_US |
dc.contributor.author | Öztürk, Cüneyd | |
dc.contributor.author | Özaktaş, Haldun M. | |
dc.contributor.author | Gezici, Sinan | |
dc.contributor.author | Koç, Aykut | |
dc.date.accessioned | 2022-02-01T06:37:35Z | |
dc.date.available | 2022-02-01T06:37:35Z | |
dc.date.issued | 2021-05-19 | |
dc.department | Department of Electrical and Electronics Engineering | en_US |
dc.description.abstract | Graph signal processing has recently received considerable attention. Several concepts, tools, and applications in signal processing such as filtering, transforming, and sampling have been extended to graph signal processing. One such extension is the optimal filtering problem. The minimum mean-squared error estimate of an original graph signal can be obtained from its distorted and noisy version. However, the best separation of signal and noise, and thus the least error, is not always achieved in the ordinary Fourier domain, but rather a fractional Fourier domain. In this work, the optimal filtering problem for graph signals is extended to fractional Fourier domains, and theoretical analysis and solution of the proposed problem are provided along with computational cost considerations. Numerical results are presented to illustrate the benefits of filtering in fractional Fourier domains. | en_US |
dc.description.provenance | Submitted by Evrim Ergin (eergin@bilkent.edu.tr) on 2022-02-01T06:37:34Z No. of bitstreams: 1 Optimal_fractional_fourier_filtering_for_graph_signals.pdf: 773055 bytes, checksum: 0b8947d68601152a6cc91450bfd944aa (MD5) | en |
dc.description.provenance | Made available in DSpace on 2022-02-01T06:37:35Z (GMT). No. of bitstreams: 1 Optimal_fractional_fourier_filtering_for_graph_signals.pdf: 773055 bytes, checksum: 0b8947d68601152a6cc91450bfd944aa (MD5) Previous issue date: 2021-05-19 | en |
dc.identifier.doi | 10.1109/TSP.2021.3079804 | en_US |
dc.identifier.eissn | 1941-0476 | |
dc.identifier.issn | 1053-587X | |
dc.identifier.uri | http://hdl.handle.net/11693/76931 | |
dc.language.iso | English | en_US |
dc.publisher | IEEE | en_US |
dc.relation.isversionof | https://doi.org/10.1109/TSP.2021.3079804 | en_US |
dc.source.title | IEEE Transactions on Signal Processing | en_US |
dc.subject | Fractional Fourier transform | en_US |
dc.subject | Graph signal processing (GSP) | en_US |
dc.subject | Optimal filtering | en_US |
dc.subject | Wiener filter | en_US |
dc.subject | Graph Fourier transform (GFT) | en_US |
dc.subject | Signal processing on graphs | en_US |
dc.subject | Graphs | en_US |
dc.title | Optimal fractional fourier filtering for graph signals | en_US |
dc.type | Article | en_US |
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