Operator theory-based discrete fractional Fourier transform
buir.contributor.author | Koç, Aykut | |
dc.citation.epage | 1468 | en_US |
dc.citation.issueNumber | 7 | en_US |
dc.citation.spage | 1461 | en_US |
dc.citation.volumeNumber | 13 | en_US |
dc.contributor.author | Koç, Aykut | en_US |
dc.date.accessioned | 2020-01-31T12:46:06Z | |
dc.date.available | 2020-01-31T12:46:06Z | |
dc.date.issued | 2019 | |
dc.department | National Magnetic Resonance Research Center (UMRAM) | en_US |
dc.description.abstract | The fractional Fourier transform is of importance in several areas of signal processing with many applications including optical signal processing. Deploying it in practical applications requires discrete implementations, and therefore defining a discrete fractional Fourier transform (DFRT) is of considerable interest. We propose an operator theory-based approach to defining the DFRT. By deploying hyperdifferential operators, a DFRT matrix can be defined compatible with the theory of the discrete Fourier transform. The proposed DFRT only uses the ordinary Fourier transform and the coordinate multiplication and differentiation operations. We also propose and compare several alternative discrete definitions of coordinate multiplication and differentiation operations, each of which leads to an alternative DFRT definition. Unitarity and approximation to the continuous transform properties are also investigated in detail. The proposed DFRT is highly accurate in approximating the continuous transform. | en_US |
dc.description.provenance | Submitted by Zeynep Aykut (zeynepay@bilkent.edu.tr) on 2020-01-31T12:46:06Z No. of bitstreams: 2 Operator_theory-based_discrete_fractional_Fourier_transform.pdf: 363312 bytes, checksum: e05fb3f8d13f05c1eb852c42d8f48f22 (MD5) Operator_theory-based_discrete_fractional_Fourier_transform.pdf: 363312 bytes, checksum: e05fb3f8d13f05c1eb852c42d8f48f22 (MD5) | en |
dc.description.provenance | Made available in DSpace on 2020-01-31T12:46:06Z (GMT). No. of bitstreams: 2 Operator_theory-based_discrete_fractional_Fourier_transform.pdf: 363312 bytes, checksum: e05fb3f8d13f05c1eb852c42d8f48f22 (MD5) Operator_theory-based_discrete_fractional_Fourier_transform.pdf: 363312 bytes, checksum: e05fb3f8d13f05c1eb852c42d8f48f22 (MD5) Previous issue date: 2019 | en |
dc.identifier.doi | 10.1007/s11760-019-01553-x | en_US |
dc.identifier.issn | 1863-1703 | |
dc.identifier.uri | http://hdl.handle.net/11693/52953 | |
dc.language.iso | English | en_US |
dc.publisher | Springer | en_US |
dc.relation.isversionof | https://dx.doi.org/10.1007/s11760-019-01553-x | en_US |
dc.source.title | Signal, Image and Video Processing | en_US |
dc.subject | Fractional Fourier transform (FRT) | en_US |
dc.subject | Operator theory | en_US |
dc.subject | Discrete transforms | en_US |
dc.subject | Hyperdifferential operators | en_US |
dc.title | Operator theory-based discrete fractional Fourier transform | en_US |
dc.type | Article | en_US |
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