Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/11557
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dc.contributor.authorChaudhary, Pradeep Kumaren_US
dc.contributor.authorPachori, Ram Bilasen_US
dc.date.accessioned2023-04-11T11:16:56Z-
dc.date.available2023-04-11T11:16:56Z-
dc.date.issued2023-
dc.identifier.citationChaudhary, P. K., Gupta, V., & Pachori, R. B. (2023). Fourier-bessel representation for signal processing: A review. Digital Signal Processing: A Review Journal, 135 doi:10.1016/j.dsp.2023.103938en_US
dc.identifier.issn1051-2004-
dc.identifier.otherEID(2-s2.0-85148327898)-
dc.identifier.urihttps://doi.org/10.1016/j.dsp.2023.103938-
dc.identifier.urihttps://dspace.iiti.ac.in/handle/123456789/11557-
dc.description.abstractSeveral applications, analysis and visualization of signal demand representation of time-domain signal in different domains like frequency-domain representation based on Fourier transform (FT). Representing a signal in frequency-domain, where parameters of interest are more compact than in original form (time-domain). It is considered that the basis functions which are used to represent the signal should be highly correlated with the signal which is under analysis. Bessel functions are one of the set of basis functions which have been used in literature for representing non-stationary signals due to their damping (non-stationary) nature, and the representation methods based on these basis functions are named as Fourier-Bessel series expansion (FBSE) and Fourier-Bessel transform (FBT). The main purpose of this paper is to present a review related to theory and applications of FBSE and FBT methods. Roots calculation of Bessel functions, the relation between root order of Bessel function and frequency, advantages of Fourier-Bessel representation over FT have also been included in the paper. In order to make the implementation of FBSE based decomposition methods easy, the pseudo-code of decomposition methods are included. The paper also describes various applications of FBSE and FBT based methods present in the literature. Finally, the future scope of the Fourier-Bessel representation is discussed. © 2023 Elsevier Inc.en_US
dc.language.isoenen_US
dc.publisherElsevier Inc.en_US
dc.sourceDigital Signal Processing: A Review Journalen_US
dc.subjectFourier seriesen_US
dc.subjectFrequency domain analysisen_US
dc.subjectSignal processingen_US
dc.subjectTime domain analysisen_US
dc.subjectBase functionen_US
dc.subjectBessel's functionen_US
dc.subjectDecomposition methodsen_US
dc.subjectFourieren_US
dc.subjectFourier-Bessel series expansionen_US
dc.subjectFourier-Bessel transformsen_US
dc.subjectImage decompositionen_US
dc.subjectSignal decompositionen_US
dc.subjectSignal decomposition methoden_US
dc.subjectSignal-processingen_US
dc.subjectBessel functionsen_US
dc.titleFourier-Bessel representation for signal processing: A reviewen_US
dc.typeReviewen_US
Appears in Collections:Department of Electrical Engineering

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