Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/1048
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dc.contributor.authorMohanty, K B-
dc.date.accessioned2009-09-21T04:20:32Z-
dc.date.available2009-09-21T04:20:32Z-
dc.date.issued2009-
dc.identifier.citationUKSim 2009: 11th International Conference on Computer Modelling and Simulation, 2009, Article number 4809765, Pages 212-216en
dc.identifier.urihttp://dx.doi.org/10.1109/UKSIM.2009.22-
dc.identifier.urihttp://hdl.handle.net/2080/1048-
dc.description.abstractA probability distribution model is proposed in this paper. Fourier Transform of a unit rectangular pulse, whose width is a random variable with Gaussian distribution, is used to derive the probability density function (p.d.f.) in the frequency domain. Result of the mathematical derivation is an exponential mathematical function involving an infinite summation over all integers. The projection theorem is used to arrive at the exact probability density function. To verify this experimentally, a randomly generated sample of Gaussian numbers, representing the pulse width is mapped onto the frequency domain, and the resulting points have a certain probability distribution, which matches with the theoretically proposed function.en
dc.format.extent269467 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoen-
dc.publisherIEEE Computer Societyen
dc.subjectFourier transformen
dc.subjectGaussian distributionen
dc.subjectProbability density functionsen
dc.subjectSinc functionen
dc.titleFrequency Domain Modeling for Classification of Signalsen
dc.typeArticleen
Appears in Collections:Conference Papers

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