Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/1048
Title: Frequency Domain Modeling for Classification of Signals
Authors: Mohanty, K B
Keywords: Fourier transform
Gaussian distribution
Probability density functions
Sinc function
Issue Date: 2009
Publisher: IEEE Computer Society
Citation: UKSim 2009: 11th International Conference on Computer Modelling and Simulation, 2009, Article number 4809765, Pages 212-216
Abstract: A 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.
URI: http://dx.doi.org/10.1109/UKSIM.2009.22
http://hdl.handle.net/2080/1048
Appears in Collections:Conference Papers

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