In this paper the probabilistic characterization of a nonlinear system enforced by parametric Poissonian white noise in terms of complex fractional moments is presented. In fact the initial system driven by a parametric input could be transformed into a system with an external type of excitation through an invertible nonlinear transformation. It is shown that by using Mellin transform theorem and related concepts, the solution of the Kolmogorov-Feller equation for the system with external input may be obtained in a very easy way
Di Matteo, A., Pirrotta, A. (2014). Probabilistic characterization of nonlinear systems under Poisson white noise parametric input via complex fractional moments. In International Conference on Fractional Differentiation and Its Applications (ICFDA14) [10.1109/ICFDA.2014.6967409].
Probabilistic characterization of nonlinear systems under Poisson white noise parametric input via complex fractional moments
DI MATTEO, Alberto;PIRROTTA, Antonina
2014-01-01
Abstract
In this paper the probabilistic characterization of a nonlinear system enforced by parametric Poissonian white noise in terms of complex fractional moments is presented. In fact the initial system driven by a parametric input could be transformed into a system with an external type of excitation through an invertible nonlinear transformation. It is shown that by using Mellin transform theorem and related concepts, the solution of the Kolmogorov-Feller equation for the system with external input may be obtained in a very easy wayFile | Dimensione | Formato | |
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