6533b7d0fe1ef96bd125ad7e

RESEARCH PRODUCT

Probabilistic characterization of nonlinear systems under Poisson white noise parametric input via complex fractional moments

Alberto Di MatteoAntonina Pirrotta

subject

Mellin transformPoisson white noiseDifferential equationMathematical analysisLinear systemProbabilistic logicWhite noiseComplex fractional momentlaw.inventionNonlinear systemInvertible matrixlawparametric systemsParametric statisticsMathematics

description

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.

yearjournalcountryeditionlanguage
2014-06-01ICFDA'14 International Conference on Fractional Differentiation and Its Applications 2014
https://doi.org/10.1109/icfda.2014.6967409