• Medientyp: E-Artikel
  • Titel: Approximating the Density of Random Differential Equations with Weak Nonlinearities via Perturbation Techniques
  • Beteiligte: Cortés, Juan-Carlos; López-Navarro, Elena; Romero, José-Vicente; Roselló, María-Dolores
  • Erschienen: MDPI AG, 2021
  • Erschienen in: Mathematics, 9 (2021) 3, Seite 204
  • Sprache: Englisch
  • DOI: 10.3390/math9030204
  • ISSN: 2227-7390
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  • Beschreibung: We combine the stochastic perturbation method with the maximum entropy principle to construct approximations of the first probability density function of the steady-state solution of a class of nonlinear oscillators subject to small perturbations in the nonlinear term and driven by a stochastic excitation. The nonlinearity depends both upon position and velocity, and the excitation is given by a stationary Gaussian stochastic process with certain additional properties. Furthermore, we approximate higher-order moments, the variance, and the correlation functions of the solution. The theoretical findings are illustrated via some numerical experiments that confirm that our approximations are reliable.
  • Zugangsstatus: Freier Zugang