A systematic path to non-Markovian dynamics II: Probabilistic response of nonlinear multidimensional systems to Gaussian colored noise excitation
Gerassimos A. Athanassoulis, Nikolaos P. Nikoletatos-Kekatos,, Konstantinos Mamis

TL;DR
This paper develops a new probabilistic response equation for nonlinear systems under colored Gaussian noise, improving accuracy over existing models especially with longer correlation times.
Contribution
It introduces an exact non-closed response pdf-evolution equation derived from the SLE and Novikov-Furutsu theorem, with an approximation scheme for practical computation.
Findings
The new equation accurately predicts response pdfs for a bistable Duffing oscillator.
It outperforms the small correlation time approximation as excitation correlation time increases.
Numerical results show good agreement with Monte Carlo simulations.
Abstract
The probabilistic characterization of non-Markovian responses to nonlinear dynamical systems under colored excitation is an important issue, arising in many applications. Extending the Fokker-Planck-Kolmogorov equation, governing the first-order response probability density function (pdf), to this case is a complicated task calling for special treatment. In this work, a new pdf-evolution equation is derived for the response of nonlinear dynamical systems under additive colored Gaussian noise. The derivation is based on the Stochastic Liouville equation (SLE), transformed, by means of an extended version of the Novikov-Furutsu theorem, to an exact yet non-closed equation, involving averages over the history of the functional derivatives of the non-Markovian response with respect to the excitation. The latter are calculated exactly by means of the state-transition matrix of variational,…
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Taxonomy
TopicsNeural Networks and Applications
