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On the low-dimensional modelling of Stratonovich stochastic differential equations

Author

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  • Xu, Chao
  • Roberts, A.J.

Abstract

We develop further ideas on how to construct low-dimensional models of stochastic dynamical systems. The aim is to derive a consistent and accurate model from the originally high-dimensional system. This is done with the support of centre manifold theory and techniques. Aspects of several previous approaches are combined and extended: adiabatic elimination has previously been used, but centre manifold techniques simplify the noise by removing memory effects, and with less algebraic effort than normal forms; analysis of associated Fokker-Plank equations replace nonlinearly generated noise processes by their long-term equivalent white noise. The ideas are developed by examining a simple dynamical system which serves as a prototype of more interesting physical situations.

Suggested Citation

  • Xu, Chao & Roberts, A.J., 1996. "On the low-dimensional modelling of Stratonovich stochastic differential equations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 225(1), pages 62-80.
  • Handle: RePEc:eee:phsmap:v:225:y:1996:i:1:p:62-80
    DOI: 10.1016/0378-4371(95)00387-8
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    Cited by:

    1. Bunder, J.E. & Roberts, A.J., 2017. "Resolution of subgrid microscale interactions enhances the discretisation of nonautonomous partial differential equations," Applied Mathematics and Computation, Elsevier, vol. 304(C), pages 164-179.
    2. Roberts, A.J., 2008. "Normal form transforms separate slow and fast modes in stochastic dynamical systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(1), pages 12-38.

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