In:
Stochastics and Dynamics, World Scientific Pub Co Pte Ltd, Vol. 18, No. 04 ( 2018-08), p. 1850033-
Abstract:
To solve a stochastic linear evolution equation numerically, finite dimensional approximations are commonly used. For a good approximation, one might end up with a sequence of ordinary stochastic linear equations of high order. To reduce the high dimension for practical computations, we consider the singular perturbation approximation as a model order reduction technique in this paper. This approach is well-known from deterministic control theory and here we generalize it for controlled linear systems with Lévy noise. Additionally, we discuss properties of the reduced order model, provide an error bound, and give some examples to demonstrate the quality of this model order reduction technique.
Type of Medium:
Online Resource
ISSN:
0219-4937
,
1793-6799
DOI:
10.1142/S0219493718500338
Language:
English
Publisher:
World Scientific Pub Co Pte Ltd
Publication Date:
2018
SSG:
11
