14 citations · 21 across the 21 of their papers we have counts for
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(Empirical) Gramian-based dimension reduction for stochastic differential equations driven by fractional Brownian motion
Nahid Jamshidi, Martin Redmann
In this paper, we investigate large-scale linear systems driven by a fractional Brownian motion (fBm) with Hurst parameter . We interpret these equations either in t…
Exact dimension reduction for rough differential equations
Martin Redmann, Sebastian Riedel
In this paper, practically computable low-order approximations of potentially high-dimensional differential equations driven by geometric rough paths are proposed and investigated.…
Complexity reduction of large-scale stochastic systems using linear quadratic Gaussian balancing
Tobias Damm, Martin Redmann
In this paper, we consider a model reduction technique for stabilizable and detectable stochastic systems. It is based on a pair of Gramians that we analyze in terms of well-posedn…
Model reduction for stochastic systems with nonlinear drift
Martin Redmann
In this paper, we study dimension reduction techniques for large-scale controlled stochastic differential equations (SDEs). The drift of the considered SDEs contains a polynomial t…