Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Effective error estimation for model reduction with inhomogeneous
  initial conditions   A priori error bounds have been derived for different balancing-related model
reduction methods. The most classical result is a bound for balanced truncation
and singular perturbation approximation that is applicable for asymptotically
stable linear time-invariant systems with homogeneous initial conditions.
Recently, there have been a few attempts to generalize the balancing-related
reduction methods to the case with inhomogeneous initial conditions, but the
existing error bounds for these generalizations are quite restrictive.
Particularly, it is required to restrict the initial conditions to a
low-dimensional subspace, which has to be chosen before the reduced model is
constructed. In this paper, we propose an estimator that circumvents this hard
constraint completely. Our estimator is applicable to a large class of
reduction methods, whereas the former results were only derived for certain
specific methods. Moreover, our approach yields to significantly more effective
error estimation, as also will be demonstrated numerically.

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The categories of this paper are: atom-ph
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The categories of this paper are: adap-org
25
The categories of this paper are: patt-sol
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The categories of this paper are: chao-dyn
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The categories of this paper are: quant-ph
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The categories of this paper are: eess
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The categories of this paper are: bayes-an
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The categories of this paper are: plasm-ph
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The categories of this paper are: acc-phys
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The categories of this paper are: ao-sci
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The categories of this paper are: dg-ga
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The categories of this paper are: nucl-th
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The categories of this paper are: q-bio
5
The categories of this paper are: gr-qc
4
The categories of this paper are: cond-mat
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The categories of this paper are: stat