This paper presents new recursive projection techniques to compute reduced order models of time-varying linear systems. The methods produce a low rank approximation of the Gramians or of the Hankel map of the system and are mainly based on matrix operations that can exploit sparsity of the model. We show the practical relevance of our results with a few benchmark examples
Abstract. We present two efcient algorithms to produce a reduced order model of a time-invariant lin...
We present two efficient algorithms to produce a reduced order model of a time-invariant linear dyna...
We present two efficient algorithms to produce a reduced order model of a time-invariant linear dyna...
Summary. This paper presents new recursive projection techniques to compute reduced order models of ...
This paper presents new recursive projection techniques to compute reduced order models of time-vary...
This paper presents new recursive projection techniques to compute reduced order models of time-vary...
The basic idea of model reduction is to represent a complex linear dynamical system by a much simple...
The basic idea of model reduction is to represent a complex linear dynamical system by a much simple...
In this note we present a new updating technique to estimate a low rank approximation of the Hankel ...
In this note we present a new updating technique to estimate a low rank approximation of the Hankel ...
In this note we present a new updating technique to estimate a low rank approximation of the Hankel ...
In this note we present a new updating technique to estimate a low rank approximation of the Hankel ...
In this paper, we describe some recent developments in the use of projection methods to produce redu...
In this paper we present a Smith-like updating technique to estimate a low rank approximation of the...
In this paper we present a Smith-like updating technique to estimate a low rank approximation of the...
Abstract. We present two efcient algorithms to produce a reduced order model of a time-invariant lin...
We present two efficient algorithms to produce a reduced order model of a time-invariant linear dyna...
We present two efficient algorithms to produce a reduced order model of a time-invariant linear dyna...
Summary. This paper presents new recursive projection techniques to compute reduced order models of ...
This paper presents new recursive projection techniques to compute reduced order models of time-vary...
This paper presents new recursive projection techniques to compute reduced order models of time-vary...
The basic idea of model reduction is to represent a complex linear dynamical system by a much simple...
The basic idea of model reduction is to represent a complex linear dynamical system by a much simple...
In this note we present a new updating technique to estimate a low rank approximation of the Hankel ...
In this note we present a new updating technique to estimate a low rank approximation of the Hankel ...
In this note we present a new updating technique to estimate a low rank approximation of the Hankel ...
In this note we present a new updating technique to estimate a low rank approximation of the Hankel ...
In this paper, we describe some recent developments in the use of projection methods to produce redu...
In this paper we present a Smith-like updating technique to estimate a low rank approximation of the...
In this paper we present a Smith-like updating technique to estimate a low rank approximation of the...
Abstract. We present two efcient algorithms to produce a reduced order model of a time-invariant lin...
We present two efficient algorithms to produce a reduced order model of a time-invariant linear dyna...
We present two efficient algorithms to produce a reduced order model of a time-invariant linear dyna...
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