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Graph structure-preserving model reduction of linear network systems

机译:线性网络系统的图结构保持模型简化

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In this paper, a structure-preserving model reduction procedure is developed for linear network systems. The system is evolving on a graph which is assumed to be connected, weighted and undirected. A projection matrix, called cluster matrix is used to obtain the reduced-order model. In the approach, vertices in the graph having similar frequency responses are aggregated, i.e. the number of vertices is reduced. It is shown that reduced order models are still network systems with connected, weighted and undirected graphs. Moreover, we give an exact error between the original and reduced order models, which is bounded. Finally, an example demonstrates the proposed results.
机译:本文为线性网络系统开发了一种结构保持模型的简化程序。该系统在一个假设为连通,加权和无向的图形上发展。使用称为簇矩阵的投影矩阵来获得降阶模型。在该方法中,将图中具有相似频率响应的顶点聚合在一起,即减少了顶点数量。结果表明,降阶模型仍然是具有连接图,加权图和无向图的网络系统。此外,我们给出了原始模型和降阶模型之间的精确误差,该误差是有界的。最后,通过一个例子证明了所提出的结果。

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