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Common dynamic estimation via structured low-rank approximation with multiple rank constraints

机译:通过具有多个秩约束的结构化低秩近似的常见动态估计

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We consider the problem of detecting the common dynamic among several observed signals. It has been shown in (Markovsky et al., 2019) that the problem is equivalent to a generalization of the classical Hankel low-rank approximation to the case of multiple rank constraints. We propose an optimization method based on the integration of ordinary differential equations describing a descent dynamic for a suitable functional to be minimized. We show how the proposed algorithm improves the numerical solutions computed by existing subspace methods which solve the same problem.
机译:我们考虑在几个观察信号中检测到常见动态的问题。 它已经显示在(Markovsky等,2019)中,问题相当于经典Hankel低秩近似的概括到多个秩约束的情况。 我们提出了一种基于普通微分方程的集成,所述常微分方程的集成,所述常用方程用于最小化的合适功能的下降动态。 我们展示了所提出的算法如何改善现有子空间方法计算的数值解决方案,该方法解决了同样的问题。

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