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Nonparametric Preprocessing in System Identification: a Powerful Tool

机译:系统识别中的非参数预处理:功能强大的工具

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摘要

In this paper, we study the properties of existing non-parametric methods for estimating the plant and noise transfer functions of a linear dynamic system. The analysis is based on the recent insight that leakage errors in the frequency domain have a smooth nature that is completely similar to the initial transients in the time domain. This not only allows us to understand better the existing classic methods, but also opens the road to new better performing algorithms. The paper includes the output error setup, the errors-in-variables setup, and measurements under feedback conditions. Eventually, some of the methods are illustrated in the analysis of a vibrating metal beam.
机译:在本文中,我们研究了用于估计线性动态系统的植物和噪声传递函数的现有非参数方法的性质。该分析基于最近的见解,即频域中的泄漏误差具有平滑特性,该特性与时域中的初始瞬态完全相似。这不仅使我们能够更好地理解现有的经典方法,而且为新的性能更好的算法开辟了道路。本文包括输出误差设置,变量误差设置以及反馈条件下的测量。最终,在振动金属梁的分析中说明了一些方法。

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