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Recursive Identification of Errors-in-Variables Systems Based on the Correlation Analysis
Circuits, Systems, and Signal Processing ( IF 2.3 ) Pub Date : 2020-05-23 , DOI: 10.1007/s00034-020-01441-7
Shujun Fan , Feng Ding , Tasawar Hayat

This paper considers a single-input single-output linear dynamic system, whose input and output are corrupted by Gaussian white measurement noises with zero means and unknown variances; the parameter estimation of such a system is a typical errors-in-variables (EIV) system identification problem. This paper proposes the correlation function-based two-step identification methods for the EIV systems. In order to obtain the unbiased parameter estimates of the EIV system, we derive the correlation function equation by using the correlation analysis method and adopt the least squares method and the instrumental variable method to recursively compute the parameter estimates of the model, resulting in the unbiased parameter estimates of the EIV systems. Finally, a numerical simulation example is given to demonstrate the effectiveness of the proposed algorithms.

中文翻译:

基于相关分析的变量误差系统递归辨识

本文考虑了一个单输入单输出线性动态系统,其输入和输出被均值为零且方差未知的高斯白测量噪声破坏;这种系统的参数估计是一个典型的变量误差 (EIV) 系统识别问题。本文提出了基于相关函数的 EIV 系统的两步识别方法。为了得到 EIV 系统的无偏参数估计,我们采用相关分析方法推导出相关函数方程,并采用最小二乘法和工具变量法递归计算模型的参数估计,得到无偏EIV 系统的参数估计。最后,
更新日期:2020-05-23
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