This paper deals with the identification problem of discrete-time linear time-invariant errors-in-variables systems for the case of the colored output noise. Based on the correlation analysis, the multi-innovation theory is introduced to the errors-in-variables systems where both input and output data are noisy. A correlation analysis-based multi-innovation stochastic gradient algorithm and a correlation analysis-based multi-innovation least squares algorithm are proposed by means of the multi-innovation theory in order to improve the parameter accuracy. The simulation results confirm that these two algorithms are effective.

中文翻译：

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基于相关分析的变量误差系统的随机梯度和最小二乘识别方法使用多重创新

本文讨论了有色输出噪声情况下离散时间线性时不变变量误差系统的辨识问题。在相关分析的基础上，将多元创新理论引入到输入和输出数据都有噪声的变量误差系统中。为提高参数精度，利用多创新理论提出了基于相关分析的多创新随机梯度算法和基于相关分析的多创新最小二乘算法。仿真结果证实了这两种算法是有效的。