将关键变量分离原理和辅助模型思想相结合，得到单新息递推增广最小二乘辨识算法。

By combining the key term separation principle with the auxiliary model idea, we can obtain the single innovation recursive extended least squares identification algorithm.

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与常规递推增广最小二乘算法相比，提出的方法具有更快的收敛速度，能产生更高精度的参数估计。

Compared with the recursive extended least squares algorithms, the proposed two algorithms have fast convergence rates and can produce highly accurate parameter estimation.

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