Convergence of HLS estimation algorithms for multivariable ARX-like systems

Convergence of HLS estimation algorithms for multivariable ARX-like systems
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DOI：
10.1016/j.amc.2007.01.089
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发表时间：
2007-07
期刊：
Appl. Math. Comput.
影响因子：
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通讯作者：
Lingyun Wang;F. Ding;P. X. Liu
Lingyun Wang;F. Ding;P. X. Liu
中科院分区：
其他
文献类型：
--
作者：
Lingyun Wang;F. Ding;P. X. Liu

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基于分层辨识原理，详细推导了MIMO类ARX系统的分层最小二乘辨识算法。利用随机鞅理论证明了HLS算法对有界噪声方差的参数估计误差一致收敛于零。给出了一个数值例子。
A hierarchical least squares (HLS) algorithm is derived in details for identifying MIMO ARX-like systems based on the hierarchical identification principle. It is shown that the parameter estimation errors by the HLS algorithm consistently converge to zero for bounded noise variances by using the stochastic martingale theory. A numerical example is given.