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WEIGHTED ESTIMATION AND TRACKING FOR ARMAX MODELS

机译:ARMAX模型的加权估计和跟踪

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摘要

For complex multivariate ARMAX models, the author studies the weighted least squares algorithm which offers, by the choice of suitable weightings, the advantages of both the extended least squares and the stochastic gradient algorithms. Concerning adaptive tracking problems, the strong consistency of the estimator and control optimality are both ensured. Almost sure rates of convergence are also provided. [References: 28]
机译:对于复杂的多元ARMAX模型,作者研究了加权最小二乘算法,该算法通过选择合适的权重,提供了扩展最小二乘和随机梯度算法的优势。关于自适应跟踪问题,确保了估计器的强一致性和控制最优性。几乎可以确保收敛速度。 [参考:28]

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