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Optimized selection of observation model parameters based on QR decomposition

机译:基于QR分解的观测模型参数优化选择

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Based on QR decomposition, this paper proposes a method for optimized selection of observation model parameters. It includes several stages: first, by employing QR decomposition of observation matrix, the analysis of observation model is converted into the analysis of the upper triangular matrix R from QR decomposition; second, the deep analysis of the ill-condition of the model is carried out combining the observant structure; for the third stage, the reason for the production of ill-condition is further analyzed; the selection of parameters of the model is optimized in the final. The numerical experiments show that our method is feasible and can be implemented with ease.
机译:基于QR分解,提出了一种观测模型参数的优化选择方法。它包括以下几个阶段:首先,通过对观测矩阵进行QR分解,将观测模型的分析转换为QR分解对上三角矩阵R的分析。其次,结合观察者结构对模型的病情进行了深入的分析。第三阶段,进一步分析了产生疾病的原因。最后,对模型参数的选择进行了优化。数值实验表明,该方法是可行的,并且易于实现。

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