Parameter estimation in the presence of non-Gaussian noise

H. Salzwedel
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引用次数: 2

Abstract

A method for parameter estimation is derived that is insensitive to the noise distribution, and an example of its use for nonlinear systems is given. The method combines the sensitivity of the maximum-likelihood parameter estimator with the robustness of order statistics to reduce estimation uncertainty significantly, with only a slight increase in the variance. This algorithm shows improvements over conventional parameter estimates, in particular, in the case of small data sets.
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非高斯噪声存在下的参数估计
推导了一种对噪声分布不敏感的参数估计方法,并给出了非线性系统参数估计的应用实例。该方法将最大似然参数估计量的敏感性与序统计量的鲁棒性相结合,在方差略有增加的情况下显著降低了估计的不确定性。该算法比传统的参数估计有了改进,特别是在小数据集的情况下。
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