Optimization with few violated constraints for linear bounded error parameter estimation
Optimization with few violated constraints for linear bounded error parameter estimation
复制标题
线性有界误差参数估计的很少违反约束的优化
DOI：
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发表时间：
2002
影响因子：
6.8
通讯作者：
Y. Ye
中科院分区：
文献类型：
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作者：
E. Bai;Hyonyong Cho;R. Tempo;Y. Ye
在线性约束优化的背景下，我们研究了在给定的n个约束中寻找除k以外的所有最优解的问题。通过一个复杂性为min{O(n/spl midpoint/k/sup d/)，O(n/spl midpoint/d/sup k+1/)}的算法得到一个解，其中d是问题的维度。然后，我们利用这些结果来解决有界误差参数辨识设置中存在异常值时的鲁棒辨识问题。最后，我们证明了在存在异常值的情况下，所得到的估计收敛于真实的未知参数。
In the context of linear constrained optimization, we study the problem of finding an optimal solution satisfying all but k of the given n constraints. A solution is obtained by means of an algorithm of the complexity min{O(n/spl middot/k/sup d/), O(n/spl middot/d/sup k+1/)}, where d is the dimension of the problem. We then use these results to solve the problem of robust identification in the presence of outliers in the setting of bounded error parameter identification. Finally, we show that the estimate obtained converges to the true but unknown parameter in the presence of outliers.