A case study of the consistency problem in the inverse estimation
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摘要: 逆方法是海洋学研究中一个常用的方法,但是所求解的统计量通常和模式的先验假设不一致。为了解决这一问题,本文尝试将所求解的统计量作为模式的先验统计量,然后进行下一轮求逆运算,并重复这一过程。通过分析一个具体的案例,发现经过数次迭代之后,由于解和模式误差的协方差矩阵的行列式会变为零,从而所求解的统计量和它的先验假设之间的一致性变得很难评估。然而,在迭代过程中,解的后验统计量和先验统计量之间的数值上差异能够逐渐缩小。Abstract: Inverse technique is a widely used method in oceanography, but it has a problem that the retrieved solutions often violate model prior assumptions. To tune the model has consistent solutions, an iteration approach, which successively utilizes the posterior statistics for next round inverse estimation, is introduced and tested from a real case study. It is found that the consistency may become elusive as the determinants of solution and noise covariance matrices become zero in the iteration process. However, after several steps of such operation, the difference between posterior statistics and the model prior ones can be gradually reduced.
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Key words:
- regularization /
- consistency /
- inverse problems /
- box inverse model /
- L-curve method
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