A New Method for TSVD Regularization Truncated Parameter Selection

作者：Wu, Zemin^*; Bian, Shaofeng; Xiang, Caibing; Tong, Yude

来源：Mathematical Problems in Engineering, 2013, 2013: 161834.

DOI：10.1155/2013/161834

• ILL-POSED PROBLEMS
• SIMULATION

The truncated singular value decomposition (TSVD) regularization applied in ill-posed problem is studied. Through mathematical analysis, a new method for truncated parameter selection which is applied in TSVD regularization is proposed. In the new method, all the local optimal truncated parameters are selected first by taking into account the interval estimation of the observation noises; then the optimal truncated parameter is selected from the local optimal ones. While comparing the new method with the traditional generalized cross-validation (GCV) and L curve methods, a random ill-posed matrices simulation approach is developed in order to make the comparison as statistically meaningful as possible. Simulation experiments have shown that the solutions applied with the new method have the smallest mean square errors, and the computational cost of the new algorithm is the least.

• 出版日期2013
• 单位中国人民解放军海军工程大学