图 书 馆
带约束最小二乘问题的数值求解方法Numerical Methods for Solving Least Squares Problems with Constraints |
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| 课程网址: | http://videolectures.net/mlws04_gene_nmsls/ |
| 主讲教师: | Gene Golub |
| 开课单位: | 斯坦福大学 |
| 开课时间: | 2007-02-25 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | In this talk, we discuss the problem of solving linear least squares problems and Total Least Squares problems with linear constraints and/or a quadratic constraint. We are particularly interested in developing stable numerical methods when the data matrix is singular or near singular. Of particular interest are matrices which are large and sparse and for which iterative methods must be employed. The quadratically constrained problems arise in problems where regularization is required. For such problems, a Lagrange multiplier is required and that calculation may be quite intensive. The method we propose will quickly yield an estimate of the parameter and allow for finding the least squares solution. |
| 关 键 词: | 线性约束; 最小二乘问题; 数据矩阵 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-07-24：cwx |
| 阅读次数: | 83 |