首页> 外文期刊>Engineering analysis with boundary elements >Optimal algorithms in a Krylov subspace for solving linear inverse problems by MFS
【24h】

Optimal algorithms in a Krylov subspace for solving linear inverse problems by MFS

机译:MFS解决线性逆问题的Krylov子空间中的最佳算法

获取原文
获取原文并翻译 | 示例
           

摘要

The method of fundamental solutions (MFS) is used to solve backward heat conduction problem, inverse heat source problem, inverse Cauchy problem and inverse Robin problem. In order to overcome the ill-posedness of resulting linear equations, two optimal algorithms with optimal descent vectors that consist of m vectors in a Krylov subspace are developed, of which the m weighting parameters are determined by minimizing a properly defined merit function in terms of a quadratic quotient. The optimal algorithms OA1 and OA2 are convergent fast, accurate and robust against large noise, which are confirmed through numerical tests.
机译:基本解法(MFS)用于求解反向传热问题,反向热源问题,反向柯西问题和反向罗宾问题。为了克服线性方程组的不适定性,开发了两种最优算法的最优算法,这些最优算法由Krylov子空间中的m个矢量组成,其中m个权重参数通过最小化根据二次商。最优算法OA1和OA2收敛快速,准确且鲁棒,可抵抗较大的噪声,这通过数值测试得到了证实。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号