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  • 标题:On the choice of subspace for iterative methods for linear discrete ill-posed problems
  • 本地全文:下载
  • 作者:Daniela Calvetti ; Bryan Lewis ; Lothar Reichel
  • 期刊名称:International Journal of Applied Mathematics and Computer Science
  • 电子版ISSN:2083-8492
  • 出版年度:2001
  • 卷号:11
  • 期号:5
  • 出版社:De Gruyter Open
  • 摘要:Many iterative methods for the solution of linear discrete ill-posed problems with a large matrix require the computed approximate solutions to be orthogonal to the null space of the matrix. We show that when the desired solution is not smooth, it may be possible to determine meaningful approximate solutions with less computational work by not imposing this orthogonality condition
  • 关键词:minimal residual method; conjugate gradient method; ill-posed problems
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