Regularization properties of LSQR for linear discrete ill-posed problems in the multiple singular value case and best, near best and general low rank approximations

Regularization properties of LSQR for linear discrete ill-posed problems in the multiple singular value case and best, near best and general low rank approximations
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多奇异值情况下线性离散不适定问题的 LSQR 正则化特性以及最佳、近最佳和一般低秩近似

DOI:
10.1088/1361-6420/ab9c45
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发表时间:
2020-03
期刊:
影响因子:
2.1
通讯作者:
Jia Zhongxiao
Jia Zhongxiao
中科院分区:
数学2区
文献类型:
--
作者:
Jia Zhongxiao

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For the large-scale linear discrete ill-posed problem min‖Ax − b‖ or Ax = b with b contaminated by white noise, the Golub–Kahan bidiagonalization based LSQR method and its mathematically equivalent CGLS, the conjugate gradient (CG) method applied to ATAx
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