An iterative algorithm for solving ill-conditioned linear least squares problems

An iterative algorithm for solving ill-conditioned linear least squares problems

Linear Least Squares (LLS) problems are particularly difficult to solve because they are frequently ill-conditioned, and involve large quantities of data. Ill-conditioned LLS problems are commonly seen in mathematics and geosciences, where regularization algorithms are employed to seek optimal solut...

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Bibliographic Details
Main Authors: Xingsheng Deng, Liangbo Yin, Sichun Peng, Meiqing Ding
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2015-11-01
Series:Geodesy and Geodynamics
Subjects:
Severe ill-conditioned matrix
Linear least squares problems
Self-adaptive
Iterative scheme
Cholesky decomposition
Regularization parameter
Tikhonov solution
Truncated SVD solution
Online Access:http://www.sciencedirect.com/science/article/pii/S1674984715000956

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http://www.sciencedirect.com/science/article/pii/S1674984715000956

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