2020
DOI: 10.1109/mim.2020.9062690
|View full text |Cite
|
Sign up to set email alerts
|

Inverse algorithms—powerful tools to improve measurement systems

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2022
2022
2022
2022

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(2 citation statements)
references
References 10 publications
0
2
0
Order By: Relevance
“…where λ is the hyperparameter, and R is the regularization matrix by Tikhonov prior [20]. ∆σ is reconstructed by iteration as ( ) ( )…”
Section: A Second-order Sensitivity Matrix Eitmentioning
confidence: 99%
See 1 more Smart Citation
“…where λ is the hyperparameter, and R is the regularization matrix by Tikhonov prior [20]. ∆σ is reconstructed by iteration as ( ) ( )…”
Section: A Second-order Sensitivity Matrix Eitmentioning
confidence: 99%
“…where λ is the hyperparameter, and R is the regularization matrix by Tikhonov regularization [20]. k is the number of iteration times in the Gauss-Newton iterative method supported by the EIDORS software (ver.…”
Section: Image Reconstructionmentioning
confidence: 99%