Nonlinear Estimation for Linear Inverse Problems with Error in the Operator
Nonlinear Estimation for Linear Inverse Problems with Error in the Operator
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Publisher
Hayward, CA: Institute of Mathematical Statistics
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Language
English
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Publisher
Hayward, CA: Institute of Mathematical Statistics
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Contents
We study two nonlinear methods for statistical linear inverse problems when the operator is not known. The two constructions combine Galerkin regularization and wavelet thresholding. Their performances depend on the underlying structure of the operator, quantified by an index of sparsity. We prove their rate-optimality and adaptivity properties ove...
Alternative Titles
Full title
Nonlinear Estimation for Linear Inverse Problems with Error in the Operator
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Author / Creator
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TN_cdi_projecteuclid_primary_oai_CULeuclid_euclid_aos_1201877303
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_projecteuclid_primary_oai_CULeuclid_euclid_aos_1201877303
Other Identifiers
ISSN
0090-5364
E-ISSN
2168-8966
DOI
10.1214/009053607000000721
