Regularization Theory for Ill-posed Problems
Produktnummer:
185a5e888d20b9463797ccb774bbd4850e
Autor: | Lu, Shuai Pereverzev, Sergei V. |
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Themengebiete: | Balancing Principle Blood Glucose Prediction Convergence Rate Discrepancy Principle Error Bound Estimation Ill-posed Problem Learning Theory Meta-learning Multi-parameter Regularization Regularization Method |
Veröffentlichungsdatum: | 17.07.2013 |
EAN: | 9783110286465 |
Auflage: | 1 |
Sprache: | Englisch |
Seitenzahl: | 289 |
Produktart: | Gebunden |
Verlag: | De Gruyter |
Untertitel: | Selected Topics |
Produktinformationen "Regularization Theory for Ill-posed Problems"
This monograph is a valuable contribution to the highly topical and extremly productive field of regularisation methods for inverse and ill-posed problems. The author is an internationally outstanding and accepted mathematician in this field. In his book he offers a well-balanced mixture of basic and innovative aspects. He demonstrates new, differentiated viewpoints, and important examples for applications. The book demontrates the current developments in the field of regularization theory, such as multiparameter regularization and regularization in learning theory. The book is written for graduate and PhD students and researchers in mathematics, natural sciences, engeneering, and medicine.

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