Regularization Theory for Ill-posed Problems
Selected Topics
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Beschreibung
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.
Autor*in
Shuai Lu
Themen in »Regularization Theory for Ill-posed Problems«
Ill-posed Problem Regularization Method Multi-parameter Regularization Discrepancy Principle Balancing Principle Error Bound Estimation Convergence Rate Learning Theory Meta-learning Blood Glucose Prediction