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Regularization theory for ill-posed problems : selected topics / / by Shuai Lu, Sergei V. Pereverzev



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Autore: Lu Shuai <1976-> Visualizza persona
Titolo: Regularization theory for ill-posed problems : selected topics / / by Shuai Lu, Sergei V. Pereverzev Visualizza cluster
Pubblicazione: Berlin ; ; Boston : , : Walter de Gruyter, , [2013]
©2013
Descrizione fisica: 1 online resource (304 p.)
Disciplina: 518/.53
Soggetto topico: Numerical analysis - Improperly posed problems
Numerical differentiation
Soggetto non controllato: Balancing Principle
Blood Glucose Prediction
Convergence Rate
Discrepancy Principle
Error Bound Estimation
Ill-posed Problem
Learning Theory, Meta-learning
Multi-parameter Regularization
Regularization Method
Altri autori: PereverzevSergei V  
Note generali: Description based upon print version of record.
Nota di bibliografia: Includes bibliographical references and index.
Nota di contenuto: Front matter -- Preface -- Contents -- Chapter 1. An introduction using classical examples -- Chapter 2. Basics of single parameter regularization schemes -- Chapter 3. Multiparameter regularization -- Chapter 4. Regularization algorithms in learning theory -- Chapter 5. Meta-learning approach to regularization - case study: blood glucose prediction -- Bibliography -- Index
Sommario/riassunto: This monograph is a valuable contribution to the highly topical and extremely productive field of regularization 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 demonstrates the current developments in the field of regularization theory, such as multi parameter regularization and regularization in learning theory. The book is written for graduate and PhDs
Titolo autorizzato: Regularization theory for ill-posed problems  Visualizza cluster
ISBN: 3-11-028649-1
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910787646303321
Lo trovi qui: Univ. Federico II
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Serie: Inverse and ill-posed problems series ; ; v. 58.