1.

Record Nr.

UNISA996209738303316

Titolo

African journal of information and communication technology

Pubbl/distr/stampa

Sydney, Australia, : University of Technology

Soggetti

Telecommunication

Information theory

Software engineering

Periodicals.

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Periodico

Note generali

Refereed/Peer-reviewed

African Journal of Information and Communication Technology (AJICT)--is an international journal providing a publication vehicle for coverage of topics of interest to those involved in computing, communication networks, electronic communications, information technology systems and Bioinformatics. It is serving as an open source vehicle of the works of researchers in ICT world wide that hitherto would not be available to organisations outside and within the African sub-region.



2.

Record Nr.

UNINA9910787646303321

Autore

Lu Shuai <1976->

Titolo

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

Pubbl/distr/stampa

Berlin ; ; Boston : , : Walter de Gruyter, , [2013]

©2013

ISBN

3-11-028649-1

Descrizione fisica

1 online resource (304 p.)

Collana

Inverse and ill-posed problems series ; ; 58

Altri autori (Persone)

PereverzevSergei V

Disciplina

518/.53

Soggetti

Numerical analysis - Improperly posed problems

Numerical differentiation

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

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