The goal of this book is to introduce the reader to methodologies in recovery problems for objects, such as functions and signals, from partial or indirect information. The recovery of objects from a set of data demands key solvers of inverse and sampling problems. Until recently, connections betwee...

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Bibliographic Details

Main Authors:	Freeden, Willi 1948- (Author), Nashed, M. Zuhair 1936- (Author)
Format:	Electronic eBook
Language:	English
Published:	Providence, Rhode Island American Mathematical Society [2023]
Series:	Mathematical surveys and monographs Volume 274
Subjects:	Sampling (Statistics) Inverse problems (Differential equations) / Numerical solutions Numerical analysis > Numerical analysis in abstract spaces > Improperly posed problems; regularization Statistics > Sampling theory, sample surveys > Sampling theory, sample surveys Numerical analysis > Integral equations, integral transforms > Inverse problems Optics, electromagnetic theory > General > Antennas, wave-guides Information and communication, circuits > Communication, information > Sampling theory Geophysics > Geophysics > Inverse problems
Online Access:	Volltext
Summary:	The goal of this book is to introduce the reader to methodologies in recovery problems for objects, such as functions and signals, from partial or indirect information. The recovery of objects from a set of data demands key solvers of inverse and sampling problems. Until recently, connections between the mathematical areas of inverse problems and sampling were rather tenuous. However, advances in several areas of mathematical research have revealed deep common threads between them, which proves that there is a serious need for a unifying description of the underlying mathematical ideas and concepts. Freeden and Nashed present an integrated approach to resolution methodologies from the perspective of both these areas. Researchers in sampling theory will benefit from learning about inverse problems and regularization methods, while specialists in inverse problems will gain a better understanding of the point of view of sampling concepts. This book requires some basic knowledge of functional analysis, Fourier theory, geometric number theory, constructive approximation, and special function theory. By avoiding extreme technicalities and elaborate proof techniques, it is an accessible resource for students and researchers not only from applied mathematics, but also from all branches of engineering and science.
Item Description:	Includes bibliographical references and index
Physical Description:	1 Online-Ressource (xii, 490 Seiten) Illustrationen, Diagramme
ISBN:	9781470474515 9781470473457
DOI:	10.1090/surv/274