The book examines the mollification method and its multiple applications when used as a space marching method. Unlike most books on ill-posed problems, this volume contains all the motivations, proofs, algorithms, and exercises necessary to fully understand the subject.

The book examines the mollification method and its multiple applications when used as a space marching method. These computations are compared with various other methods used to arrive at the same numerical results. Of special interest is a novel treatment of the two-dimensional inverse heat conduction problem on a bounded domain.

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The mollification method and the numerical solution of ill-posed problems.

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The author created the Mollification Method as a means of dealing with ill-posed problems. About the author DIEGO A. MURIO is Professor of Mathematics at the University of Cincinnati. Although the presentation focuses on problems with origins in mechanical engineering, many of the ideas and techniques can be easily applied to a broad range of situations. A recipient of both the Taft and National Science Foundation grants, Professor Murio has published more than forty papers and serves as referee for the NSF as well as several mathematics journals. He is a member of SIAM and an executive member of the Annual Seminar on Inverse Problems in Engineering.

This book is intended to be a self-contained presentation of practical computational methods which have been extensively and successfully applied to a wide range of ill-posed problems. The Mollification Method and the Numerical Solution of Ill-Posed Problems (Diego A. Murio).

Book Publishing WeChat. ABSTRACT: In preceding papers, the present authors proposed the application of the mollification based on wavelets to the calculation of the fractional derivative (fD) or the derivative of a function involving noise. 1993) The Mollification Method and the Numerical Solution of Ill-Posed Problems. John Wiley, New York. We study here the application of that method to the detection of edge of a function. Mathieu et al. proposed the CRONE detector for a detection of an edge of an image.