On the solution of operator equation problems with application to Preisach density estimation

Yu Hua, Ram V. Iyer

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, we study the numerical solution of a linear, compact, integral operator equation with linear inequality constraints on the solution space. The operator equation is approximated by a linear matrix equation via discretization, which may be then solved using a linear least squares L2 approach. Three methods, including two new methods, for the regularization of the discretized equation without constraints were presented. We compare the sensitivity of the solutions from these methods for perturbations in the data; we also compare the time taken for solution. Next, we present a new algorithm to solve the linear inequality constrained, minimum norm, least squares problem by adapting the solution methods presented for the unconstrained problem. Then we compare it with the MatLab

Original languageEnglish
Title of host publication2016 American Control Conference, ACC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2427-2432
Number of pages6
ISBN (Electronic)9781467386821
DOIs
StatePublished - Jul 28 2016
Event2016 American Control Conference, ACC 2016 - Boston, United States
Duration: Jul 6 2016Jul 8 2016

Publication series

NameProceedings of the American Control Conference
Volume2016-July
ISSN (Print)0743-1619

Conference

Conference2016 American Control Conference, ACC 2016
CountryUnited States
CityBoston
Period07/6/1607/8/16

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