Regularization of linear and nonlinear ill-posed problems by mollification
In this paper, we address the problem of approximating solutions of ill-posed problems using mollification. We quickly review existing mollification regularization methods and provide two new approximate solutions to a general ill-posed equation $T(f) =g$ where $T$ can be nonlinear. The regularized...
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creator | Lee, Walter Cedric Simo Tao |
description | In this paper, we address the problem of approximating solutions of ill-posed
problems using mollification. We quickly review existing mollification
regularization methods and provide two new approximate solutions to a general
ill-posed equation $T(f) =g$ where $T$ can be nonlinear. The regularized
solutions we define extend the work of Bonnefond and Mar\'echal \cite{xapi},
and trace their origins in the variational formulation of mollification, which
to the best of our knowledge, was first introduced by Lannes et al.
\cite{lannes}. In addition to consistency results, for the first time, we
provide some convergence rates for a mollification method defined through a
variational formulation. |
doi_str_mv | 10.48550/arxiv.2003.07913 |
format | Article |
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problems using mollification. We quickly review existing mollification
regularization methods and provide two new approximate solutions to a general
ill-posed equation $T(f) =g$ where $T$ can be nonlinear. The regularized
solutions we define extend the work of Bonnefond and Mar\'echal \cite{xapi},
and trace their origins in the variational formulation of mollification, which
to the best of our knowledge, was first introduced by Lannes et al.
\cite{lannes}. In addition to consistency results, for the first time, we
provide some convergence rates for a mollification method defined through a
variational formulation.</description><identifier>DOI: 10.48550/arxiv.2003.07913</identifier><language>eng</language><subject>Computer Science - Numerical Analysis ; Mathematics - Functional Analysis ; Mathematics - Numerical Analysis ; Mathematics - Optimization and Control</subject><creationdate>2020-03</creationdate><rights>http://arxiv.org/licenses/nonexclusive-distrib/1.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,780,885</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2003.07913$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2003.07913$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Lee, Walter Cedric Simo Tao</creatorcontrib><title>Regularization of linear and nonlinear ill-posed problems by mollification</title><description>In this paper, we address the problem of approximating solutions of ill-posed
problems using mollification. We quickly review existing mollification
regularization methods and provide two new approximate solutions to a general
ill-posed equation $T(f) =g$ where $T$ can be nonlinear. The regularized
solutions we define extend the work of Bonnefond and Mar\'echal \cite{xapi},
and trace their origins in the variational formulation of mollification, which
to the best of our knowledge, was first introduced by Lannes et al.
\cite{lannes}. In addition to consistency results, for the first time, we
provide some convergence rates for a mollification method defined through a
variational formulation.</description><subject>Computer Science - Numerical Analysis</subject><subject>Mathematics - Functional Analysis</subject><subject>Mathematics - Numerical Analysis</subject><subject>Mathematics - Optimization and Control</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotz8tqwzAUBFBtsihJP6Cr6gfsypIlRcsS0heBQMne3KtHEciSkdPS9OtL3ayGWczAIeSuY22_lZI9QP2OXy1nTLRMm07ckLd3__GZoMYfOMeSaQk0xeyhUsiO5pKvLabUTGX2jk61YPLjTPFCx5JSDNEu2w1ZBUizv73mmpye9qfdS3M4Pr_uHg8NKC0ajb22XeBaWImcqdB7i1oFB7I3gTs02DnnNSgvJDPcaLdliiupEdCiEmty_3-7YIapxhHqZfhDDQtK_ALpMUio</recordid><startdate>20200317</startdate><enddate>20200317</enddate><creator>Lee, Walter Cedric Simo Tao</creator><scope>AKY</scope><scope>AKZ</scope><scope>GOX</scope></search><sort><creationdate>20200317</creationdate><title>Regularization of linear and nonlinear ill-posed problems by mollification</title><author>Lee, Walter Cedric Simo Tao</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a673-7b47c1f273c5b206f4ecb76fda549f2db9b1dde7a6e3509297d8062657babcb63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Computer Science - Numerical Analysis</topic><topic>Mathematics - Functional Analysis</topic><topic>Mathematics - Numerical Analysis</topic><topic>Mathematics - Optimization and Control</topic><toplevel>online_resources</toplevel><creatorcontrib>Lee, Walter Cedric Simo Tao</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv Mathematics</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Lee, Walter Cedric Simo Tao</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Regularization of linear and nonlinear ill-posed problems by mollification</atitle><date>2020-03-17</date><risdate>2020</risdate><abstract>In this paper, we address the problem of approximating solutions of ill-posed
problems using mollification. We quickly review existing mollification
regularization methods and provide two new approximate solutions to a general
ill-posed equation $T(f) =g$ where $T$ can be nonlinear. The regularized
solutions we define extend the work of Bonnefond and Mar\'echal \cite{xapi},
and trace their origins in the variational formulation of mollification, which
to the best of our knowledge, was first introduced by Lannes et al.
\cite{lannes}. In addition to consistency results, for the first time, we
provide some convergence rates for a mollification method defined through a
variational formulation.</abstract><doi>10.48550/arxiv.2003.07913</doi><oa>free_for_read</oa></addata></record> |
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subjects | Computer Science - Numerical Analysis Mathematics - Functional Analysis Mathematics - Numerical Analysis Mathematics - Optimization and Control |
title | Regularization of linear and nonlinear ill-posed problems by mollification |
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