Loading…
Generalized RMIL conjugate gradient method under the strong Wolfe line search with application in image processing
RMIL conjugate gradient method originally proposed by Rivaie et al. (2012) has recently gained lots of attention. In this article, we propose a generalized conjugate gradient parameter that contains both RMIL and its variant, that is, RMIL+, as special cases. We show that the search direction genera...
Saved in:
Published in: | Mathematical methods in the applied sciences 2023-11, Vol.46 (16), p.17544-17556 |
---|---|
Main Authors: | , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c289t-bbbd91dff89f0a2b9b3aadbbb0e298ae3462ef3dcd0974f5762b0a386cded7e43 |
---|---|
cites | cdi_FETCH-LOGICAL-c289t-bbbd91dff89f0a2b9b3aadbbb0e298ae3462ef3dcd0974f5762b0a386cded7e43 |
container_end_page | 17556 |
container_issue | 16 |
container_start_page | 17544 |
container_title | Mathematical methods in the applied sciences |
container_volume | 46 |
creator | Awwal, Aliyu Muhammed Wang, Lin Kumam, Poom Sulaiman, Mohammed Ibrahim Salisu, Sani Salihu, Nasiru Yodjai, Petcharaporn |
description | RMIL conjugate gradient method originally proposed by Rivaie et al. (2012) has recently gained lots of attention. In this article, we propose a generalized conjugate gradient parameter that contains both RMIL and its variant, that is, RMIL+, as special cases. We show that the search direction generated by the new method is sufficiently descent. Under standard mild conditions, we discuss the convergence analysis of the propose method. We demonstrate the numerical efficiency of the propose method on a set of unconstrained minimization benchmark test problems as well as an image restoration problem. The results of the experiment reveal that the proposed method performs better than its main competitors. |
doi_str_mv | 10.1002/mma.9515 |
format | article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2879080537</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2879080537</sourcerecordid><originalsourceid>FETCH-LOGICAL-c289t-bbbd91dff89f0a2b9b3aadbbb0e298ae3462ef3dcd0974f5762b0a386cded7e43</originalsourceid><addsrcrecordid>eNotkN1KAzEUhIMoWKvgIwS88WZrkv3NpRSthYogipdLNjnZTdlN1iRF9OmNVBg4MAxnhg-ha0pWlBB2N01ixUtanqAFJZxntKirU7QgtCZZwWhxji5C2BNCGkrZAvkNWPBiND-g8Ovzdoels_tDLyLg3gtlwEY8QRycwgerwOM4AA7RO9vjDzdqwKOxyQHh5YC_TBywmOfRSBGNs9gkTaIHPHsnIQRj-0t0psUY4Or_LtH748Pb-inbvWy26_tdJlnDY9Z1neJUad1wTQTreJcLoZJLgPFGQF5UDHSupCK8LnRZV6wjIm8qqUDVUORLdHP8m6o_DxBiu3cHb1Nly5qak4aUeZ1St8eU9C4ED7qdfVrsv1tK2j-ibSLa_hHNfwEg8GvP</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2879080537</pqid></control><display><type>article</type><title>Generalized RMIL conjugate gradient method under the strong Wolfe line search with application in image processing</title><source>Wiley-Blackwell Read & Publish Collection</source><creator>Awwal, Aliyu Muhammed ; Wang, Lin ; Kumam, Poom ; Sulaiman, Mohammed Ibrahim ; Salisu, Sani ; Salihu, Nasiru ; Yodjai, Petcharaporn</creator><creatorcontrib>Awwal, Aliyu Muhammed ; Wang, Lin ; Kumam, Poom ; Sulaiman, Mohammed Ibrahim ; Salisu, Sani ; Salihu, Nasiru ; Yodjai, Petcharaporn</creatorcontrib><description>RMIL conjugate gradient method originally proposed by Rivaie et al. (2012) has recently gained lots of attention. In this article, we propose a generalized conjugate gradient parameter that contains both RMIL and its variant, that is, RMIL+, as special cases. We show that the search direction generated by the new method is sufficiently descent. Under standard mild conditions, we discuss the convergence analysis of the propose method. We demonstrate the numerical efficiency of the propose method on a set of unconstrained minimization benchmark test problems as well as an image restoration problem. The results of the experiment reveal that the proposed method performs better than its main competitors.</description><identifier>ISSN: 0170-4214</identifier><identifier>EISSN: 1099-1476</identifier><identifier>DOI: 10.1002/mma.9515</identifier><language>eng</language><publisher>Freiburg: Wiley Subscription Services, Inc</publisher><subject>Conjugate gradient method ; Image processing ; Image restoration</subject><ispartof>Mathematical methods in the applied sciences, 2023-11, Vol.46 (16), p.17544-17556</ispartof><rights>2023 John Wiley & Sons, Ltd.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c289t-bbbd91dff89f0a2b9b3aadbbb0e298ae3462ef3dcd0974f5762b0a386cded7e43</citedby><cites>FETCH-LOGICAL-c289t-bbbd91dff89f0a2b9b3aadbbb0e298ae3462ef3dcd0974f5762b0a386cded7e43</cites><orcidid>0000-0002-1040-3626 ; 0000-0001-5246-6636 ; 0000-0002-5463-4581</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Awwal, Aliyu Muhammed</creatorcontrib><creatorcontrib>Wang, Lin</creatorcontrib><creatorcontrib>Kumam, Poom</creatorcontrib><creatorcontrib>Sulaiman, Mohammed Ibrahim</creatorcontrib><creatorcontrib>Salisu, Sani</creatorcontrib><creatorcontrib>Salihu, Nasiru</creatorcontrib><creatorcontrib>Yodjai, Petcharaporn</creatorcontrib><title>Generalized RMIL conjugate gradient method under the strong Wolfe line search with application in image processing</title><title>Mathematical methods in the applied sciences</title><description>RMIL conjugate gradient method originally proposed by Rivaie et al. (2012) has recently gained lots of attention. In this article, we propose a generalized conjugate gradient parameter that contains both RMIL and its variant, that is, RMIL+, as special cases. We show that the search direction generated by the new method is sufficiently descent. Under standard mild conditions, we discuss the convergence analysis of the propose method. We demonstrate the numerical efficiency of the propose method on a set of unconstrained minimization benchmark test problems as well as an image restoration problem. The results of the experiment reveal that the proposed method performs better than its main competitors.</description><subject>Conjugate gradient method</subject><subject>Image processing</subject><subject>Image restoration</subject><issn>0170-4214</issn><issn>1099-1476</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNotkN1KAzEUhIMoWKvgIwS88WZrkv3NpRSthYogipdLNjnZTdlN1iRF9OmNVBg4MAxnhg-ha0pWlBB2N01ixUtanqAFJZxntKirU7QgtCZZwWhxji5C2BNCGkrZAvkNWPBiND-g8Ovzdoels_tDLyLg3gtlwEY8QRycwgerwOM4AA7RO9vjDzdqwKOxyQHh5YC_TBywmOfRSBGNs9gkTaIHPHsnIQRj-0t0psUY4Or_LtH748Pb-inbvWy26_tdJlnDY9Z1neJUad1wTQTreJcLoZJLgPFGQF5UDHSupCK8LnRZV6wjIm8qqUDVUORLdHP8m6o_DxBiu3cHb1Nly5qak4aUeZ1St8eU9C4ED7qdfVrsv1tK2j-ibSLa_hHNfwEg8GvP</recordid><startdate>20231115</startdate><enddate>20231115</enddate><creator>Awwal, Aliyu Muhammed</creator><creator>Wang, Lin</creator><creator>Kumam, Poom</creator><creator>Sulaiman, Mohammed Ibrahim</creator><creator>Salisu, Sani</creator><creator>Salihu, Nasiru</creator><creator>Yodjai, Petcharaporn</creator><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>KR7</scope><orcidid>https://orcid.org/0000-0002-1040-3626</orcidid><orcidid>https://orcid.org/0000-0001-5246-6636</orcidid><orcidid>https://orcid.org/0000-0002-5463-4581</orcidid></search><sort><creationdate>20231115</creationdate><title>Generalized RMIL conjugate gradient method under the strong Wolfe line search with application in image processing</title><author>Awwal, Aliyu Muhammed ; Wang, Lin ; Kumam, Poom ; Sulaiman, Mohammed Ibrahim ; Salisu, Sani ; Salihu, Nasiru ; Yodjai, Petcharaporn</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c289t-bbbd91dff89f0a2b9b3aadbbb0e298ae3462ef3dcd0974f5762b0a386cded7e43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Conjugate gradient method</topic><topic>Image processing</topic><topic>Image restoration</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Awwal, Aliyu Muhammed</creatorcontrib><creatorcontrib>Wang, Lin</creatorcontrib><creatorcontrib>Kumam, Poom</creatorcontrib><creatorcontrib>Sulaiman, Mohammed Ibrahim</creatorcontrib><creatorcontrib>Salisu, Sani</creatorcontrib><creatorcontrib>Salihu, Nasiru</creatorcontrib><creatorcontrib>Yodjai, Petcharaporn</creatorcontrib><collection>CrossRef</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><jtitle>Mathematical methods in the applied sciences</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Awwal, Aliyu Muhammed</au><au>Wang, Lin</au><au>Kumam, Poom</au><au>Sulaiman, Mohammed Ibrahim</au><au>Salisu, Sani</au><au>Salihu, Nasiru</au><au>Yodjai, Petcharaporn</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Generalized RMIL conjugate gradient method under the strong Wolfe line search with application in image processing</atitle><jtitle>Mathematical methods in the applied sciences</jtitle><date>2023-11-15</date><risdate>2023</risdate><volume>46</volume><issue>16</issue><spage>17544</spage><epage>17556</epage><pages>17544-17556</pages><issn>0170-4214</issn><eissn>1099-1476</eissn><abstract>RMIL conjugate gradient method originally proposed by Rivaie et al. (2012) has recently gained lots of attention. In this article, we propose a generalized conjugate gradient parameter that contains both RMIL and its variant, that is, RMIL+, as special cases. We show that the search direction generated by the new method is sufficiently descent. Under standard mild conditions, we discuss the convergence analysis of the propose method. We demonstrate the numerical efficiency of the propose method on a set of unconstrained minimization benchmark test problems as well as an image restoration problem. The results of the experiment reveal that the proposed method performs better than its main competitors.</abstract><cop>Freiburg</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1002/mma.9515</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0002-1040-3626</orcidid><orcidid>https://orcid.org/0000-0001-5246-6636</orcidid><orcidid>https://orcid.org/0000-0002-5463-4581</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0170-4214 |
ispartof | Mathematical methods in the applied sciences, 2023-11, Vol.46 (16), p.17544-17556 |
issn | 0170-4214 1099-1476 |
language | eng |
recordid | cdi_proquest_journals_2879080537 |
source | Wiley-Blackwell Read & Publish Collection |
subjects | Conjugate gradient method Image processing Image restoration |
title | Generalized RMIL conjugate gradient method under the strong Wolfe line search with application in image processing |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-27T10%3A29%3A07IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Generalized%20RMIL%20conjugate%20gradient%20method%20under%20the%20strong%20Wolfe%20line%20search%20with%20application%20in%20image%20processing&rft.jtitle=Mathematical%20methods%20in%20the%20applied%20sciences&rft.au=Awwal,%20Aliyu%20Muhammed&rft.date=2023-11-15&rft.volume=46&rft.issue=16&rft.spage=17544&rft.epage=17556&rft.pages=17544-17556&rft.issn=0170-4214&rft.eissn=1099-1476&rft_id=info:doi/10.1002/mma.9515&rft_dat=%3Cproquest_cross%3E2879080537%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c289t-bbbd91dff89f0a2b9b3aadbbb0e298ae3462ef3dcd0974f5762b0a386cded7e43%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2879080537&rft_id=info:pmid/&rfr_iscdi=true |