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Solving fuzzy linear systems by a block representation of generalized inverse: the core inverse
This paper presents a method for solving fuzzy linear systems, where the coefficient matrix is an n × n real matrix, using a block structure of the Core inverse, and we use the Hartwig–Spindelböck decomposition to obtain the Core inverse of the coefficient matrix A . The aim of this paper is twofold...
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Published in: | Computational & applied mathematics 2020-05, Vol.39 (2), Article 133 |
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container_title | Computational & applied mathematics |
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creator | Jiang, Hongjie Wang, Hongxing Liu, Xiaoji |
description | This paper presents a method for solving fuzzy linear systems, where the coefficient matrix is an
n
×
n
real matrix, using a block structure of the Core inverse, and we use the Hartwig–Spindelböck decomposition to obtain the Core inverse of the coefficient matrix
A
. The aim of this paper is twofold. First, we obtain a strong fuzzy solution of fuzzy linear systems, and a necessary and sufficient condition for the existence strong fuzzy solution of fuzzy linear systems are derived using the Core inverse of the coefficient matrix
A
. Second, general strong fuzzy solutions of fuzzy linear systems are derived, and an algorithm for obtaining general strong fuzzy solutions of fuzzy linear systems by Core inverse is also established. Finally, some examples are given to illustrate the validity of the proposed method. |
doi_str_mv | 10.1007/s40314-020-01156-0 |
format | article |
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n
×
n
real matrix, using a block structure of the Core inverse, and we use the Hartwig–Spindelböck decomposition to obtain the Core inverse of the coefficient matrix
A
. The aim of this paper is twofold. First, we obtain a strong fuzzy solution of fuzzy linear systems, and a necessary and sufficient condition for the existence strong fuzzy solution of fuzzy linear systems are derived using the Core inverse of the coefficient matrix
A
. Second, general strong fuzzy solutions of fuzzy linear systems are derived, and an algorithm for obtaining general strong fuzzy solutions of fuzzy linear systems by Core inverse is also established. Finally, some examples are given to illustrate the validity of the proposed method.</description><identifier>ISSN: 2238-3603</identifier><identifier>EISSN: 1807-0302</identifier><identifier>DOI: 10.1007/s40314-020-01156-0</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Algorithms ; Applications of Mathematics ; Applied physics ; Coefficients ; Computational mathematics ; Computational Mathematics and Numerical Analysis ; Fuzzy systems ; Generalized inverse ; Linear systems ; Mathematical analysis ; Mathematical Applications in Computer Science ; Mathematical Applications in the Physical Sciences ; Mathematics ; Mathematics and Statistics ; Matrix methods</subject><ispartof>Computational & applied mathematics, 2020-05, Vol.39 (2), Article 133</ispartof><rights>SBMAC - Sociedade Brasileira de Matemática Aplicada e Computacional 2020</rights><rights>SBMAC - Sociedade Brasileira de Matemática Aplicada e Computacional 2020.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c319t-8fddc061aefe610e3deebdd6a3369a84ea5e857807366cba4c36b1858b3765a93</citedby><cites>FETCH-LOGICAL-c319t-8fddc061aefe610e3deebdd6a3369a84ea5e857807366cba4c36b1858b3765a93</cites><orcidid>0000-0003-2569-0821</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Jiang, Hongjie</creatorcontrib><creatorcontrib>Wang, Hongxing</creatorcontrib><creatorcontrib>Liu, Xiaoji</creatorcontrib><title>Solving fuzzy linear systems by a block representation of generalized inverse: the core inverse</title><title>Computational & applied mathematics</title><addtitle>Comp. Appl. Math</addtitle><description>This paper presents a method for solving fuzzy linear systems, where the coefficient matrix is an
n
×
n
real matrix, using a block structure of the Core inverse, and we use the Hartwig–Spindelböck decomposition to obtain the Core inverse of the coefficient matrix
A
. The aim of this paper is twofold. First, we obtain a strong fuzzy solution of fuzzy linear systems, and a necessary and sufficient condition for the existence strong fuzzy solution of fuzzy linear systems are derived using the Core inverse of the coefficient matrix
A
. Second, general strong fuzzy solutions of fuzzy linear systems are derived, and an algorithm for obtaining general strong fuzzy solutions of fuzzy linear systems by Core inverse is also established. Finally, some examples are given to illustrate the validity of the proposed method.</description><subject>Algorithms</subject><subject>Applications of Mathematics</subject><subject>Applied physics</subject><subject>Coefficients</subject><subject>Computational mathematics</subject><subject>Computational Mathematics and Numerical Analysis</subject><subject>Fuzzy systems</subject><subject>Generalized inverse</subject><subject>Linear systems</subject><subject>Mathematical analysis</subject><subject>Mathematical Applications in Computer Science</subject><subject>Mathematical Applications in the Physical Sciences</subject><subject>Mathematics</subject><subject>Mathematics and Statistics</subject><subject>Matrix methods</subject><issn>2238-3603</issn><issn>1807-0302</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp9kMFKw0AQhhdRsFZfwNOC59XZTLJJvEnRKhQ8qOdlk0xqarpbd9NC-vSmRvHmaWD4v3-Yj7FLCdcSIL0JMaCMBUQgQMpECThiE5lBKgAhOmaTKMJMoAI8ZWchrAAwlXE8YfrFtbvGLnm93e973jaWjOehDx2tAy96bnjRuvKDe9p4CmQ70zXOclfzJVnypm32VPHG7sgHuuXdO_HSefrdnLOT2rSBLn7mlL093L_OHsXief40u1uIEmXeiayuqhKUNFSTkkBYERVVpQyiyk0Wk0koS9LhIVSqLExcoipklmQFpioxOU7Z1di78e5zS6HTK7f1djipI8wTlJDmMKSiMVV6F4KnWm98sza-1xL0QaQeRepBpP4WqQ8QjlAYwnZJ_q_6H-oLJkZ3ZQ</recordid><startdate>20200501</startdate><enddate>20200501</enddate><creator>Jiang, Hongjie</creator><creator>Wang, Hongxing</creator><creator>Liu, Xiaoji</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0003-2569-0821</orcidid></search><sort><creationdate>20200501</creationdate><title>Solving fuzzy linear systems by a block representation of generalized inverse: the core inverse</title><author>Jiang, Hongjie ; Wang, Hongxing ; Liu, Xiaoji</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c319t-8fddc061aefe610e3deebdd6a3369a84ea5e857807366cba4c36b1858b3765a93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Algorithms</topic><topic>Applications of Mathematics</topic><topic>Applied physics</topic><topic>Coefficients</topic><topic>Computational mathematics</topic><topic>Computational Mathematics and Numerical Analysis</topic><topic>Fuzzy systems</topic><topic>Generalized inverse</topic><topic>Linear systems</topic><topic>Mathematical analysis</topic><topic>Mathematical Applications in Computer Science</topic><topic>Mathematical Applications in the Physical Sciences</topic><topic>Mathematics</topic><topic>Mathematics and Statistics</topic><topic>Matrix methods</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Jiang, Hongjie</creatorcontrib><creatorcontrib>Wang, Hongxing</creatorcontrib><creatorcontrib>Liu, Xiaoji</creatorcontrib><collection>CrossRef</collection><jtitle>Computational & applied mathematics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Jiang, Hongjie</au><au>Wang, Hongxing</au><au>Liu, Xiaoji</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Solving fuzzy linear systems by a block representation of generalized inverse: the core inverse</atitle><jtitle>Computational & applied mathematics</jtitle><stitle>Comp. Appl. Math</stitle><date>2020-05-01</date><risdate>2020</risdate><volume>39</volume><issue>2</issue><artnum>133</artnum><issn>2238-3603</issn><eissn>1807-0302</eissn><abstract>This paper presents a method for solving fuzzy linear systems, where the coefficient matrix is an
n
×
n
real matrix, using a block structure of the Core inverse, and we use the Hartwig–Spindelböck decomposition to obtain the Core inverse of the coefficient matrix
A
. The aim of this paper is twofold. First, we obtain a strong fuzzy solution of fuzzy linear systems, and a necessary and sufficient condition for the existence strong fuzzy solution of fuzzy linear systems are derived using the Core inverse of the coefficient matrix
A
. Second, general strong fuzzy solutions of fuzzy linear systems are derived, and an algorithm for obtaining general strong fuzzy solutions of fuzzy linear systems by Core inverse is also established. Finally, some examples are given to illustrate the validity of the proposed method.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><doi>10.1007/s40314-020-01156-0</doi><orcidid>https://orcid.org/0000-0003-2569-0821</orcidid></addata></record> |
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source | Springer Nature |
subjects | Algorithms Applications of Mathematics Applied physics Coefficients Computational mathematics Computational Mathematics and Numerical Analysis Fuzzy systems Generalized inverse Linear systems Mathematical analysis Mathematical Applications in Computer Science Mathematical Applications in the Physical Sciences Mathematics Mathematics and Statistics Matrix methods |
title | Solving fuzzy linear systems by a block representation of generalized inverse: the core inverse |
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