中心原理子矩阵约束下的 IEVP 解矩阵

IF 1.3 4区 数学 Q1 MATHEMATICS Journal of Mathematics Pub Date : 2024-05-06 DOI:10.1155/2024/7908231
Vineet Bhatt, Manpreet Kaur, I. Ahmed M. AL-Hammadi, Sunil Kumar
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AL-Hammadi, Sunil Kumar","doi":"10.1155/2024/7908231","DOIUrl":null,"url":null,"abstract":"The <span><svg height=\"7.35473pt\" style=\"vertical-align:-0.3499303pt\" version=\"1.1\" viewbox=\"-0.0498162 -7.0048 17.063 7.35473\" width=\"17.063pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g transform=\"matrix(.013,0,0,-0.013,0,0)\"></path></g><g transform=\"matrix(.013,0,0,-0.013,9.432,0)\"></path></g></svg><span></span><svg height=\"7.35473pt\" style=\"vertical-align:-0.3499303pt\" version=\"1.1\" viewbox=\"19.9181838 -7.0048 6.703 7.35473\" width=\"6.703pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g transform=\"matrix(.013,0,0,-0.013,19.968,0)\"><use xlink:href=\"#g113-111\"></use></g></svg></span> real matrix <svg height=\"8.68572pt\" style=\"vertical-align:-0.0498209pt\" version=\"1.1\" viewbox=\"-0.0498162 -8.6359 8.15071 8.68572\" width=\"8.15071pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g transform=\"matrix(.013,0,0,-0.013,0,0)\"></path></g></svg> is called centrosymmetric matrix if <span><svg height=\"10.2124pt\" style=\"vertical-align:-1.576501pt\" version=\"1.1\" viewbox=\"-0.0498162 -8.6359 19.289 10.2124\" width=\"19.289pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g transform=\"matrix(.013,0,0,-0.013,0,0)\"><use xlink:href=\"#g113-81\"></use></g><g transform=\"matrix(.013,0,0,-0.013,11.658,0)\"></path></g></svg><span></span><svg height=\"10.2124pt\" style=\"vertical-align:-1.576501pt\" version=\"1.1\" viewbox=\"22.8711838 -8.6359 26.759 10.2124\" width=\"26.759pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g transform=\"matrix(.013,0,0,-0.013,22.921,0)\"></path></g><g transform=\"matrix(.013,0,0,-0.013,31.072,0)\"><use xlink:href=\"#g113-81\"></use></g><g transform=\"matrix(.013,0,0,-0.013,38.315,0)\"><use xlink:href=\"#g113-83\"></use></g><g transform=\"matrix(.013,0,0,-0.013,46.466,0)\"></path></g></svg><span></span></span> where <svg height=\"8.8423pt\" style=\"vertical-align:-0.2064009pt\" version=\"1.1\" viewbox=\"-0.0498162 -8.6359 8.28119 8.8423\" width=\"8.28119pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g transform=\"matrix(.013,0,0,-0.013,0,0)\"><use xlink:href=\"#g113-83\"></use></g></svg> is permutation matrix with ones on cross diagonal (bottom left to top right) and zeroes elsewhere. In this article, the solvability conditions for left and right inverse eigenvalue problem (which is special case of inverse eigenvalue problem) under the submatrix constraint for generalized centrosymmetric matrices are derived, and the general solution is also given. In addition, we provide a feasible algorithm for computing the general solution, which is proved by a numerical example.","PeriodicalId":54214,"journal":{"name":"Journal of Mathematics","volume":"24 1","pages":""},"PeriodicalIF":1.3000,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Solution Matrix by IEVP under the Central Principle Submatrix Constraints\",\"authors\":\"Vineet Bhatt, Manpreet Kaur, I. Ahmed M. AL-Hammadi, Sunil Kumar\",\"doi\":\"10.1155/2024/7908231\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The <span><svg height=\\\"7.35473pt\\\" style=\\\"vertical-align:-0.3499303pt\\\" version=\\\"1.1\\\" viewbox=\\\"-0.0498162 -7.0048 17.063 7.35473\\\" width=\\\"17.063pt\\\" xmlns=\\\"http://www.w3.org/2000/svg\\\" xmlns:xlink=\\\"http://www.w3.org/1999/xlink\\\"><g transform=\\\"matrix(.013,0,0,-0.013,0,0)\\\"></path></g><g transform=\\\"matrix(.013,0,0,-0.013,9.432,0)\\\"></path></g></svg><span></span><svg height=\\\"7.35473pt\\\" style=\\\"vertical-align:-0.3499303pt\\\" version=\\\"1.1\\\" viewbox=\\\"19.9181838 -7.0048 6.703 7.35473\\\" width=\\\"6.703pt\\\" xmlns=\\\"http://www.w3.org/2000/svg\\\" xmlns:xlink=\\\"http://www.w3.org/1999/xlink\\\"><g transform=\\\"matrix(.013,0,0,-0.013,19.968,0)\\\"><use xlink:href=\\\"#g113-111\\\"></use></g></svg></span> real matrix <svg height=\\\"8.68572pt\\\" style=\\\"vertical-align:-0.0498209pt\\\" version=\\\"1.1\\\" viewbox=\\\"-0.0498162 -8.6359 8.15071 8.68572\\\" width=\\\"8.15071pt\\\" xmlns=\\\"http://www.w3.org/2000/svg\\\" xmlns:xlink=\\\"http://www.w3.org/1999/xlink\\\"><g transform=\\\"matrix(.013,0,0,-0.013,0,0)\\\"></path></g></svg> is called centrosymmetric matrix if <span><svg height=\\\"10.2124pt\\\" style=\\\"vertical-align:-1.576501pt\\\" version=\\\"1.1\\\" viewbox=\\\"-0.0498162 -8.6359 19.289 10.2124\\\" width=\\\"19.289pt\\\" xmlns=\\\"http://www.w3.org/2000/svg\\\" xmlns:xlink=\\\"http://www.w3.org/1999/xlink\\\"><g transform=\\\"matrix(.013,0,0,-0.013,0,0)\\\"><use xlink:href=\\\"#g113-81\\\"></use></g><g transform=\\\"matrix(.013,0,0,-0.013,11.658,0)\\\"></path></g></svg><span></span><svg height=\\\"10.2124pt\\\" style=\\\"vertical-align:-1.576501pt\\\" version=\\\"1.1\\\" viewbox=\\\"22.8711838 -8.6359 26.759 10.2124\\\" width=\\\"26.759pt\\\" xmlns=\\\"http://www.w3.org/2000/svg\\\" xmlns:xlink=\\\"http://www.w3.org/1999/xlink\\\"><g transform=\\\"matrix(.013,0,0,-0.013,22.921,0)\\\"></path></g><g transform=\\\"matrix(.013,0,0,-0.013,31.072,0)\\\"><use xlink:href=\\\"#g113-81\\\"></use></g><g transform=\\\"matrix(.013,0,0,-0.013,38.315,0)\\\"><use xlink:href=\\\"#g113-83\\\"></use></g><g transform=\\\"matrix(.013,0,0,-0.013,46.466,0)\\\"></path></g></svg><span></span></span> where <svg height=\\\"8.8423pt\\\" style=\\\"vertical-align:-0.2064009pt\\\" version=\\\"1.1\\\" viewbox=\\\"-0.0498162 -8.6359 8.28119 8.8423\\\" width=\\\"8.28119pt\\\" xmlns=\\\"http://www.w3.org/2000/svg\\\" xmlns:xlink=\\\"http://www.w3.org/1999/xlink\\\"><g transform=\\\"matrix(.013,0,0,-0.013,0,0)\\\"><use xlink:href=\\\"#g113-83\\\"></use></g></svg> is permutation matrix with ones on cross diagonal (bottom left to top right) and zeroes elsewhere. In this article, the solvability conditions for left and right inverse eigenvalue problem (which is special case of inverse eigenvalue problem) under the submatrix constraint for generalized centrosymmetric matrices are derived, and the general solution is also given. 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引用次数: 0

摘要

如果实矩阵的对角线(从左下角到右上角)上为 1,其他地方为 0,则该矩阵称为中心对称矩阵。本文推导了广义中心对称矩阵在子矩阵约束下左右逆特征值问题(逆特征值问题的特例)的可解条件,并给出了通解。此外,我们还提供了计算一般解的可行算法,并通过一个数值示例加以证明。
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A Solution Matrix by IEVP under the Central Principle Submatrix Constraints
The real matrix is called centrosymmetric matrix if where is permutation matrix with ones on cross diagonal (bottom left to top right) and zeroes elsewhere. In this article, the solvability conditions for left and right inverse eigenvalue problem (which is special case of inverse eigenvalue problem) under the submatrix constraint for generalized centrosymmetric matrices are derived, and the general solution is also given. In addition, we provide a feasible algorithm for computing the general solution, which is proved by a numerical example.
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来源期刊
Journal of Mathematics
Journal of Mathematics Mathematics-General Mathematics
CiteScore
2.50
自引率
14.30%
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0
期刊介绍: Journal of Mathematics is a broad scope journal that publishes original research articles as well as review articles on all aspects of both pure and applied mathematics. As well as original research, Journal of Mathematics also publishes focused review articles that assess the state of the art, and identify upcoming challenges and promising solutions for the community.
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