通过最小加代数确定矩阵的逆值

Siswanto Siswanto, A. Gusmizain
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引用次数: 0

摘要

具有⊗(加)和⨁(最大)运算的 R_ε 上的线性代数,称为 max-plus 代数。与此代数同构的代数之一是最小加代数。最小加代数即集合 R_(ε^')=R∪{ε'},其中有⊗^'(加)和⨁'(最小)运算。给定一个矩阵,其分量是 R_(ε^' ) 的元素,称为最小加代数矩阵。任何矩阵都可以通过逆矩阵连接。在传统代数中,如果〖det〗(A)≠0,则称一个正方形矩阵为可逆矩阵。与 max-plus 代数相反,如果矩阵满足某些条件,则称其具有逆条件。由于结构相似,max-plus 代数中的一些概念可以转换到 min-plus 中。这意味着 max-plus 中的逆矩阵概念可以构造成 min-plus 版本。因此,本研究将采用文献研究法,通过书籍、期刊、文章和论文等文献来源,解释在 min-plus 代数上的矩阵逆、两个可逆矩阵相乘的性质以及可逆矩阵与线性映射之间的联系。本研究采用的数据分析技术是定性数据分析技术。然后,本文有一个主要结果,即矩阵 A∈R_(ε^')^(n×n) 有一个右逆,当且仅当存在 σ 的排列且 λ_i 的值<ε',i∈{1,2,3,......,n},使得 A=P_σ ⊗^'D(λ_i ) 是矩阵的逆。此外,如果 B 是正确的逆矩阵,满足 A⊗^'B=E 那么 B⊗^'A=E 且 B 由 A 唯一决定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Determining the Inverse of a Matrix over Min-Plus Algebra
Linear algebra over the semiring  R_ε with ⊗ (plus) and ⨁ (maximum) operations which is known as max-plus algebra. One of the isomorphic with this algebra is a min-plus algebra. Min-plus algebra that is the set R_(ε^' )=R∪{ε'}, with ⊗^' (plus) and ⨁' (minimum) operations. Given a matrix whose components are elements of R_(ε^' )  is called min-plus algebra matrices. Any matrix can be connected by an inverse. In conventional algebra, a square matrix is said an invertible matrix if the det⁡〖(A)〗≠0. In contrast to max-plus algebra, a matrix is said to have inverse condition if it meets certain conditions. Some concepts from the max-plus algebra can be transformed to the min-plus, because of their structural similarity. This means that the inverse matrix concept in max-plus can be constructed into a min-plus version. Thus, this study will explain the inverse of a matrix over the min-plus algebra, property of multiplying two invertible matrices, and connection between invertible matrix and linear mapping used the literature study method, with literature sources such as books, journals, articles, and theses. The data analysis technique used in this research is qualitative data analysis technique. Then, this article has a principal result that is matrix A∈R_(ε^')^(n×n) has a right inverse if and only if there are permutations of σ and the value of λ_i<ε', i∈{1,2,3,…,n} such that A=P_σ ⊗^' D(λ_i ) which is the inverse of matrices. Furthermore, if B is the correct inverse that satisfies A⊗^' B=E then B⊗^' A=E and B is uniquely determined by A.
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