Epsilon: Jurnal Matematika Murni dan Terapan
Vol. 15(2), 2021

INVERS TERGENERALISASI MOORE PENROSE

Mardiyana Mardiyana (Program Studi Matematika FMIPA Universitas Lambung Mangkurat)
Na'imah Hijriati (Program Studi Matematika FMIPA Universitas Lambung Mangkurat)
Thresye Thresye (Unknown)



Article Info

Publish Date
28 Jan 2022

Abstract

The generalized inverse is a concept for determining the inverse of a singular matrix and and  matrix which has the characteristic of the inverse matrix. There are several types of generalized inverse, one of which is the Moore-Penrose inverse. The matrix  is called Moore Penrose inverse of a matrix if it satisfies the four penrose equations and is denoted by . Furthermore, if the matrix  satisfies only the first two equations of the Moore-Penrose inverse and , then  is called the group inverse of  and is denoted by . The purpose of this research was to determine the group inverse of a non-diagonalizable square matrix using Jordan’s canonical form and Moore Penrose’s inverse of a singular matrix, also a non-square matrix using the Singular Value Decomposition (SVD) method. The results of this study are the sufficient condition for a matrix  to have a group inverse, i.e., a matrix  has an index of 1 if and only if the product of two matrices forming  is a full rank factorization and is invertible. Whereas for a singular matrix  and a non-square , the Moore-Penrose inverse can be determined using Singular Value Decomposition (SVD).                                                           Keywords: generalized matrix inverse, Moore Penrose inverse, group inverse, Jordan canonical form, Singular Value Decomposition.

Copyrights © 2021






Journal Info

Abbrev

epsilon

Publisher

Subject

Decision Sciences, Operations Research & Management Transportation

Description

Jurnal Matematika Murni dan Terapan Epsilon is a mathematics journal which is devoted to research articles from all fields of pure and applied mathematics including 1. Mathematical Analysis 2. Applied Mathematics 3. Algebra 4. Statistics 5. Computational ...