The Moore-Penrose Inverse Matrix of the Non-Normal Cyclic Subgroup Graph by Using Rank Factorization

Authors

  • Nabilah Fikriah Rahin Department of Mathematics, Centre for Foundation Defence Studies, National Defence University of Malaysia, MALAYSIA
  • Nor Haniza Sarmin Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, MALAYSIA
  • Sheila Ilangovan School of Information and Technology, Monash University Malaysia, MALAYSIA
  • Ahmad Erfanian Department of Pure Mathematics and Center of Excellence in Analysis on Algebraic Structures, Ferdowsi University of Mashhad, IRAN

DOI:

https://doi.org/10.17576/jqma.2203.2026.01

Keywords:

Moore-Penrose inverse matrix, subgroup graph, non-normal subgroup

Abstract

The inverse matrix can be determined for any non-singular or square matrix and it is particularly useful in solving linear systems. At the same time, the Moore-Penrose inverse matrix is an inverse matrix for any rectangular matrix constructed when the linear system has more unknowns than the number of values provided by the measurements. In previous studies, this inverse matrix has been applied to some graphs unrelated to finite groups. The main objective of this paper is to determine the Moore-Penrose inverse matrix in general form for the non-normal cyclic subgroup graph of two finite groups, namely the dihedral groups and the generalized quaternion groups. The digraph for these two finite groups represented by the incidence matrix is then applied to generate the Moore-Penrose inverse matrix using the rank factorization method. It is useful when the matrix is not of full rank. The Moore-Penrose inverse matrices are given in the form of matrix size, and the entries of the matrices are block matrices, as the digraph is disconnected and the incidence matrix is not unique.

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Published

26-09-2026

How to Cite

Rahin, N. F., Sarmin, N. H., Ilangovan, S., & Erfanian, A. (2026). The Moore-Penrose Inverse Matrix of the Non-Normal Cyclic Subgroup Graph by Using Rank Factorization. Journal of Quality Measurement and Analysis, 22(3), 1–18. https://doi.org/10.17576/jqma.2203.2026.01

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