Bridging Gauss-Jordan Reduction and Determinant Methods Through Cross-Multiplication-Flip (CMF) Method in Matrix Inversion and Solving Systems of Linear Equations

preprint OA: closed CC-BY-4.0
🔓 Open OA copy View at publisher
AI-generated summary by claude@2026-07, 2026-07-17

This paper presents a new Cross-Multiplication-Flip (CMF) algorithm for matrix inversion and solving linear equations by combining Gauss-Jordan reduction with determinant calculation methods.

One-sentence paraphrase of the abstract; not a substitute for reading it. No clinical advice. How this works

Abstract

In this paper, we introduce as a pedagogical strategy an internal division-free, straightforward, and symmetrically progressing algorithm in manually computing matrix inverse and solving systems of linear equations by revisiting the application of elementary row operations in the Gauss-Jordan reduction method and connecting it to the determinant method. The proposed cross-multiplication-flip (CMF) algorithm employs cross-multiplication similar to the butterfly movement in computing determinants as a strategic application of elementary row operations to efficiently reduce the rows and then applies flipping of rows and entries to put an upper triangular matrix into lower triangular form to continue the reduction process.

My notes (saved in your browser only)

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. The paper's references may be in our DB but unresolved to ``paper_id`` (resolution happens at ingest when the cited DOI matches a row we already have). Run the cross-source citation reconcile pass to retry.

Source provenance

europepmc
last seen: 2026-05-19T01:45:01.086888+00:00
unpaywall
last seen: 2026-06-02T02:00:03.124865+00:00
License: CC-BY-4.0