Research Article
Convolution Factorization Method in Graph Theory
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 187 - Issue 146 |
| Published: October 2026 |
| Authors: Bal Govind Shukla |
10.5120/ijcab16c56d4e4ad
|
Bal Govind Shukla . Convolution Factorization Method in Graph Theory. International Journal of Computer Applications. 187, 146 (October 2026), 10-13. DOI=10.5120/ijcab16c56d4e4ad
@article{ 10.5120/ijcab16c56d4e4ad,
author = { Bal Govind Shukla },
title = { Convolution Factorization Method in Graph Theory },
journal = { International Journal of Computer Applications },
year = { 2026 },
volume = { 187 },
number = { 146 },
pages = { 10-13 },
doi = { 10.5120/ijcab16c56d4e4ad },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2026
%A Bal Govind Shukla
%T Convolution Factorization Method in Graph Theory%T
%J International Journal of Computer Applications
%V 187
%N 146
%P 10-13
%R 10.5120/ijcab16c56d4e4ad
%I Foundation of Computer Science (FCS), NY, USA
Abstract
In this work we investigate the relationship between complete bipartite graph theory and the convolution factorization method, with an emphasis on the applications of convolution-based methods to graph factorization, coloring, and edge distribution problems. Although convolution factorization is primarily utilized in mathematical analysis and signal processing, its concepts can also be applied to graph theory, especially when breaking down and examining entire bipartite graphs. This paper presents a comprehensive mathematical model that illustrates how graph-theoretical ideas can be handled using convolution techniques, with particular emphasis on applications such as network flow analysis, r-factorizations, and perfect matchings.
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