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    Abstract
2017 (Vol. 14, Issue: 8)
Research Article

A Novel Compressing a Sparse Matrix using Folding Technique

Ashwak Alabaichi, Amjad Hamead Alhusiny and Elham Mohammed Thabit
Computer Department, Sciences Collage, Kerbala University, Karbala, Iraq
 

DOI: 10.19026/rjaset.14.4955
Submitted Accepted Published
April 20, 2017 May 23, 2017 August 15, 2017

  How to Cite this Article:

Ashwak Alabaichi, Amjad Hamead Alhusiny and Elham Mohammed Thabit, 2017. A Novel Compressing a Sparse Matrix using Folding Technique.  Research Journal of Applied Sciences, Engineering and Technology, 14(8): 310-319.

DOI: 10.19026/rjaset.14.4955

URL: http://www.maxwellsci.com/jp/mspabstract.php?jid=RJASET&doi=rjaset.14.4955

Abstract:


There are many application problems that emerge in the areas of engineering simulations, scientific computing, information retrieval and economics which use matrixes where non-zero elements are a significant minority with less than 10%. These are universal in many mathematical and scientific applications. These matrixes enable the reduction of storage and computational requirements by storing and carrying out arithmetic with, only the non-zero elements. This is the sparse matrix which must be compressed for these applications. The sparse matrix compression represents non-zero matrix entries. This study presents a novel algorithm for compressing a sparse matrix, which involves three steps. Firstly it involves the division of sparse matrix into sub-matrixes; secondly conducting several transformations; finally coding them. The novel algorithm is called folding. The compressed matrix reduces memory requirement with a good rate compared with the original sparse matrix. C++ is used in the implementation of this algorithm.

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    Competing interests

The authors have no competing interests.
    Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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© The Author(s) 2017

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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