Skip to content
Free planNo credit card requiredStart writing
AI for Research home
AI for Research home
Dashboard
Sign inGet started

preprint · arXiv (Cornell University) · 2021

Binary code optimization

Parviz Gharehbagheri, Sayeed Hamid Haji Sayeed Javadi, Parvaneh Asghari, Naser Gharehbagheri

Cited by 0Open access

Abstract

This article shows that any type of binary data can be defined as a collection from codewords of variable length. This feature helps us to define an Injective and surjective function from the suggested codewords to the required codewords. Therefore, by replacing the new codewords, the binary data becomes another binary data regarding the intended goals. One of these goals is to reduce data size. It means that instead of the original codewords of each binary data, it replaced the Huffman codewords to reduce the data size. One of the features of this method is the result of positive compression for any type of binary data, that is, regardless of the size of the code table, the difference between the original data size and the data size after compression will be greater than or equal to zero. Another important and practical feature of this method is the use of symmetric codewords instead of the suggested codewords in order to create symmetry, reversibility and error resistance properties with two-way decoding.

Cite this paper

APA 7

Gharehbagheri, P., Javadi, S. H. H. S., Asghari, P., & Gharehbagheri, N. (2021). Binary code optimization. arXiv (Cornell University). https://doi.org/10.48550/arxiv.2110.00917

MLA 9

Gharehbagheri, Parviz, et al. “Binary code optimization.” arXiv (Cornell University), 2021, https://doi.org/10.48550/arxiv.2110.00917.

Chicago

Gharehbagheri, Parviz, Sayeed Hamid Haji Sayeed Javadi, Parvaneh Asghari, and Naser Gharehbagheri. 2021. “Binary code optimization.” arXiv (Cornell University). https://doi.org/10.48550/arxiv.2110.00917.

Harvard

Gharehbagheri, P. et al. (2021) ‘Binary code optimization’, arXiv (Cornell University). Available at: https://doi.org/10.48550/arxiv.2110.00917.

BibTeX
@misc{gharehbagheri2021binary,
  title = {{Binary code optimization}},
  author = {Gharehbagheri, Parviz and Javadi, Sayeed Hamid Haji Sayeed and Asghari, Parvaneh and Gharehbagheri, Naser},
  journal = {arXiv (Cornell University)},
  year = {2021},
  doi = {10.48550/arxiv.2110.00917}
}

Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.

Related papers