Abdullah A. Hussain CODE DENSITY OPTOMIZATION AND IMPLEMENTATION USING LZW APPROACH BASED ON 32-BIT RISC PROCESSOR

Considering the worldwide used of mobile to connect internet, and code compression technology that played significant role in saving space and power. Our study is focusing on how many items will be stored in the dictionary and how many bits long for every item, which will determine the optimum dic...

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Main Author: Abdullah Hussain
Format: Article
Language:English
Published: University of Thi-Qar 2019-05-01
Series:مجلة علوم ذي قار
Subjects:
Online Access:https://jsci.utq.edu.iq/index.php/main/article/view/404
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author Abdullah Hussain
author_facet Abdullah Hussain
author_sort Abdullah Hussain
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description Considering the worldwide used of mobile to connect internet, and code compression technology that played significant role in saving space and power. Our study is focusing on how many items will be stored in the dictionary and how many bits long for every item, which will determine the optimum dictionary size to the compression process .  Focusing on the dictionary size, one can gain the key for improving the compression ratio on interesting Benchmark. The results will hold on variant size of Benchmarks to investigate the proper dictionary size for variant cases. The average result of compression ratio was 62.34% for a dictionary with 9 bits code and 256 items, where the maximum value of compression ratio was 72.89%.  If we use another dictionary with more than 10 bits, the compression ratio will vary a little.
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spelling doaj.art-0412208f731d45ad9c170c22b1af8f312023-11-14T08:11:03ZengUniversity of Thi-Qarمجلة علوم ذي قار1991-86902709-02562019-05-0121Abdullah A. Hussain CODE DENSITY OPTOMIZATION AND IMPLEMENTATION USING LZW APPROACH BASED ON 32-BIT RISC PROCESSORAbdullah Hussain Considering the worldwide used of mobile to connect internet, and code compression technology that played significant role in saving space and power. Our study is focusing on how many items will be stored in the dictionary and how many bits long for every item, which will determine the optimum dictionary size to the compression process .  Focusing on the dictionary size, one can gain the key for improving the compression ratio on interesting Benchmark. The results will hold on variant size of Benchmarks to investigate the proper dictionary size for variant cases. The average result of compression ratio was 62.34% for a dictionary with 9 bits code and 256 items, where the maximum value of compression ratio was 72.89%.  If we use another dictionary with more than 10 bits, the compression ratio will vary a little. https://jsci.utq.edu.iq/index.php/main/article/view/404Mobile communication, Code Density, Compression Technology, Dictionary Optimization, Decompression unit, hardware implementation.
spellingShingle Abdullah Hussain
Abdullah A. Hussain CODE DENSITY OPTOMIZATION AND IMPLEMENTATION USING LZW APPROACH BASED ON 32-BIT RISC PROCESSOR
مجلة علوم ذي قار
Mobile communication, Code Density, Compression Technology, Dictionary Optimization, Decompression unit, hardware implementation.
title Abdullah A. Hussain CODE DENSITY OPTOMIZATION AND IMPLEMENTATION USING LZW APPROACH BASED ON 32-BIT RISC PROCESSOR
title_full Abdullah A. Hussain CODE DENSITY OPTOMIZATION AND IMPLEMENTATION USING LZW APPROACH BASED ON 32-BIT RISC PROCESSOR
title_fullStr Abdullah A. Hussain CODE DENSITY OPTOMIZATION AND IMPLEMENTATION USING LZW APPROACH BASED ON 32-BIT RISC PROCESSOR
title_full_unstemmed Abdullah A. Hussain CODE DENSITY OPTOMIZATION AND IMPLEMENTATION USING LZW APPROACH BASED ON 32-BIT RISC PROCESSOR
title_short Abdullah A. Hussain CODE DENSITY OPTOMIZATION AND IMPLEMENTATION USING LZW APPROACH BASED ON 32-BIT RISC PROCESSOR
title_sort abdullah a hussain code density optomization and implementation using lzw approach based on 32 bit risc processor
topic Mobile communication, Code Density, Compression Technology, Dictionary Optimization, Decompression unit, hardware implementation.
url https://jsci.utq.edu.iq/index.php/main/article/view/404
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