A. Kh. Al-Eidane, H., A. Hussain, A. (2010). CODE DENSITY OPTOMIZATION AND IMPLEMENTATIONUSING LZW APPROACH BASED ON 32-BIT RISC PROCESSOR. , 2(1), 105-116.
Hussein A. Kh. Al-Eidane; Abdullah A. Hussain. "CODE DENSITY OPTOMIZATION AND IMPLEMENTATIONUSING LZW APPROACH BASED ON 32-BIT RISC PROCESSOR". , 2, 1, 2010, 105-116.
A. Kh. Al-Eidane, H., A. Hussain, A. (2010). 'CODE DENSITY OPTOMIZATION AND IMPLEMENTATIONUSING LZW APPROACH BASED ON 32-BIT RISC PROCESSOR', , 2(1), pp. 105-116.
A. Kh. Al-Eidane, H., A. Hussain, A. CODE DENSITY OPTOMIZATION AND IMPLEMENTATIONUSING LZW APPROACH BASED ON 32-BIT RISC PROCESSOR. , 2010; 2(1): 105-116.

CODE DENSITY OPTOMIZATION AND IMPLEMENTATIONUSING LZW APPROACH BASED ON 32-BIT RISC PROCESSOR

JOURNAL OF THI-QAR SCIENCE
Article 1, Volume 2, Issue 1, 2011, Pages 105-116
Authors
Hussein A. Kh. Al-Eidane; Abdullah A. Hussain
Abstract
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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