| Quantitative information measurement and application for machine component classification codes |
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| 作者姓名： | 李凌丰 谭建荣 刘波 |
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| 作者单位： | State Kev Laboratory of CAD＆CG Zhejiang University Hangzhou 310027, China |
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| 基金项目： | Projects supported by the Hi-Tech Research and Development Program （863） of China （No. 2004AA84ts03） and the Science and Technology Committee of Zhejiang Province （No. 2004C31018）, China |
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| 摘 要： | Information embodied in machine component classification codes has internal relation with the probability distribution of the code symbol. This paper presents a model considering codes as information source based on Shannon＇s information theory. Using information entropy, it preserves the mathematical form and quantitatively measures the information amount of a symbol and a bit in the machine component classification coding system. It also gets the maximum value of information amount and the corresponding coding scheme when the category of symbols is fixed. Samples are given to show how to evaluate the information amount of component codes and how to optimize a coding system.
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| 关 键 词： | 成分分类代码 信息来源 熵 信息数量 计算机集成制造 |
| 收稿时间： | 2004-02-10 |
| 修稿时间： | 2004-08-10 |
Quantitative information measurement and application for machine component classification codes |
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| Li LingFeng;Tan JianRong;Liu Bo.Quantitative information measurement and application for machine component classification codes[J].Journal of Zhejiang University Science,2005,6(B08):35-40. |
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| Authors: | Li LingFeng;Tan JianRong;Liu Bo |
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| Abstract: | |
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| Keywords: | Component classification codes Information source Information amount Information entropy of code bit |
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