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On-line Access: 2024-08-27
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Quantitative information measurement and application for machine component classification codes
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LI Ling-Feng, TAN Jian-rong, LIU Bo. Quantitative information measurement and application for machine component classification codes[J]. Journal of Zhejiang University Science A, 2005, 6(100): 35-40.
@article{title="Quantitative information measurement and application for machine component classification codes",
author="LI Ling-Feng, TAN Jian-rong, LIU Bo",
journal="Journal of Zhejiang University Science A",
volume="6",
number="100",
pages="35-40",
year="2005",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2005.AS0035"
}
%0 Journal Article
%T Quantitative information measurement and application for machine component classification codes
%A LI Ling-Feng
%A TAN Jian-rong
%A LIU Bo
%J Journal of Zhejiang University SCIENCE A
%V 6
%N 100
%P 35-40
%@ 1673-565X
%D 2005
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2005.AS0035
TY - JOUR
T1 - Quantitative information measurement and application for machine component classification codes
A1 - LI Ling-Feng
A1 - TAN Jian-rong
A1 - LIU Bo
J0 - Journal of Zhejiang University Science A
VL - 6
IS - 100
SP - 35
EP - 40
%@ 1673-565X
Y1 - 2005
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2005.AS0035
Abstract: 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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