| Fuzzy Entropy： Axiomatic Definition and Neural Networks Model |
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| 引用本文： | QING Ming,CAO Yue,HUANG Tian-min(Department of Mathematics,Southwest Jiaotong University,Chengdu 610031,China,Zhengzhou Teacher's College,Zhengzhou 450044,China). Fuzzy Entropy： Axiomatic Definition and Neural Networks Model[J]. 数学季刊, 2004, 19(3): 319-323 |
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| 作者姓名： | QING Ming CAO Yue HUANG Tian-min(Department of Mathematics Southwest Jiaotong University Chengdu 610031 China Zhengzhou Teacher's College Zhengzhou 450044 China) |
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| 作者单位： | [1]DepartmentofMathematics,SouthwestJiaotongUniversity,Chengdu610031,China [2]ZhengzhouTeacher＇sCollege,Zhengzhou450044,China |
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| 基金项目： | Supported by the National Natural Science Foundation of China(60074014) |
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| 摘 要： | The measure of uncertainty is adopted as a measure of information. The measures of fuzziness are known as fuzzy information measures. The measure of a quantity of fuzzy information gained from a fuzzy set or fuzzy system is known as fuzzy entropy. Fuzzy entropy has been focused and studied by many researchers in various fields. In this paper, firstly, the axiomatic definition of fuzzy entropy is discussed. Then, neural networks model of fuzzy entropy is proposed, based on the computing capability of neural networks. In the end, two examples are discussed to show the efficiency of the model.
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| 关 键 词： | 模式识别论 神经网络 精度 模糊熵 |
Fuzzy Entropy: Axiomatic Definition and Neural Networks Model |
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| QINGMing CAOYue HUANGTian-min. Fuzzy Entropy: Axiomatic Definition and Neural Networks Model[J]. Chinese Quarterly Journal of Mathematics, 2004, 19(3): 319-323 |
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| Authors: | QINGMing CAOYue HUANGTian-min |
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| Abstract: | The measure of uncertainty is adopted as a measure of information. The measures of fuzziness are known as fuzzy information measures. The measure of a quantity of fuzzy information gained from a fuzzy set or fuzzy system is known as fuzzy entropy. Fuzzy entropy has been focused and studied by many researchers in various fields. In this paper, firstly, the axiomatic definition of fuzzy entropy is discussed. Then, neural networks model of fuzzy entropy is proposed, based on the computing capability of neural networks. In the end, two examples are discussed to show the efficiency of the model. |
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| Keywords: | neural networks BP networks fuzzy entropy fuzzy set model |
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