| 引用本文: | 陈英武,谭跃进,汪浩.基于神经元的动态系统模糊关系模型及其学习算法.[J].国防科技大学学报,1997,19(4):66-71.[点击复制] |
| Chen Yingwu,Tang Yuejin,Wang Hao.A Neuron-Inspired Fuzzy Relation Model of Dynamic System And Its Learning Algorithms[J].Journal of National University of Defense Technology,1997,19(4):66-71[点击复制] |
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| 基于神经元的动态系统模糊关系模型及其学习算法 |
| 陈英武, 谭跃进, 汪浩 |
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(国防科技大学 系统工程与数学系 湖南 长沙 410073)
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| 摘要: |
| 本文直接针对模糊集, 提出了三种基于模糊集运算的逻辑神经元, 即AND. OR和AND/DR. 基于上述神经元, 提出了一种应用于动态系统建模的实用的模糊关系网络模型, 通过一个简单实例, 证实了上述模型建模算法的学习能力和快速计算能力。 |
| 关键词: 模糊神经元, 动态系统, 建模 |
| DOI： |
| 投稿日期：1996-09-16 |
| 基金项目:国防科技预研基金, 国防科技大学青年基金资助项目 |
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| A Neuron-Inspired Fuzzy Relation Model of Dynamic System And Its Learning Algorithms |
| Chen Yingwu, Tang Yuejin, Wang Hao |
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(Department of Systems Engineering and Methematics National University of Defense Technology, Changsha, Hunan, 410073)
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| Abstract: |
| In view of fuzzy sets and their operations, three kinds of logical neurons, i, e. , AND, OR and AND/OR neurons can be chassified into two types: weighted and relational. Using AND, OR and AND/OR neurons, a fuzzy relational model for dynamic system modeling is provided as well as its learning algorithms. By a simple example, the soundness and learning capability of the algorithms are verified. |
| Keywords: Fuzzy Neurons, Dynamic System, Learning Algorithm, Modeling |
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