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A novel fuzzy neural network and its approximation capability

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【作者】 刘普寅

【Author】 LIU PuyinDepartment of Mathematics, Beijing Normal University, Beijing 100875, China

【摘要】 <正>The polygonal fuzzy numbers are employed to define a new fuzzy arithmetic. A novel ex-tension principle is also introduced for the increasing function σ:R→R. Thus it is convenient to con-struct a fuzzy neural network model with succinct learning algorithms. Such a system possesses some universal approximation capabilities, that is, the corresponding three layer feedforward fuzzy neural networks can be universal approximators to the continuously increasing fuzzy functions.

【Abstract】 The polygonal fuzzy numbers are employed to define a new fuzzy arithmetic. A novel ex-tension principle is also introduced for the increasing function σ:R→R. Thus it is convenient to con-struct a fuzzy neural network model with succinct learning algorithms. Such a system possesses some universal approximation capabilities, that is, the corresponding three layer feedforward fuzzy neural networks can be universal approximators to the continuously increasing fuzzy functions.

【基金】 The author would like to thank Professor H. Wang for helpful suggestions; This work was supported by the National Natural Science Foundation of China( Grants Nos. 69974006 and 69974041) .
  • 【文献出处】 Science in China(Series F:Information Sciences) ,中国科学(F辑:信息科学)(英文版) , 编辑部邮箱 ,2001年03期
  • 【分类号】TP183
  • 【被引频次】4
  • 【下载频次】89
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