一类模糊神经网络的函数逼近能力
The Approximation Ability of Fuzzy Neural Networks
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摘要: 根据多元Fourier变换理论提出一种多元函数的积分变换方法.据此讨论一类模糊 神经网络作为函数逼近器时的逼近误差与其结构关系,得到模糊神经网络的逼近误差与其隐 含层的节点数成反比的结论.并论证了模糊神经网络的函数逼近精度与输入变量数无关.
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关键词:
- 多元Fourier变换 /
- 函数积分变换 /
- 模糊神经网络
Abstract: A new theorem on an integral transform of multi-variable functions is presented based on the multi-variable Fourier transform theory. Using this theorem, the relationship between the approximation error and the structure of the fuzzy function approximator is discussed. And the approximation accuracy, which is inversely proportional to the number of hidden units of the fuzzy function approximator, is obtained. This result shows that the approximation accuracy is independent of the input dimensions.
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