模糊神经网络模型辨识 Fuzzy neural network model identification
理论证明，只要神经网络辨识模型的精度足够高，就会获得很好的控制精度。
It is proved that the control performance is very well under the enough accuracy of the identification model.
该文提出一种用于复杂的非线性未知系统辨识的混合神经网络模型—自适应模糊神经网络(AFNN)。
This paper presents a compound neural network model, i. e., adaptive fuzzy neural network (AFNN), which can be used for identifying the complicated nonlinear system.
神经网络的非线性逼近能力的研究是神经网络成为辨识模型的理论基础。
The theory of identification model based on neural networks(NN)is to research into its capability of nonlinear approximation.
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