A novel direct adaptive fuzzy neural networks (FNNs) controller for a class of uncertain nonlinear chaotic system is presented.
提出利用直接自适应模糊神经网络控制一类不确定非线性混沌系统新方法。
Based on the identification model, an adaptive fuzzy neural networks voltage controller was designed. The parameters of the controller are regulated by adopting the novel BP algorithm.
基于该辨识模型，设计了一个自适应模糊神经电压控制器，其参数采用改进的BP算法进行在线修正。
This fuzzy neural network USES wavelet basis function as membership function whose shape can be adjusted on line so that the networks have better learning and adaptive ability.
这种模糊神经网络利用了小波基函数作为隶属函数，可在线根据误差调整隶属函数的形状，使模糊神经网络具有更强的学习和适应能力。
We study expert PID control, fuzzy adaptive PID control, RBF neural network PID control, internal control based on RBF neural networks.
研究了专家PID控制、模糊自适应PID控制、基于RBF神经网络整定的PID控制、基于RBF神经网络的内模控制。
Based on the theory of neural networks, fuzzy clustering algorithm and adaptive pattern recognition, the method can be used to classify and design the sample workpiece automatically.
该方法借鉴了神经网络理论、模糊聚类算法和自适应模式识别法的优点，自动完成样本的分类与样件设计工作。
Based on the theory of neural networks, fuzzy clustering algorithm and adaptive pattern recognition, the method can be used to classify and design the sample workpiece automatically.
该方法借鉴了神经网络理论、模糊聚类算法和自适应模式识别法的优点，自动完成样本的分类与样件设计工作。
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