The theory of fuzzy neural network (FNN) modeling for nonlinear systems is presented.
论述了模糊系统和神经网络相结合的非线性系统辨识理论。
Modeling for nonlinear soft measuring by means of neural network can be used to estimate variables that can not be measured on line.
用神经网络为非线性软测量建模，用于推断估计不可在线测量的变量。
An approach for building accurate and fast running T-S models is proposed based on summarization of the experience of nonlinear modeling.
在总结非线性建模经验的基础上，给出了一种建立精确且运行速度快的T - S模型的方法。
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