Choosing a training method is very important when using neural network to obtain the model and the inverse model of the nonlinear object.
在使用神经网络完成非线性对象的模型和逆模型时，选择的训练方法很重要。
Based on the property of the system inverse model, an integral approach to nonlinear compensation of temperature measuring system with thermistor based on neural network is presented.
从系统逆模型补偿出发，基于神经网络提出一种更加完备的热敏电阻测温系统非线性校正方法。
A direct inverse model controller of fuzzy neural network with changeable structure based on t s inference is presented in this paper and it is used to the motion control of mobile robot.
本文提出一种基于T - S模型的变结构模糊神经网络直接逆模型控制器，并将其应用于移动机器人的运动控制中。
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