根据陀螺平台实测超高数据，采用LM算法对所设计的非线性神经网络进行训练。
According to the practical superelevation data measured with single-axis gyroscope platform, the designed non-linear neural network is trained with LM algorithm.
针对零极点匹配动态补偿方法的不足，提出基于非线性神经网络的摆式列车检测系统动态补偿方法。
In view of the disadvantages of zero-pole matching dynamic compensation method, the dynamic compensation method of tilting train measurement system based on non-linear neural network is put forward.
本文研究一类非线性神经网络自适应控制系统，提出一种基于双误差——辨识误差和跟踪误差的新控制方案。
A class of nonlinear neural network adaptive control systems is studied and a new design concept based on double errors was proposed in this paper.
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