The radial basis function neural network (RBFNN) can be employed as an approximator to compensate the system uncertainties after effective learning.

与类神经网路学成效息息相关者有二：类神经网路架构与学法。

In order to further discuss the identification of fault after the detection, a nonlinear online neural network approximator is used to provide an estimate of the fault.

进一步实现故障特性的辨识与跟踪,讨论一种利用神经网络对非线性故障模式进行在线逼近的鲁棒故障诊断方法。