1.The radial basis function neural network (RBFNN) can be employed as an approximator to compensate the system uncertainties after effective learning.
经网路学习成效息息相关者有二:经网路架构学习法则。
2.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.