The radial basis function neural network (RBFNN) can be employed as an approximator to compensate the system uncertainties after effective learning.
与类神路学习成效息息相关者有二:类神路架构与学习法则。
The radial basis function neural network (RBFNN) can be employed as an approximator to compensate the system uncertainties after effective learning.
与类神路学习成效息息相关者有二:类神路架构与学习法则。
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.
为了进一步实现故障特性的识与跟踪,讨论了一种利用神络对非线性故障模式进行在线逼近的鲁棒故障诊法。
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