Also, the influence on learning convergence from compression mapping in those CMAC models with actual neurons is discussed.
对于存在实际层神经元的CMAC模型，讨论了压缩映射对网络学习收敛性的影响。
CMAC (Cerebellar Model Articulation Controller) is a kind of local learning feed - forward neural network with simple architecture, quick learning convergence and effective implementation.
小脑模型清晰度控制器(CMAC)是一种局部学习前馈网络，结构简单，收敛速度快，易于实现。
The result shows that RBF networks has very high learning convergence speed and better classifying performance. RBF networks has good practicality in the field of equipment fault diagnosis.
应用结果表明，RBF网络训练速度快、分类性能良好，在设备故障诊断领域具有很好的实用性。
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