Radial basis function (RBF) network have unique advantages in control applications due to its features of simple topological structure, quick convergence speed and no local minima.
径向基函数(RBF)神经网络由于其结构简单、收敛速度快、无局部极小等特点使其在控制中的应用有着独特的优势。
The calculated results indicate that Chen's lattice inversion method was exact for radial interatomic potential of alkali metals with much faster convergence than CGE method.
计算表明，陈氏三维晶格反演比CGE方法具有更快的收敛性，容易获得较高精度的原子间相互作用势。
People put forward radial basis function networks considering the conventional BP algorithm problems of slow convergence speed and easily getting into local dinky value.
对于传统BP算法存在的收敛速度慢和易陷入局部极小值问题，人们提出了径向基函数网络。
The weights of network adjusted by using the least mean square made fast convergence of radial basis function to obtain better PID control parameters and achieve the speed tracked control.
利用最小均方差来调整网络的权值，使径向基函数快速收敛，获得较佳pid控制参数，达到对转速跟随控制。
The synthetic tests show that the convergence of SV-component receiver function inversion is faster than that of the radial receiver function inversion.
理论数值实验显示：在反演地壳S波速度结构时，SV分量接收函数比径向接收函数具有更好的收敛性。
Radial Basis Function Neural network is an effective feedforward network. It has high convergence rate and high approaching precision, and can avoid local optima.
径向基函数神经网络是其中的一类非常有效的前馈网络，具有收敛速度快、逼近精度高、可避免局部最小等优越性。
Radial Basis Function Neural network is an effective feedforward network. It has high convergence rate and high approaching precision, and can avoid local optima.
径向基函数神经网络是其中的一类非常有效的前馈网络，具有收敛速度快、逼近精度高、可避免局部最小等优越性。
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