The radial basis function network (RBFN) has good extensible and classified (ability).
径向基函数网络具有良好的推广能力和分类能力。
A constructive theory and its constructive algorithm of radial basis function network are presented.
通过对径向基神经网络的研究，提出了径向基神经网络的构造性理论及其构造算法。
The classification mechanism of a radial basis function network (RBFN) is investigated in this paper.
本文研究了径向基函数网络(RBFN)的分类机理问题。
Performance of radial basis function network highly depends on the locations of radial basis function centers.
径向基函数网络的性能在很大程度上取决于径基函数中心位置的选取。
A classification method based on fuzzy vector space model and radial basis function network is presented in this paper.
文本提出了一种基于模糊向量空间模型和径向基函数网络的分类方法。
The problem of recognition of numeric text in topographic maps based on radial basis function network (RBFN) is discussed in this paper.
讨论了基于径向基函数网络(RBFN)的地图数字注记识别问题。
Applying neural network to intensity compensation of optical fiber sensors, a method based on radial basis function network is proposed.
将神经网络应用于光纤传感器的光强补偿，提出了一种基于径向基函数神经网络的光强补偿方法。
A novel forecasting model for compressor casing wall pressure based on phase space reconstruction and radial basis function network was established.
建立了基于相空间重构和径向基神经网络的压气机机匣静压的预测模型。
This article presents surface fitting by use of radial basis function network approach dealing with 3d discrete data, and visualization of 3d data is achieved.
运用径向基函数网络方法将三维离散数据拟合成曲面，实现了三维数据可视化。
The radial basis function network is proposed to use in the determination of pulp kappa number with near-infrared spectroscopy in order to increase precision of kappa number determination.
为了提高制浆过程中的在线预测纸浆卡伯值的精度，提出采用径向基函数网络来建立纸浆卡伯值近红外光谱法在线测量模型。
Using RBF (Radial Basis Function) network as the soft-sensing model, its natural to introduce regularization learning algorithm.
以径向基函数神经网络作为软测量模型，在软测量建模中引入正则化学习算法。
A self_calibrating PCC CAM controller based on RBF (Radial Basis Function) network is presented.
提出了一种基于径向基函数(RBF)网络的具有自校正功能的PCC协联控制器。
For reinforcement learning control in continuous Spaces, a Q-learning method based on a self-organizing fuzzy RBF (radial basis function) network is proposed.
针对连续空间下的强化学习控制问题，提出了一种基于自组织模糊rbf网络的Q学习方法。
For reinforcement learning control in continuous Spaces, a Q-learning method based on a self-organizing fuzzy RBF (radial basis function) network is proposed.
针对连续空间下的强化学习控制问题，提出了一种基于自组织模糊rbf网络的Q学习方法。
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