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1·A new method that determines radial basis function centers is proposed.

提出了一种新的确定径向基函数中心的方法。

2·Among them, the Radial Basis Function (RBF) neural network is a better model.

在这些预测模型中性能比较突出的是径向基函数网络(rbf)法。

3·The structure and features of radial basis function (RBF) network are introduced.

介绍了径向基函数(RBF)神经网络的结构和特点。

4·The structure and principle of Radial Basis Function (RBF) neural network are studied.

分析了径向基函数(RBF)网络的结构和工作原理。

5·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。

6·An adaptive radial basis function neural network (ARBFNN) power control scheme is proposed.

提出了一种自适应r BF神经网络功率控制方案。

7·It can train polynomial function, neural networks, or radial basis function (RBF) classifiers.

它可以对多项式函数，神经网络，径向基函数进行训练。

8·A method based on radial basis function networks for forecasting chaotic time series is proposed.

给出了基于径向基函数网络的混沌时间序列预测的方法。

9·We present a new algorithm of facial expression animation based on radial basis function networks.

提出了基于径向基神经网络的人脸动画生成的算法。

10·A novel radial basis function neural network based on ant colony clustering (RBF-ACC) was proposed.

提出了一种基于蚁群聚类算法的径向基神经网络。