Aiming at solving the complicated non-linear pattern classification problem of protein secondary structure prediction, a new method based on radial basis function is proposed.
文章针对蛋白质二级结构预测这一复杂非线性模式分类问题，提出了基于径向基函数的预测方法。
Radial Basis Function Neural Network is a kind of Neural Networks which have simple topological structure and clear learn procedure.
径向基函数神经网络是一种拓扑结构简单、学习过程透明的神经网络模型。
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。
In this paper, the model structure and the application of Radial Basis Function Neural Network (RBF NN) to fault diagnosis of power transformer is presented.
研究了径向基函数(RBF)神经网络的模型结构及其在电力变压器故障诊断中的实现方法。
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 structure of an amorphous inorganic ion exchanger-stannic hexametaphosphate is postulated with radial distribution function (RDF) by X-ray diffraction.
通过大角度X射线散射分析，求出了新型无机离子交换剂六偏磷酸锡的径向分布函数，推断其化学结构。
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。
A learning algorithm of subtractive clustering for RBF network is used to obtain the parameters of radial basis function so as to optimize network structure.
在RBF网络中采用了一种减聚类的学习算法来确定径向基函数的相应参数，使网络结构得到优化。
A learning algorithm of subtractive clustering method for RBFNN is used to obtain the parameters of radial basis function, so that RBFNN has an optimized structure.
在RBF神经网络中采用了一种减聚类的学习算法来确定径向基函数的相应参数，从而使神经网络结构得到优化。
This paper proposes a hidden layer structure adaptive radial basis function (HSARBF) classifier.
提出了一种隐层结构自适应学习的径向基函数网络(HSARBF)水声目标分类器。
A novel algorithm for optimizing the structure and parameters of Direction of Arrival (DOA) estimation model based on radial basis function neural network is presented.
提出一种优化径向基函数神经网络来波方位(DOA)估计模型结构和参数的方法。
A novel algorithm for optimizing the structure and parameters of Direction of Arrival (DOA) estimation model based on radial basis function neural network is presented.
提出一种优化径向基函数神经网络来波方位(DOA)估计模型结构和参数的方法。
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