One kind of alternant gradient algorithm for improving the training of Radial Basis Function (RBF) neural network is proposed.
提出一种交替梯度算法，对径向基函数(RBF)神经网络的训练进行改进。
Radial Basis Function (RBF) neural network learning algorithm based on immune recognition principle is proposed.
提出了一种基于免疫识别原理的径向基函数神经网络学习算法。
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 Radial Basis Function (RBF) neural network learning algorithm based on immune recognition principle is proposed.
提出了一种基于免疫识别原理的径向基函数神经网络学习算法。
A Radial Basis Function (RBF) neural network learning algorithm based on immune recognition principle is studied.
提出了一种基于免疫识别原理的径向基函数神经网络学习算法。
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。
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。
Aiming at the design difficulty for fuzzy neural network controller, an immune evolutionary algorithm is proposed to design the parameters of a radial basis function fuzzy neural network controller.
针对模糊神经网络控制器难于设计的问题，提出了一种免疫进化算法用于径向基函数模糊神经网络控制器参数的优化设计。
A two-level learning method combining improved immune algorithm and least square method was proposed to design a radial basis function (RBF) network.
结合改进的免疫算法和最小二乘法，提出了一种设计径向基函数(RBF)网络的两级学习方法。
This paper presents a new leaning method for radial basis function network, minimum mean entropy difference criterion algorithm is used to get pattern cluster of training sets.
本文对径向基函数网络提出了一种新的学习算法，利用最小均熵差准则对训练样本进行模式聚类。
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。
Based on immune evolutionary algorithm, a novel radial basis function (RBF) designing algorithm, the immune RBF (IRBF) network, was proposed.
基于免疫进化算法，提出了一种设计径向基函数(RBF)网络的新算法——免疫径向基函数网络(IRBF)训练算法。
In the algorithm, the radial-basis function neural network (RBFNN) is utilized as forward model, and the IGLSA is used to solve the optimization problem in the inverse problem.
该算法中，径向基函数神经网络(RBFNN)用作前向模型，IGLSA用于求解逆问题中的优化问题。
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。
This paper presents an adaptive algorithm of optimally determining the structures, number, positions and widths of kernel functions of the improved radial basis function (IRBF) neural networks.
本文提出了改进的RBF神经网络结构、核函数个数、位置与宽度优化算法。
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。
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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