The hidden-layer R of RBF neural network consists of a set of RBF (radial base function).
径向基函数（RBF）神经网络隐含层R由一组径向基函数构成。
Here I give some references to the selection of the number of hidden-layer nodes and learning rate.
在这里我们对于隐含层节点数选择、学习速率选择等问题提出一些参考意见。
A class of process neural network model with two hidden-layer based on expansion of basis function is brought forward.
提出一类基于基函数展开的双隐层过程神经元网络模型。
This layer cannot be deleted or hidden, and it is not shown in the Layers view.
该层不能被删除或者隐藏，它不能显示在Layers视图之中。
This setting will create a neural network model that does not contain a hidden layer, and that therefore is equivalent to logistic regression.
这样设置便可以创建不包含隐藏层的神经网络模型，从而使该神经网络模型与逻辑回归等效。
Trial numerical computation indicates that taking radial basic function as exciting function of a hidden layer brings good sample fitting effect.
经数值计算结果表明，选择径向基函数作为隐层的激励函数，可以得到较好的样本拟合效果。
Adaptive wavelet neural network intelligent detection is a method in which the wavelet function substitutes for the activation function of hidden layer in the neural network.
自适应小波神经网络检测法就是利用小波函数取代通常神经网络中隐层的作用函数来实现的。
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。
In this scheme, the inputs of hidden layer neurons are acquired by using the gradient descent method, and the weights and threshold of each neuron are trained using the linear least square method.
在该方案中，通过梯度法获取隐层神经元的输入，使用线性最小二乘法训练各神经元的权值和阈值。
This paper proposes a method which can determine the suitable structure in the hidden layer of a neural network.
提出一种确定神经网络隐层中合理结构的方法。
The role of hidden layer neurons of a RBF neural network can be interpreted as a function which maps input patterns from a nonlinear separable space to a linear separable space.
R BF神经网络的隐层神经元的作用可解释成从非线性可分空间向线性可分空间映射的函数。
With the best polynomial approximation as a metric, the rate of approximation of the neural networks with single hidden layer to a continuous function is estimated by using a constructive approach.
以最佳多项式逼近为度量，用构造性方法估计单隐层神经网络逼近连续函数的速度。
First, the usual ways that are employed to choose the number of RBFNN's hidden layer nodes are analyzed and compared.
首先对目前常用的RBF网络的隐层节点数的选择办法进行了分析，并指出它们的优点和不足。
This paper analyzed the tertiary industry added value in Inner Mongolia using Artificial Neural Network. Finally, the paper built the BP Neural Network model with single hidden layer.
文章通过运用神经网络的建模方法对内蒙古自治区第三产业增加值进行分析，最后建立了单隐层的BP神经网络模型。
The choice of quantity and position of hidden layer radial basis functions is very important and directly affects the goodness of fit of overall network classification ability.
在径向基函数神经网络中，隐层中心的数量和位置的选择是整个网络性能优劣的关键，直接影响网络的分类能力。
Due to the shortage of traditional color matching methods applied with BP neural network, an improved algorithm is put forward in this paper. The new algorithm references the outputs of hidden layer.
本文针对传统的BP网络在织物染色配色中的缺点，提出了一种参考隐层输出的改进算法，建立了一个计算精度更高、收敛速度更快的计算机配色网络模型。
Toggling layer visibility no longer makes a hidden layer active.
切换图层可视性不再使一个隐藏层激活。
With the pull methodology, individual nodes have no way of knowing if they are in the input, hidden, or output layer.
使用pull方法则无法知道节点究竟位于输入层、隐藏层还是输出层。
The equalizer is constructed with decision feedback structure, and an immune algorithm is used to determine the structure and parameters of RBF nonlinear hidden layer.
这种均衡器引入了判决反馈均衡器的结构，并采用免疫算法确定RBF网络隐层（非线性层）的结构和参数。
Taking a MLP with a single hidden layer for an example, a semi-linear analysis theory of internal behavior of MLPs is presented.
作者以单隐层的MLP为例，论述了关于MLP的内部行为的半线性分析理论。
The analysis shows that: by the sacrifice of compression ratio, the quality of the recovered image can be improved with the increase of the number of the neurons in the hidden layer.
分析结果表明：可以通过牺牲压缩率，增加隐含层的神经元数来提高重建图像的质量。
Determining the thickness of "hidden layer" is an important problem in engineering geophysics and engineering geology.
确定“隐蔽层”的厚度，是工程物探、工程地质和工程地震学中的一个重要问题。
The principle and methods to determine the network parameters such as number of neuron in hidden layer, excitation function and the convergence accuracy have been analyzed in detail.
并且详细叙述了神经网络结构参数如隐含层神经元个数、激励函数、网络收敛精度等的确定原则和方法。
This paper investigates the identification of unknown nonlinear dynamical system using multilayered feedforward neural network with a single hidden layer.
本文探讨了只用单个隐含层的前向神经网络对未知非线性动态系统的识别。
It is composed of a hybrid locally connected recurrent network with an activation feedback and an output feedback respectively in the hidden layer.
该网络控制器的隐含层由带有输出反馈和激活反馈的混合局部连接递归网络组成。
Aiming at the slow convergence rate of BP neural network, append a correlative node on hidden layer, improve the adaptive ability and rate of studying of neural network.
针对BP算法收敛速度慢的特点，在隐含层上加入了关联节点，改善了网络的学习速率和适应能力。
The effects of neuron number in hidden layer and momentum parameter on classification have been investigated.
文章还对隐含层神经元数目和动量参数的影响做了考察。
With the relative water consumption of each growing stage as input and relative crop yield output, a BP artificial neural network structure containing a single hidden layer is established.
将各生育阶段的耗水量作为输入，将作物单产作为输出，构建了具有1个隐含单元层的BP神经网络结构。
With the relative water consumption of each growing stage as input and relative crop yield output, a BP artificial neural network structure containing a single hidden layer is established.
将各生育阶段的耗水量作为输入，将作物单产作为输出，构建了具有1个隐含单元层的BP神经网络结构。
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