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。
The method determining the number of hidden layer node is mainly studied in this paper.
重点探讨了隐含层节点数的确定方法。
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。
The network model consists of three layers: the input layer, the hidden layer, and the output layer.
网络模型由三层构成：输入层、隐含层、输出层。
We have studied that the variable structure neural network for single hidden layer and multi hidden layer.
先后研究了神经网络单隐层和多隐层的变化情况。
The chosen neural network architecture consisted of one input layer, one hidden layer and the output layer.
我们选择的网络结构包括一个输入层、一个隐含层、一个输出层。
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。
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。
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。
Through the analysis of character features, confirm the input layer, hidden layer and the License of output layer units.
通过对字符特征的分析，确定输入层，隐含层，输出层单元数目。
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。
Yet with little damage the result is relatively low. To resolve the problem, augmenting node of hidden layer or number of hidden layer.
只是对于小的损伤识别精度相对差一些，可以通过增大网络隐含层节点数或网络层数来加以解决。
Compare to other ANN modeling, the neuron number of the CNN hidden layer is few, and the ability of generalization of the CNN system is well.
与其它的AN N建模相比较，用CNN建立的模型的隐层神经元数量少，系统的泛化能力强。
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。
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。
The first network is BP network with one hidden layer, and the second network is linear status Neural network based on linear system dynamic equation.
第一种神经网络是具有一个隐层的动态前向BP网络，第二种是基于线性系统动态方程的线性状态神经网络。
The neurons of hidden layer perform the pattern matching of process input information and aggregation operation of time and respond to the input patterns.
隐层神经元完成对过程序输入信息的模式匹配和对时间的聚合运算，输出层对输入模式作出响应。
Method:The main effective factors could be found by weights of the BP Nerual Network, which has one hidden layer, and the correlation of input and output.
方法：拟合输入与输出之间含有一个隐层的BP神经网络，利用各层输入与输出间的相关程度与网络权值确定各因素影响力大小。
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。
Methods the main effective factors could be found by weights of the BP Nerual Network, which has one hidden layer, and the correlation of inputs and output.
方法拟合输入与输出之间含有一个隐层的BP神经网络，利用各层输入与输出间的相关程度与网络权值确定各因素影响力大小。
A novel three-layer neural network with knowledge-based neurons (NNKBN) in hidden layer has been applied to model the crossover discontinuities in stripline circuits.
本文采用一种新型的三层神经网络，即隐蔽层具有知识神经元的神经网络(NNKBN)模拟带状线电路中的十字交越不连续性。
This paper investigates the problem of the model validation in identifying discrete-time-nonlinear dynamic systems by using neural networks with a single hidden layer.
讨论了利用仅含一个隐层的前馈多层神经网络来辨识离散时间非线性动态系统时的模型检验问题。
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。
The RBF network configuration is formulated as a minimization problem with respect to the number of hidden layer nodes, the center locations and the connection weights.
R BF网络的设计问题就是关于网络隐节点数和隐层节点RBF函数中心、宽度和隐层到输出层的权值的性能指标的最小化问题。
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。
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。
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。
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。
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