Some problems in the research of multilayer feedforward network are pointed out.
对当前前向网络研究中的一些问题提出了看法。
The prediction accuracy is guaranteed by the interpolation ability of the feedforward network.
预测准确度由前馈网络的插值能力保证。
A new second order recursive learning algorithm to multilayer feedforward network is proposed.
提出了多层前向神经网络的新型二阶递推学习算法。
Neural networks have several different topologies, but the simplest is known as a feedforward network.
神经网络有几种不同的拓扑结构，但是最简单的一种是前馈网络。
A correlation immunity is a capability of feedforward network stream ciphers resisting correlation attacks.
相关免疫是前馈网络流密码抵抗相关攻击的一种能力。
RBF neural network is a three-layer feedforward network and can be used to identify nonlinear model effectively.
RBF神经网络是一种三层前向网络，可有效用来进行非线性模型的辨识。
The neural network used is called DLF network, which is the combination of multilayer feedforward network with linear model.
所采用的网络为一种将线性模型与多层前向网络相结合的DLF网络。
Based on gradient algorithm and the fundamental approximation of feedforward network, a new supervised comprehensive training mechanism is put forward.
基于梯度算法和前馈网络所具有的普遍近似性质，提出了一种新的监督型多目标系统化训练机制。
Radial Basis Function Neural network is an effective feedforward network. It has high convergence rate and high approaching precision, and can avoid local optima.
径向基函数神经网络是其中的一类非常有效的前馈网络，具有收敛速度快、逼近精度高、可避免局部最小等优越性。
Comparing with time delayed feedforward network and diagonal recurrent network, output recurrent network shows its advantages in real-time fault detection system.
通过仿真，与前馈时延网络与对角递归网络的比较研究，说明了在实时故障诊断系统中输出递归网络结构的优越性。
Feedforward networks use back propagation algorithm to train a multi-layer network. After training, the multi-layer network can fit the function in the data space very well.
前向网络利用反向传播算法训练多层网络，使训练后的网络较好地拟合样本空间中各点的函数值。
In the model, using APEX network extracts classification information and condenses vector space dimensions, making use of feedforward network establishes the classification recognition function.
在诊断模型中，应用APEX网络提取分类信息，压缩向量空间维数，利用前馈网络建立其类型识别函数。
Feedforward neutral network are researched on the most mature and used most widely.
多层前向神经网络网络是研究最为成熟、应用最为广泛的人工神经网络。
This paper presents a text categorization model based on multilayered feedforward neutral network, and introduces the design and implementation of this model.
给出一种基于多层前馈神经网络的中文文本分类模型，介绍了该模型的设计和实现。
This paper compresses remote sensing images with multilayer feedforward neural network and gives the compression algorithm in detail.
本文采用多层前馈神经网络对遥感图像进行压缩，给出了具体的压缩算法。
Because the feedforward neural network has an ability of approach to arbitrary nonlinear mapping, it can be used effectively in the modeling and controlling of nonlinear system.
前馈神经网络由于具有理论上逼近任意非线性连续映射的能力，因而非常适合于非线性系统建模及构成自适应控制。
The model was a Feedforward Fuzzy neural network possessing five layers, and Gradient Descent was adopted as learning algorithm.
该模型采用五层前向模糊神经网络，学习算法为梯度下降法。
Presents a method of training a feedforward neural network using supervised learning scheme to balance an inverted pendulum and cart system.
采用平衡的倒摆小车所记录下来的数据，经处理后用有师学习方法来训练前馈神经网络。
A new mutual genetic operator based three stages feedforward neural network training method is proposed in this paper, which divides neural networks training procedure into three stages.
论文提出了一种新的基于互补遗传算子的前馈神经网络三阶段学习方法。该方法把神经网络的学习过程分为三个阶段。
Automated identification of tomato maturation using multilayer feedforward neural network with GA can be realized.
采用遗传算法训练的多层前馈神经网络实现番茄成熟度的自动判别。
A hierarchical feedforward neural network model particularly suited to practical statistical pattern recognition tasks is proposed in this paper.
本文提出了一个适用于统计模式识别任务的阶层式前馈神经网络模型。
In this paper, a novel fast learning algorithm for multilayered feedforward neural network is introduced.
本文提出一种前馈神经网络的快速学习算法。
Multilayer feedforward neural network is the most popular one in practice.
多层前馈神经网络是在实践中应用最为广泛的一种神经网络。
A modified neural network structure which is composed of a linear network and a multilayered feedforward neural network (MFNN) is presented.
本文提出一种改进的神经网络结构，它由线性网络和多层前向网络两部分组成。
In this paper, we present a method of training a feedforward neural network using supervised learning scheme to balance an inverted pendulum and cart system.
本文将专家在平衡—模拟倒摆小车时记录下来的数据经处理后，用监督式学习的方法训练一前置式神经网络。
The theoretical basis of ANN is function approximation, it USES a two - level feedforward neural network to approach arbitrary function to realize better power flow control.
径向基函数神经网络的理论基础是函数逼近，用一个两层的前向网络去逼近任意函数，以更好地进行潮流控制。
The theoretical basis of ANN is function approximation, it USES a two - level feedforward neural network to approach arbitrary function to realize better power flow control.
径向基函数神经网络的理论基础是函数逼近，用一个两层的前向网络去逼近任意函数，以更好地进行潮流控制。
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