非毗邻层连接的前馈神经网络结构有极快的收敛速度。
The front feedback nerve network structure of not-adjacent layer conjunction has splitting velocity on convergence.
提出了一种新的前馈神经网络(N - FNN)复值盲均衡算法。
In this paper, a new complex-valued blind equalization algorithm based on the feedforward neural network (N-FNN) is proposed.
构造了局部连接的前馈神经网络的结构和基于递推预报误差的网络训练算法；
The structure of a partially connected feed forward neural network and the training algorithm based on the recursive prediction error are constructed.
然后介绍了如何使用模糊聚类算法和等价的前馈神经网络从样本数据中辨识离散的TS模型。
Then we introduce how to identify the TS model from sample data using fuzzy clustering algorithm and equivalent feedforward neural network.
研究结果表明，与标准的前馈神经网络相比，是比较合理的和有用的故障诊断应用椭球单元网络。
The research results show that, compared with standard feedforward neural networks, the ellipsoidal unit network is more reasonable and useful for fault diagnosis applications.
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。
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.
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。
Neural networks have several different topologies, but the simplest is known as a feedforward network.
多层前馈人工神经网络在装备故障诊断中的应用含设备运行状态特征值设定和故障判定。
The application of multi-layer feed-forward artificial neural network in fault equipment diagnosis includes feature value setting of equipment operation condition and fault judgment.
以人工神经网络的前馈型网络为基础结构，基于反向传播算法进行学习和训练来拟和证券价格指数的运动趋势。
In this model, back propagation algorithm based on forward networks was conducted to learn information of historical data and to train the network weights.
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。
Multilayer feedforward neural network is the most popular one in practice.
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。
This paper compresses remote sensing images with multilayer feedforward neural network and gives the compression algorithm in detail.
前馈神经网络在许多领域有着广泛的应用。
Feedforward neural networks have been widely used in many applications.
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。
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.
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 presents a text categorization model based on multilayered feedforward neutral network, and introduces the design and implementation of this model.
对于单输出前馈神经网络的梯度算法的收敛性已经有了详细的讨论。
The convergence of the gradient algorithm for feedforward neural networks with one output unit has thoroughly studied.
在闭式循环柴油机配氧反馈控制的基础上采用了神经网络前馈控制策略。
Based on the feedback control, the neural feedforward compensation was applied in oxygen control of closed cycle diesel.
采用混沌优化策略，提出一种前馈神经网络权参数的最优学习方案。
In this paper, the optimization design for feed-forward neural network is proposed based on chaos optimization.
该文利用凸优化理论和约束优化理论为前馈神经网络构造出了一个新的优化目标函数。
The paper constructs a new optimal target function for feed forward neural networks according to convex optimization theory and constraint optimization theory.
BP算法是前馈神经网络训练中应用最多的算法，但其具有收敛慢和陷入局部极值的严重缺点。
BP algorithm is the most popular training algorithm for feed forward neural network learning. But falling into local minimum and slow convergence are its drawbacks.
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。
A hierarchical feedforward neural network model particularly suited to practical statistical pattern recognition tasks is proposed in this paper.
然后提出了两种改进的前馈模糊神经网络，并应用于解决石油工业中的实际问题。
Then two improved feedforward fuzzy neural networks are presented and applied to resolving the practical proWem in petroleum industry.
提出并实现了一种结合前馈型神经网络和K最近邻的文本分类算法。
This paper put forward and carried out a text classification method using feed-forward neural network and K-nearest neighbor.
PD反馈控制器用于使系统达到稳定，同时和前馈的神经网络学习控制器一起使系统达到理想的控制效果。
By PD controller which is used to make system more stable, the system can reach ideal control effects with the feed forward neural learning controller.
本文结合岩体质量的模式识别，阐述了半线性前馈神经网络的基本原理和应用，并给出了其部分试验结果。
In this paper, the principle and application of semilinear feedforward neural network are described, some experimental results are also presented.
椭球单元通过高斯分布逼近形成各模式类的决策区域，是一种非常适合于模式识别任务的前馈型人工神经网络模型。
Neural Networks with Ellipsoidal Activation Functions closes in upon a decision making region by Gauss distribution for various patterns and is adapted to fault diagnosis well.
此目标函数的优化速度快，大大提高了前馈神经网络的学习效率。
The target function's optimal velocity is high, so it can boost learning efficiency of feed forward neural networks.
总结了正交法的应用研究，提出用正交化方法来确定前馈神经网络的结构，包括隐层数、节点数以及网络训练步数。
Based on summarizing of the application of onhogonal method, an onhogonal method for deciding the number of hidden layers, neurons and the training step of neural networks is presented.
总结了正交法的应用研究，提出用正交化方法来确定前馈神经网络的结构，包括隐层数、节点数以及网络训练步数。
Based on summarizing of the application of onhogonal method, an onhogonal method for deciding the number of hidden layers, neurons and the training step of neural networks is presented.
应用推荐