feedforward network中文是什么意思

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中文翻译
造句

前馈网络

network n. 1.网眼织物。 2.(铁路、河道等的)网状系统，网 ...
feedforward 前馈的; 前馈控制; 正反馈; 正向馈电传送
compensating feedforward 补偿前馈
compounding feedforward 复合前馈
correcting feedforward 校正前馈
feedforward action 前馈作用
feedforward activation 前馈活化
feedforward compensation 前馈补偿
feedforward connection 前馈连接
feedforward control 前馈控制下; 事前控制
feedforward controller 前馈控制器
feedforward element 前馈元件
feedforward inhibition 前馈抑制
feedforward mapping 前馈映射
feedforward matrix 前馈矩阵
feedforward of information 信息前馈
feedforward path 前馈通道; 前馈通路
feedforward stimulation 前馈促进
feedforward system 前馈系统
limiting feedforward 限制前馈; 有限前馈
modifying feedforward 修改前馈, 调整前馈
stabilizing feedforward 稳定前馈, 稳定前授
fec feedforward error correction 前馈纠错
feed-forward=feedforward 前馈
feedforward control system 前馈控制系统

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例句与用法

The one main way that nn is applied to fdd is dynamic system identification with feedforward networks
采用前馈型网络对动态系统辨识是神经网络应用到故障检测和诊断中的主要方法之一。
In this paper multilayer feedforward networks is used to design the nonlinear flight control systems , including the systems identification and control
随着社会的发展，网络的广泛应用，人们对信息的需求量越来越大，需要保存更多的信息。
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。
Three types of artificial neural networks , namely radial basis function network , feedforward network , stochastic network , and their application in the analysis of electromagnetic stop band structure in coplanar waveguide have been discussed
本文研究了以下三种人工神经网络：径向基函数网络、前向网络、随机网络，并用于分析共面波导中的电磁阻带结构。
The paper makes simulation studies into the field oriented control systems based on multiplayer feedforward networks and dynamic recursive networks respectively , and compares the convergence speed and approximate extent between the two learning algorithms
对采用多层前向网络和动态递归网络的矢量控制系统分别进行了仿真实验，比较了两种学习算法收敛的快速性和逼近程度。
In the paper , based on the existing literature research foundation an analog circuit catastrophic fault location approach by using feedforward networks with back ? propagation learning is realized . by this approach , the simulation require ments before test are reduced because fewer training samples are needed , and the fault location process is fast . this method is very efficient in location of single hard fault wit component tolerances . the measureme nt space feature and the general characterization concept of single and double soft fault in linear circuits are presented . according to this concept , a linear circuits soft fault location approach using subhidden layer bpnn is established with element tolerance , and it is shown that this approach is successful in fault location . a double fault feature extraction . ,
本文在现有文献理论研究的基础上实现了采用bp算法前向多层神经网络对直流测试下模拟电路硬故障的诊断方法。其特点是采用少量典型特征样本作为bp网络的训练样本,获得训练样本的代价小,减少了测前工作量,同时诊断速度快,在考虑元件容差时仍有好的诊断效果。文中介绍了线性电路单一软故障和双软故障所具有的电压增量空间特性和统一特征概念。
Nonlinear dynamic modelling of sensors is an important aspect in the field of instrument technique . the recursive neural network is proposed for nonlinear dynamic modelling of sensors , as its architecture is determined only by the number of nodes in the input , hidden and output layers . with the feedback behavior , the recursive neural network can catch up with the dynamic response of the system . the recursive neural network which involves dynamic elements and feedback connections has important capabilities that are not found in feedforward networks , such as the ability to store information for later use and higher predicting precision . a recursive prediction error algorithm which converges fast is applied to training the recursive neural network . experimental results show that the performance of the recursive neural network model conforms to the sensor to be modeled , and the method is not only effective but of high precision
根据动态校准实验结果建立传感器的动态数学模型,以研究传感器的动态性能,是动态测试的一个重要内容.讨论了递归神经网络模型在传感器动态建模中的应用,给出了递归神经网络模型的结构及相应的训练算法.由于其反馈特征,使得递归神经网络模型能获取系统的动态响应.该方法特别适用于传感器非线性动态建模,而且避免了传感器模型阶次的选择的困难.试验结果表明,应用递归神经网络对传感器进行动态建模是一种行之有效的方法
The paper makes research into the multiplayer feedforward networks and dynamic recursive networks , and proposes a method to estimate the speed and rotor flux of induction motors using the dynamic recursive networks . to the used dynamic recursive network model , the off - line dynamic bp algorithm has been reasoned out so as to observe induction motor state variables
本文分别对多层前向网络和动态递归网络进行了研究，提出基于动态递归网络的异步电机的转速估计和磁链观测，针对采用的动态神经网络模型，推导了离线动态bp算法，以便利用动态递归网络进行状态观测。
In this paper multilayer feedforward networks is used to design the nonlinear flight control systems , including the systems identification and control . the main contribution and creativeness result of this dissertation are summarized as follows : firstly , the basic theory of feedforward neural networks is reviewed . and this paper summarized the identification and control methods of nonlinear based on neural networks
本文以某特定飞行器纵向运动非线性系统为被控对象，主要是针对系统中的非线性和未知因素，研究了前向神经网络( bp网络)在非线性飞行控制系统中的应用，并进行了大量的仿真验证，主要完成了以下工作： 1

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Last modified time:Mon, 11 Aug 2025 00:29:56 GMT