查询词典 neural network

In this thesis, we firstly introduce several class of discrete-time neural network models and the research progress of the neural networks. By Schauder fixed-point principle we prove the existence of an equilibrium (i.e. a fixed point) of a discrete-time neural network with generalized input-output function and by using the converse theorem of Lyapunov function we study the uniformly asymptotical stability of equilibrium in this discrete-time neural network with variable weight and give some sufficient conditions that guarantee the stability of it.

本文首先介绍了几类离散神经网络模型的由来及其研究概况，利用Schauder不动点原理证明了一类具有广义输入输出函数的离散神经网络模型平衡点的存在性，利用Lyapunov函数逆定理给出了这类离散神经网络模型在时变权值下的一致渐近稳定性的充分条件。

In this paper chip shapes were recognized by using of radbas neural network. We put forward area ratio feature, Euler number feature, etc. geometry feature of chip shape image and thing of those features as inputting vector of neural network. Adopt radbas neural network and training the network using RLS.

研究了径向基函数神经网络在硬质合金刀具切屑形态图像识别中的应用，提出了面积比、欧拉数、分散度等硬质合金刀具切屑形态图像的几何特征，以上述特征作为神经网络的输入矢量，利用径向基函数网络，采用了递推最小二乘法训练该网络。

At first, with the low-frequency data measured, three of the LRE fault detection systems for the real-time condition are proposed using the nonlinear identification technology of the BP neural network, the state estimation technology of the dynamic neural network, and the pattern recognition technology of the fuzzy hypersphere neural network. The learning algorithms of the BP and dynamic neural network are researched at the same time. Furthermore, while the engine operation is divided into the start and steady-state processes, the real time ability, the response time, the accuracy, the robustness, the sensitivity and the monitoring parameter optimization are studied. In the test data analyses of the YF-75 engine, the detection system correctly carried out for all normal tests, and in the three abnormal tests the engine faults were accurately forecasted.

首先，基于低频测量数据，采用BP神经网络的非线性辨识技术、动态神经网络的状态估计技术及模糊超球神经网络的模式识别技术，提出了三种发动机故障实时检测系统；同时研究了BP神经网络和动态神经网络的学习算法；另外还把发动机工作分为启动过程和稳态过程，分别讨论了神经网络故障检测系统的实时性、及时性、准确性、鲁棒性、敏感性及参数优化问题；在YF-75发动机试车数据分析中，不仅全部正确地监测了正常试车过程，而且准确地预报了三次异常试车中的发动机故障。

The penalty optimal brain surgeon is a post-training algorithm and it has extreme high complexity. The OBS oriented compute model implemented neural network training and OBS pruning simultaneously, by taking the OBS pruning case as a penalty term of neural network objective functions based on optimized structure of the regularization method included in the neural network training process. It both maintained the OBS's accuracy and had regularization method's high efficiency. Raised the generalization of neural network model.

最优脑外科过程是一种训练后网络剪枝算法，计算的复杂度非常高，通过把剪枝条件以惩罚项的形式纳入神经网络的训练目标函数中，把正则化方法的结构优化蕴涵于网络训练过程，构建面向最优脑外科过程的计算模型，实现网络训练过程和最优脑外科过程并行剪枝，既保持了最优脑外科过程的准确性，又具有正则化的高效性，提高了神经网络模型的泛化性能。

Aiming at the disadvantage of conventional BP neural network, such as selecting parameter values by the empirical method, slow convergence speed and easy trap into local minimum points, this paper designs an improved BP neural network system. In order to improve the network convergence rate and reduce the training error, this paper optimizes the initial connecting weight value of neural network by the use of ant colony algorithm and trains artificial neural network by Levenberg-Marquardt algorithm.

针对常规BP神经网络参数的经验式取值方法以及收敛速度慢，容易陷入局部最小点等缺陷，设计了一种改进的神经网络系统，利用蚁群算法优化神经网络连接权初值，并采用LM算法对人工神经网络进行训练，提高了网络的收敛速度，降低了训练误差。

For further study to improve performance, an adaptive control algorithm based on Neural Network is tried in stabilization control. A new method of selecting the initial weights of Neural Network is put forward, which is that the coefficients of discrete equivalent of continuous transfer function in traditional control are used as the initial weights of Neural Network. Adaptive Neural Network control is combined with traditional control by using different method in different segment.

作为进一步提高稳定系统性能的探讨，对基于神经网络的参数自适应调整控制方法在稳定控制中的应用进行了研究，提出了将传统校正方法经离散化后所得到的数字控制算法的系数作为神经网络权值初值的新方法，并采用分段控制，将传统校正方法和神经网络控制方法相结合，取得了较好的控制效果。

In this paper, the theory of artificial neural network is summarized; the analyse on BP neural network model is put stress on. For the predominance of artificial neural network"s dealing with non-linear complicated relation, the technology of artificial neural network is introduced into the evaluation of the highway bridge"s carrying capacity; and the preferences , the collection and disposal of stylebook, the structuring of BP neural network model are analyzed.

文中对人工神经元网络理论进行了综述，重点对神经元网络的BP算法进行了分析，利用人工神经元网络处理非线性复杂关系的优势，将人工神经元网络技术引入到公路桥梁承载力评估中；并对其中的参数选择、样本收集与处理、构造BP网络模型等进行了分析。

In chapter 4, basing theories and methods of scientific visualization, and artificial neural network BP algorithm, we integrate the Visual C++, OpenGL graphics library and Excel VBA technique to develop the program of artificial neural network and to make the BP algorithm visually, this program works can be divided into four parts: Using C language to develop program about BP algorithm; Using Visual C++, develop the GUI Interface, make input parameter visually; Using OpenGL graphic technique to display the training sample point in three dimension; at last using Excel DDE technique display the error graphic tables in Excel system In chapter 5, on the view of engineering application, we establish new method of surface reconstruction basing artificial neural network, develop interface program between module and commercial CAD/CAM system, meantime deeply discuss some key problems, for example, setting up the base plane, using the API technique, cutting and editing surface boundary, and also discuss the more compliant problem: how to intersect surface, at end we finish the work of translation from our surface reconstruction module to commercial CAD/CAM system, then make reverse engineering system basing artificial neural network more useful.

第四章基于科学计算可视化理论，依据人工神经网络BP算法理论模型，综合Visual C++，OpenGL图形库以及Excel VBA等多项软件开发技术，编制了人工神经网络程序，实现了BP算法的可视化映射。具体工作分为四部分：利用C语言实现人工神经网络BP算法；利用VisualC++的GUI技术开发图形用户界面，实现参数设置可视化；利用OpenGL图形技术进行三维映射，显示学习样本及训练样本点；利用微软电子表格DDE动态数据交换技术，在Excel上动态显示学习误差曲线图。第五章从工程应用的角度出发，提出了一种新的基于人工神经网络算法的曲面裁剪重构方法，完成了曲面重建模块与通用CAD/CAM系统的接口设计工作，对其中的若干关键问题进行了深入讨论，例如基平面设定、API技术的应用、边界裁剪等问题，同时，对曲面计算中较为困难的曲面相交问题也进行的专门探讨，最终完成了曲面重建模块向CAD/CAM系统的数据传输工作，使人工神经网络逆向工程系统趋向实用。

It points out the current situation and existing problems of this method. This paper actualizes the integration of Expert System and Neural Network. It excellently utilizes the advantages of Expert System and BP Neural Network, and overcomes some of their disadvantages.Neural network expert system is designed based on neural network high identification ability and theory research.

本文介绍了专家系统应用于故障诊断的原理，详细阐述了专家系统的结构、各部分功能、工作流程等，并指出了该方法在故障诊断中的应用现状和存在的问题；实现了神经网络和专家系统的结合，很好地利用专家系统和BP神经网络的优点并且克服了它们的一些缺点。

The main contents are as follows:Firstly, starting with the general situation of soil erosion and the harms caused by it, the causes leading to the local soil erosion problem are analyzed comprehensively in the paper. And connecting with the measures taking place, sticking points towards the career of soil and water conservation are expatiated upon.Secondly, Back-Propagation Neural Network, One of Artificial Neural Network is used to set up a modal about the connection of the soil erosion modulus and seven factors impacts on it, such as, rainfall, rainfall largest intensity in 30 minutes, runoff coefficient, vegetation cover percent, rate of granule, rate of physical viscidity-clay, the rate of organic matter. Through the comparison with linear regression model, the second regression model, the Chinese Soil Loss Equation, it illustrated that BP Neural Network modal is more accurate than the other three modals in forecasting the mount of soil erosion, and the BP Neural Network will have some applicability in forecasting in soil erosion.

本文以霍山县作为皖西大别山区的典型区域，主要研究了以下内容：(1)从介绍霍山县土壤侵蚀状况以及所造成的危害入手，全面分析了导致当地土壤侵蚀发生的原因，并结合当地采取的水土保持相关措施，阐述了当地水土保持工作的症结所在；(2)结合上土市水土保持试验站多年实测资料和2005年实验资料，应用BP神经网络理论，建立了次降雨土壤侵蚀量与次降雨量、最大30min雨强、径流系数、植被覆盖度等因子之间关系的模型，并通过BP神经网络的预测模型与一次回归模型、二次回归模型、CSLE模型之间的对比分析，说明了建立的BP神经网络模型在土壤侵蚀预测可以取得较回归模型和CSLE模型更高的精度，也说明了BP神经网络理论在土壤侵蚀预报中具有一定的适用性。

Neither the killing of Mr Zarqawi nor any breakthrough on the political front will stop the insurgency and the fratricidal murders in their tracks.

在对危险的南部地区访问时，他斥责什叶派民兵领导人对中央集权的挑衅行为。

In fact,I've got him on the satellite mobile right now.

实际上 我们已接通卫星可视电话了