特征映射

本文介绍一种面向非回转体零件并采用特征映射方法实现CAD／CAPP信息集成的系统。

Based on the method of feature mapping , an integrated system of CAD / CAPP for prismatic component is introduced .

自适应SOM特征映射研究

Research on Adaptive Self - Organizing Feature Mapping

基于SOM特征映射图上引力场的故障模式识别

Fault Pattern Recognition Based on Gravitation Field of Self-organizing Feature Map

基于SOM特征映射图的同步区域生长故障模式识别。

Pattern recognition method of Remote Fault Diagnosis based on synchronous enlargement of Self-Organizing Feature Map .

应用自组织特征映射（SOM）神经网络实现凝汽器的故障诊断。

A method based on self-organizing neural network is applied to realize fault diagnosis of condenser .

本文通过利用涌现自组织特征映射神经网络对数据进行聚类分析，并通过无边界U矩阵实现可视化功能。

To facilitate clustering analysis and visualization of data , the Emergent Self-Organizing Feature Maps ( ESOM ) and a boundless U-matrix are needed .

基于模糊c-线性簇聚类算法的Kohonen特征映射

Fuzzy c Linear Clustering Algorithm Based Kohonen Feature Mapping Network

提出了一种基于Voronoi距离的双自组织特征映射网络。

An improved twinned Self-Organizing Maps ( SOM ) based on Voronoi distance was presented in this paper .

采用层次分析法（AHP）、模糊神经网络（FNN）和自组织特征映射神经网络（SOM）三种方法对电子政务进行评估研究。

Analytic hierarchy process ( AHP ), fuzzy neural network ( FNN ) and self organizing feature map ( SOM ) are used .

描述了Hopfield神经网络和自组织特征映射神经网络解决TSP问题时的求解过程和仿真算法。

Hopfield neural network and self-organizing feature map neural network are utilized to solve traveling salesman problem . The arithmetic of software is given .

基于EBF网络的非线性特征映射器及其在鲁棒话者识别中的应用

A Nonlinear Feature Mapper Based on EBF Networks for Robust Speaker Verification

为了解决测井岩性识别问题，引入具有较强的聚类和容错能力的自组织特征映射（SOFM）神经网络。

Based on the self-organizing feature map ( SOFM ) neural network this paper introduces a logging lithological identification technology .

在地形表面建模技术方面介绍了Creator地形建模的主要功能，重点讨论了地形表面特征映射方式以及地形建模的主要流程；

Furthermore , after describing the main functions about Terrain surface modeling , the Feature projection modes and primary flow chat of Creator Terrain modeling are discussed especially .

提出一种基于自组织特征映射网络（SOFM）和遗传算法的定量数据规则提取模型。

A rule induction model based on self-organizing feature map ( SOFM ) and genetic algorithm is proposed for quantitative data .

针对船舶雷达目标识别存在的问题，研究了基于聚类的自组织特征映射网络（SOM网）的船舶识别。

Aimed at the problem existed in ship 's radar target recognition , the paper investigated ship recognition using cluster based SOM ( Self-Organizing feature Map ) .

介绍了一种利用SOFM（自组织特征映射）网络的聚类功能进行全天星图识别的算法。

An autonomous star pattern recognition method using the tri-star clustering function of SOFM ( Self-Organizing Feature Maps ) network is described .

针对冲压零件设计和加工过程特点，提出一种基于特征映射的板料冲压件面向制造的设计（designformanu－facture，DFM）系统结构，以实现DFM方法在冲压零件设计中的应用。

An architecture of DFM ( design for manufacture ) system for stamped product is proposed and the main functional modules are described .

对此，本文提出了一种基于自组织特征映射（SOM）的聚类算法，该算法将SOM与潜在语义索引技术（LSI）有机地结合。

To meet these requirements , we proposed a clustering algorithm that is based on Self-organizing Map ( SOM ) and Latent Semantic Indexing ( LSI ) .

Keane曾用特征映射问题比较了类比映射的三种计算模型，但缺乏相应心理学实验的验证。

Keane et compared the three computational models using the Attribute-Mapping problem , but it is lack of validation psychological experiments .

针对图像的分类识别问题，提出了自组织特征映射网络（SOM）的可识别图像目标特征模板库构建的方法。

For image classification and recognition , the approaches to set up sample feature database using self-organizing feature map neural networks ( SOM ) is presented in this thesis .

提出了一种基于模糊c－线性簇聚类算法的Kohonen特征映射算法.这种特征映射克服了Kohonen网存在的一些缺点.对某些识别问题，其计算效率非常高。

A new fuzzy Kohonen feature mapping algorithm ( FLKCN ) based on the fuzzy c linear clustering algorithm is proposed . It can overcome some disadvantages of the original Kohonen network .

基于Kohonen神经网络能够保持拓扑结构的自组织映射的特性，对散乱数据点进行曲面重构，建立了基于自组织特征映射神经网络的矩形网格重构模型。

Basing on Kohonen neural network 's self-organizing feature map of being capable of keeping topologic structure , surface is reconstructed from scattered data points .

并对SOM算法进行了改进，提出了一种分类频率敏感自组织特征映射（CFSSOM）算法。

Then a classified frequency sensitive self-organizing feature map ( CFSSOM ) was proposed for the codebook training .

自组织特征映射（SOFM）网络利用神经元权值向量表示输入数据的结构、具有较好的分类能力。

The self-organizing feature map ( SOFM ) uses weight of network to present structure of the input data and has preferable ability of classification .

以嵌岩桩嵌岩段承载力极限值估计的BP网络模型为基础，提出了用自组织特征映射网络来分析问题的特征参数的方法，其分析结果与工程实践结果相一致；

Based on the neural network model of limit load of rock socketed segment of pile , the analysis method of characteristic parameters is proposed by means of self organizing character map network . The analysis results are consistent with practical results .

第一层结构使用自组织特征映射神经网络（SOFM）将像素映射到二维的平面上。

The first level of our system employs the self-organizing feature map ( SOFM ) to map colors of image on a two dimensional feature map .

提出曲元分析（CCA）和自组织特征映射（SOFM）相结合的方法用于轴承的故障诊断特征提取。

The combination of curvilinear component analysis ( CCA ) and self-organizing feature map ( SOFM ) were applied to a diagnosis for fault feature extraction of bearing .

采用GMM-UBM结构进行特征映射能够实现数据压缩，并提取代表说话人个性信息的特征矢量。

The GMM-UBM based feature mapping can realize the data condensation and extract the speaker feature vector .

在COREL图像库上的实验也验证了该方法的有效性。4.相关特征映射及其在CBIR上的应用研究。

Experiments performed on COREL image database also show the efficacy of our method . 4 . Relevance feature mapping and its applications to CBIR .

文中以一个实际500kV输电网络为模型，提出了基于BP前馈网络和Kohonen自组织特征映射网络的高压输电线路故障分类方法，并进行了仿真研究。

Based on BP neural network and Kohonen self-organization network , is designed in this paper . Simulation results show its effectiveness on an actual 500 kV transmission network . Feature extraction .