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self organizing map
相关语句
  自组织映射
     It can be divided into three parts: Introduce the method of detecting outlier by Self Organizing Map on the base of comparing existing detection methods of outlier;
     在自组织映射检测结果的基础上,提出了两个互补的结合领域知识区分不同类型异常数据的方法;
短句来源
     In this paper, the Self Organizing Map (SOM) learning and classification algorithms are modified.
     本文改进了自组织映射学习和分类算法。
短句来源
     This paper introduced the principle and algorithm of using SOM (Self Organizing Map) neuralnetwork to classify leather vein. The specific design and classified results were given.
     本文介绍了采用自组织映射SOM(SelfOrganizingMap)神经网络方法对皮革纹理进行分类的原理和算法,给出了具体的设计方法和实际分类结果。
短句来源
     Self Organizing Map Neural Network (SOM) that has the capability of classifying automatically is used to classify the reclamation condition, which provides the base for adopting suitable reclamation method.
     介绍了利用自组织映射神经网络的自动分类功能对进行矿区土地复垦条件分类,为因地制宜地采取复垦措施提供依据。
短句来源
     The principles and characteristics of typical pattern recognition algorithms,such as k nearest neighbour(k NN),cluster analysis(CA),discriminant analysis(DA),back propagation artificial neural networks(BP ANN),principal component analysis(PCA),probabilistic neural network(PNN),learning vector quantization(LVQ),self organizing map(SOM),adaptive resonance theory(ART) and genetic algorithm(GA),are presented.
     介绍了k近邻法、聚类分析、判别函数分析、反向传播人工神经网络、主元分析法、概率神经网、学习向量量化、自组织映射、自适应共振网、遗传算法等气体传感器阵列常用模式识别算法的原理和特点。
短句来源
  自组织特征映射
     It shows that the trained Kohonen′s self organizing map (SOM) artificial neural net reflects the probability density of the input samples through its output without need of the knowledge of the prior probability of input samples, and it can be applied in function approximation, too.
     Kohonen的自组织特征映射 (Self-organizing map,SOM)人工神经网络在输出上可反映出输入学习样本的概率密度分布 ,且无需知道样本的概率分布的先验知识 ,兼具函数逼近功能。
短句来源
     The article introduces in detail the structure of index, and its realization of algorithm and schematic of program structure of Self Organizing Map (SOM); and explains the feasibility of SOM through examples.
     文章详细介绍了索引结构及自组织特征映射网络(Self Organizing Map,SOM),阐述了它在本软件中的实现算法和程序结构简图。
短句来源
     moreover, this article introduces in detail the Self Organizing Map (SOM), its realization of algorithm and schematic of program structure;
     并详细介绍了自组织特征映射网络 (SelfOrganizingMap,SOM) ,以及其在该软件中的实现算法和程序结构简图 ;
短句来源
     Self Organizing Map is a method of artificial neural network, which implements pattern recognition and data clustering simultaneously.
     自组织特征映射是一种人工神经网络方法 ,可以同时实现模式识别和数据分类。
短句来源
  自组织神经网络
     According to self organizing map principle, a visualized topology map model for radar system effectiveness analysis based on information fusion of multiple parameters is built, and the effectiveness of different airborne radar is analyzed through the topology map obtained from the model.
     根据自组织神经网络原理 ,构建了基于多参数信息融合的雷达系统效能可视拓扑映射图分析模型 ,并根据模型学习获得的拓扑映射图对机载雷达效能进行了分析。
短句来源
  “self organizing map”译为未确定词的双语例句
     The Analysis of Feature Principal Component Extraction and Self organizing Map
     特征主元提取与自组织影射的剖析
短句来源
     This paper unfolds with the degree of supervision,summarizing several methods in supervised,unsupervised and semi supervised learning strategies NBC(Nave Bayes Classifier),FCM(Fuzzy C Means),SOM(Self Organizing Map),ssFCM(semi supervised Fuzzy C Means)and gSOM(guided Self Organizing Map)and also their application in text categorization.
     本文以监督的程度为线索 ,综述了分属全监督 ,非监督以及半监督学习策略的若干方法—NBC(Na veBayesClassifier) ,FCM (FuzzyC Means) ,SOM (Self OrganizingMap) ,ssFCM (semi supervisedFuzzyC Means)和gSOM(guidedSelf OrganizingMap) ,并应用于文本分类中。
短句来源
     A new approach for water quality analysis of water source was expected through the study on Self Organizing Map (SOM).
     通过对自组织数据地图(Self Organizing Map,SOM)理论及技术的研究和应用,力求找到水源水质分析的新方法。
短句来源
     The self organizing map (SOM) was used in the visual classification of the carcinogenicity of 77 polycyclic aromatic hydrocarbons (PAHs).
     将自适应映射 (SOM)用于多环芳烃致癌性的分级。
短句来源
     Improving the speed of computation in image classification is one of the most elements in image dispatching,so improving the algorithm speed becomes the important aspect in study. Kmeans algorithm,FCM,self organizing map network algorithm are all the image classification methods.
     图像分类中提高分类的运算速度是图像处理的一个重要因素 ,提高运算速度成为研究的一个重要方面。
短句来源
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  self organizing map
In fact, a Self Organizing Map (SOM), combined with multiple recurrent neural networks (RNN) has been trained to predict the components of noisy and large data set.
      
The training set is fed to a self organizing map neural network to cluster the measurements.
      
The Self Organizing Map (SOM) algorithm has been utilized, with much success, in a variety of applications for the automatic organization of full-text document collections.
      
In this paper we study the sensitivity of the Self Organizing Map to several parameters in the context of the one-pass adaptive computation of cluster representatives over non-stationary data.
      
We only need to replace normal E-step with the modified E-step presented here to obtain a self-organizing map version of the given mixture model.
      
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In this paper, the neural network processing principle and structure are given which are requisite for damage assessment and processing of fiberoptic array sensing signals in fiberoptic smart materials and structures Requiring of this application,the models of backpropagation neural network, self-organizing map neural network and its variants(such as LVQ1,LVQ2,LVQ3,LVQ4 and LVQ5 et al)are discribed in detail.At the same time,the simulation results are also given.

本文以光纤机敏材料与结构中的损伤估计为目的,根据光纤阵列传感信号处理的需要,在给出人工神经网络处理原理与结构基础上,结合应用详细地阐述了适用的反向传播神经网络(BP)模型、自组织特征映射神经网络(Kohonen)模型及其变化形式(LVQ_1,LVQ_2,LVQ_3,LVQ_4及LVQ_5等),同时给出了仿真实验的结果

A novel approach is introduced for composite damage assessment.The system consists of an embedded fiberoptic sensor array,Shape Memory Alloy(SMA)and Kohonen Self-Organizing Maps(SOM) neural network processor. The fiberoptic sensor array embedded in the com-posite structure can be used to detect the damages in the composite。The neural network is simu-lated by high speed Parallel Distributed Proeessing(PDP) which consists of TMS320C25 high speed processor and IBM PC/386 computer, deals with...

A novel approach is introduced for composite damage assessment.The system consists of an embedded fiberoptic sensor array,Shape Memory Alloy(SMA)and Kohonen Self-Organizing Maps(SOM) neural network processor. The fiberoptic sensor array embedded in the com-posite structure can be used to detect the damages in the composite。The neural network is simu-lated by high speed Parallel Distributed Proeessing(PDP) which consists of TMS320C25 high speed processor and IBM PC/386 computer, deals with the output signals of sensors on time,and controls and actuates the shape memory alloy wires to change the strain state of the compo-site,So that,the damage of composite will be delayed。

介绍了一种复合材料损伤评估的新系统。该系统由埋入光纤传感器阵列、形状记忆合金丝和K ohonen 自组织神经网络处理器组成。由埋入光纤传感器阵列实现对材料损伤的检测,神经网络由TMS320C25 高速并行处理器和IBMPC/386组成的高速并行分布处理器进行模拟,实现传感器输出信号的实时处理,并产生相应的控制信号激励形状记忆合金丝(SMA),以改变材料的应力状态,延缓材料的破坏。

Analyses the neural networks of the feature principal comonent extraction(PCE),the self organizing feature map(SOFM),the classes augment self organizing semantic map(SOSM)and improved feature fine quantization self organizing map.By means of the feature compression of vehicles and vision analysis,the result indicates that PCE and SOFM can show similarity between objects and relative structures,have function of semantic map.The SOFM of feature fine...

Analyses the neural networks of the feature principal comonent extraction(PCE),the self organizing feature map(SOFM),the classes augment self organizing semantic map(SOSM)and improved feature fine quantization self organizing map.By means of the feature compression of vehicles and vision analysis,the result indicates that PCE and SOFM can show similarity between objects and relative structures,have function of semantic map.The SOFM of feature fine quantization can achieve detail classfication as classes augment SOSM, it overcomes the drawbacks of increasing dimensions of SOSM augments input feature,unnecessary calculation and inconsistency of input feature and map result.

剖析了用神经网络实现特征主元提取(PCE)、自组织特征影射(SOFM)、类扩展自组织语义影射(SOSM)和改进的特征细化自组织影射.通过对运载工具的特征压缩,进行可视性分析,结果表明PCE和SOFM都能显示事物间的类似程度和关系结构,具有语义影射的功能.特征细化的SOFM同样能达到类扩展SOSM细化分类的功能,它克服了类扩展的SOSM增加输入特征的维数、增加不必要的计算量、输入特征与影射结果不相一致的缺点.

 
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