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self organizing map
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  自组织映射
    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。
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  自组织特征映射
    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 ;
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  “self organizing map”译为未确定词的双语例句
    By using the overlapping sensitivity of chemical gas sensors, an artificial olfactory system based on a telepresence robotic system, combing a chemical gas sensor array with self organizing map (SOM) neural networks, is constructed to qualitatively analyze chemical gases.
    利用半导体气体传感器的交叉敏特性 ,将气体传感器阵列与神经网络相结合 ,构建了一个用于临场感机器人的人工嗅觉系统 ,用于气体的定性识别 .
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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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The self-organizing map is an artificial neural networks model and algorithm that implememts a characteristic nonliner projection from the high-dimensional space of signal data into a low-dimensional array of neurons in an orderly fashion, which is made by T. Kohonen. The mapping tends to preserve the topological relationships of signal domains. Owing to the order, the image of the signal space tends to manifest clusters of input information and their relationship on the map. The map...

The self-organizing map is an artificial neural networks model and algorithm that implememts a characteristic nonliner projection from the high-dimensional space of signal data into a low-dimensional array of neurons in an orderly fashion, which is made by T. Kohonen. The mapping tends to preserve the topological relationships of signal domains. Owing to the order, the image of the signal space tends to manifest clusters of input information and their relationship on the map. The map can be shown by square shades of gray, so it makes machinery operating conditions be visualized. The map will vary with changes of machinery operating conditions, which helps us to detect and identify the faults . 

自组织映射法是由T.Kohonen提出的一种人工神经网络模式,它能把高维的信息数据以有序方式映射到低维的网络上,形成一种拓扑意义上的有序图。由于其有序性,使得信号空间图成为许多输入信息及其关系的群落图。每个图可用灰度深浅不等的方块阴影图表示出来,这种可视的图形表示了机械运行的状态。人们可以非常直观地从图上判断机械运行状态,从而使得机械运行状态的监测和故障诊断更为简便。

The weight_value convergence of the self_organizing map(SOM) algorithm is discussed. At first, an objective function in the context of a continuous input is proposed. Using this objective function and the Robbins_Monro algorithm, it is proved that the weight value of SOM in the state of continuous input converges to a stationary value. This result is applicable to any finite_dimensional case.

研究了自组织映射 (SOM )算法的权值收敛性问题 ,提出了一个连续状态下的目标函数 ,由这个目标函数出发利用Robbins_Monro算法证明了连续状态下的自组织映射的权值将收敛到一个稳定值 ,其结果适应于任意有限维的情形

Firstly, this paper represents the necessity for the development of Aircraft Fault Diagnosis Expert System, and explains briefly on the knowledge substrate and the implementation of this system; and then introduces the advantage of the Case-Based Reasoning (CBR), the stress is laid on the source and structure of cases in this system; moreover, this article introduces in detail the Self Organizing Map (SOM), its realization of algorithm and schematic of program structure; finally analyses the extensive...

Firstly, this paper represents the necessity for the development of Aircraft Fault Diagnosis Expert System, and explains briefly on the knowledge substrate and the implementation of this system; and then introduces the advantage of the Case-Based Reasoning (CBR), the stress is laid on the source and structure of cases in this system; moreover, this article introduces in detail the Self Organizing Map (SOM), its realization of algorithm and schematic of program structure; finally analyses the extensive application prospect of this software.

首先提出了开发飞机故障诊断专家系统的必要性 ,并简要说明了笔者所研制的软件的知识基础和设计与实现方法 ;介绍了基于事例的推理 (Case BasedReasoning ,CBR)的优越性 ,重点说明了该软件中事例的来源和事例库的构造 ;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 ;最后分析了该软件广泛的应用前景。

 
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