• 本文根据组织特征映射神经网络学习算法提出了CMOS实现电路

    According to a learning algorithm of self organizing neural network for mapping character, a CMOS implementation of its synaptic weight by circuit is presented in this paper.

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  • 第一结构使用组织特征映射神经网络SOFM)将像素映射平面

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

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  • 针对汽轮机转子故障分类问题采用模糊数学组织特征映射神经网络方法诊断汽轮机转子的故障。

    In the light of the problems involved in a steam turbine rotor fault diagnosis proposed in this paper is a new diagnostic method based on a fuzzy self organizing neural network.

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  • 本文应用多层前馈神经网络自组织特征映射神经网络分别简单目标复杂飞机目标进行分类识别。

    The classification of simple and complex objects is investigated using the multiple layer forward neural network and the self-organizing feature map network.

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  • 本文通过利用涌现自组织特征映射神经网络数据进行聚类分析通过无边界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.

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  • 本文简要介绍了自组织特征映射神经网络基本原理,利用原理土地复垦的条件分类进行了初步研究

    The paper briefly introduces the fundamentals of neural network of self-organizing feature map and on the basis of which discusses the classification of land reclamation conditions.

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  • 自组织特征映射神经网络特性进行分析将其与矢量量化问题实质进行比较,提出了一个实现矢量量化的自组织特征映射算法

    The characteristics of SOFM neural network is analysed and compared with the feature of Vector Quantizing problem in this paper. Based on this an algorithm for Vector Quantizing is put forward.

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  • 组织特征映射一种人工神经网络方法可以同时实现模式识别数据分类

    Self Organizing Map is a method of artificial neural network, which implements pattern recognition and data clustering simultaneously.

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  • 组织特征映射人工神经网络正常识别正确率达84.8% ,对脂肪肝的识别正确率达90 .9%。

    The neural network algorithm showed accuracy rate of 84.8% for normal liver and 90.9% for fatty liver.

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  • 本文研究了多层感知器径向函数网络学习向量量化网络组织特征映射网络四种神经网络回转窑火焰图像分割中的应用

    In this paper, four neural networks, i. e. multi layer perception, radial basis function, learning vector quantization and self organizing feature mapping, are used to segment the flame image.

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  • 组织特征映射(SOM)神经网络通过自组织有效地提取出特征参数内在特征映射分类模板可以用于各种模式识别问题

    Self organizing feature map (SOM) network can extract the internal features of parameter by self organizing and reflect them on the classified map. It can be used in problems of pattern recognition.

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  • 提出一种基于自组织特征映射(SOFM)神经网络图像融合二值方法

    An image fusion binarization method based on Selforganization Feature Map (SOFM) neural network is presented.

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  • 提出一种基于自组织特征映射(SOFM)神经网络图像融合二值方法

    An image fusion binarization method based on Selforganization Feature Map (SOFM) neural network is presented.

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