Experimental results show that the new method is better than the traditional SOFM algorithm and can...
实验表明此方法明显优于传统的SOFM算法，而且易于硬件实现。
An image fusion binarization method based on Selforganization Feature Map (SOFM) neural network is presented.
提出了一种基于自组织特征映射(SOFM)神经网络的图像融合二值化方法。
We use SOFM algorithm to train the samples clustering, and employ SVR respectively to predict the price trend of stock.
SOFM算法将训练样本聚类，然后分别应用SVR来预测股票价格走势。
The sample classification of abdomen MRI is carried out by the combining method of SOFM Neural network and doctors diagnosis.
将SOFM神经网络与医师诊断相结合对腹部MRI进行样本分类，并利用判别分析方法对肝硬化进行图像识别。
The fusion image using SVM method outperformed the fusion image using SOFM networks method in terms of classification accuracy.
在分类精度方面，基于SVM方法的融合影像明显优于基于自组织神经网络方法的融合影像。
The first level of our system employs the self-organizing feature map (SOFM) to map colors of image on a two dimensional feature map.
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。
A method that applies the clustering function of SOFM (Self-Organizing Feature Maps) network is proposed for autonomous star pattern recognition.
介绍了一种利用自组织特征映射(SOFM)网络的聚类功能进行全天星图识别的方法。
An autonomous star pattern recognition method using the tri-star clustering function of SOFM (Self-Organizing Feature Maps) network is described.
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。
The self-organizing feature map (SOFM) uses weight of network to present structure of the input data and has preferable ability of classification.
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 SOFM algorithm based on a neural network and an improved algorithm have a good effect on space compression of hyperspectral remote sensing images.
基于神经网络的SOFM算法及其改进算法取得较好的空间压缩效果，实现了对高光谱遥感图像的有效压缩。
Because the traditional SOFM often produce result with color distortion, it setting the map size with different length according to the complexity of images.
针对传统s OFM易产生色彩的映射畸变，根据彩色图像自身不同的复杂度自动选择不等边距的映射网络。
The combination of curvilinear component analysis (CCA) and self-organizing feature map (SOFM) were applied to a diagnosis for fault feature extraction of bearing.
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。
Nine major kinds of fault in electrical source system of surface-to-air missile have been diagnosed respectively through BP and SOFM neural network, and pleasing results are obtained.
针对地空导弹电源系统的九种主要故障，分别用BP神经网络和SOFM神经网络对其进行了故障诊断，均取得了较好的效果。
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.
对自组织特征映射神经网络的特性进行分析，并将其与矢量量化问题的实质进行比较，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.
对自组织特征映射神经网络的特性进行分析，并将其与矢量量化问题的实质进行比较，提出了一个实现矢量量化的自组织特征映射算法。
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