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- A new discriminant analysis method based on LWT(Lifting Wavelet Transform) and LVQ(Learning Vector Quantization) Network was proposed in this paper. 提出了一种基于提升小波变换（LWT）和学习矢量量化网络（LVQ）相结合的鉴别分析方法。
- Three learning vector quantization(LVQ) networks with same structure corresponding to three kinds of stimulations were built for the predictive classification of the EEG signals. 对应3种刺激方式建立3个相同结构的学习向量量化(LVQ)神经网络,用于对脑电信号的预分类;
- The principle of fuzzy vector quantization (FVQ) for image coding is discussed in this paper, and an exponential fuzzy learning vector quantization algorithm (EFLVQ) is proposed. 本文分析了模糊矢量量化(FVQ)图像编码的原理，提出了一种指数型模糊学习矢量量化算法(EFLVQ)。
- Nicolaos B. Karayiannis, An axiomatic approach to soft learning vector quantization and clustering, IEEE Trans on Neural Networks, vol. 10, pp1153-1165, 1999. 孔祥为;李国平;"动态模糊矢量量化算法";2000年第5卷(A)655-659页.
- N.B. Karayiannis, Pin-I Pai and Nicholas Zervos, Fuzzy algorithms for learning vector quantization, IEEE Trans on Neural Networks, vol.7, pp.1196-1211, 1996. 张基宏;李霞;谢维信;"一种随机竞争学习矢量量化图像编码算法";2000年第28卷第10期33-36页.
- This method combines a genetic algorithm with an artificial neural network classifier, such as back-propagation( BP) neural classifier, radial basis function( RBF) classifier or learning vector quantization( LVQ) classifier. 此方法结合基因演算法与类神经分类器，如倒传递分类器、射基底函数分类器以及学习矢量量化分类器。
- This method combines a genetic algorithm with an artificial neural network classifier, such as back-propagation (BP) neural classifier, radial basis function (RBF) classifier or learning vector quantization (LVQ) classifier. 此方法结合基因演算法与类神经分类器，如倒传递分类器、放射基底函数分类器以及学习矢量量化分类器。
- learning vector quantization (LVQ) neural network 学习向量量化神经网络（LVQ）
- learning vector quantization network 学习矢量量化神经网络
- learning vector quantization neural network 学习矢量量化神经网络
- LVQ (Learning Vector Quantization) 学习矢量量化
- Learning Vector Quantization (LVQ) 学习向量量化
- Learning Vector Quantization Network(LVQ) 学习矢量量化网络
- Learning Vector Quantization(LVQ) 学习矢量量化（LVQ）
- Batch fuzzy learn vector quantization 批量模糊学习矢量量化
- The data space was mapped to high dimension feature space with Mercer kernel function, and fuzzy kernel learning vector quantization (FKLVQ) was done on the feature space to obtain the effective and stable clustering weight vectors. 该方法通过Mercer核,将数据空间映射到高维特征空间,并在此特征空间上进行FKLVQ学习获取数据空间有效且稳定的聚类权矢量,然后在特征空间和输出空间上仅针对各空间的数据样本和它们各自的聚类权矢量进行Sammon非线性核映射。
- A New Initial Codebook Algorithm of Learning Vector Quantization 新的学习矢量量化初始码书算法
- Recognition of cancerous stomach tissues by artificial learning vector quantization neural network 学习向量量化神经网络用于胃癌组织样品分类识别的研究
- A Stochastic Competitive Learning Vector Quantization Algorithm for Image Coding 一种随机竞争学习矢量量化图像编码算法
- Seafloor Classification from Multibeam Backscatter Data Using Learning Vector Quantization Neural Network 学习向量量化神经网络在多波束底质分类中的应用研究
