PNN network; LVQ network; SOM network; the non-asbestos gaskets; classification;
PNN神经网络；LVQ神经网络；SOM神经网络；非石棉垫片； 分类；
This paper proposes a face recognition method based on PCA and LVQ neural networks.
提出利用主元分析（PCA）和学习矢量量化神经网络（LVQ）相结合的方法进行人脸识别。
Tongue color automatic classification, based on LVQ neural networks classifier, is proposed in this paper.
本文基于学习矢量量化（LVQ）神经网络分类器，实现了舌象分析中的舌色、苔色自动分类。
By comparison, LVQ network was better than the others in classification ability and training cost, and PNN network in computation load and easy use.
比较而言，学习矢量量化网络在分类能力和训练成本方面更胜一筹，而概率神经网络则在计算负载和易用性方面更好一些。
By comparison, LVQ network and PNN network are better than BPN network in classification ability, and PNN network is better than the others in computation load.
比较而言，学习矢量量化网络和概率神经网络在分类能力方面要比反向传播网络好一些，概率神经网络在计算负载方面比学习矢量量化网络要更胜一筹。
The mean accurate rate of recognition of the LVQ neural network would be different, as the input vectors comtained different kind of FTIR characteristic frequencies.
作为输入的FTIR特征谱峰不同时，则网络的平均分类识别正确率也不同。
To solve these problems, based on minimizing the increment of learning errors and combining LVQ and GNG, the authors propose a new growing LVQ method and apply it to text classification.
针对这些问题，基于最小化学习误差的增量思想，该文将学习型矢量量化（LVQ）和生长型神经气（GNG）结合起来提出一种新的增量学习型矢量量化方法，并将其应用到文本分类中。
Objective: to investigate the potential of learning vector quantization (LVQ) artificial neural network tools for discrimination and forecasting of occurrent intensity of typhoid and paratyphoid.
目的：探讨学习矢量量化(LVQ)人工神经网络在伤寒、副伤寒发生强度判别与预测中的应用。
Absrtact: By considering the error rates and the training speed of neural networks, a hierarchical classifiers which is called as BP - LVQ neural network combination model is proposed in this paper.
摘要：综合考虑神经网络分类误差率以及训练速率，文中从组合分类器结构出发，提出一种树形多层的BP—LV Q神经网络组合分类器模型。
Absrtact: By considering the error rates and the training speed of neural networks, a hierarchical classifiers which is called as BP - LVQ neural network combination model is proposed in this paper.
摘要：综合考虑神经网络分类误差率以及训练速率，文中从组合分类器结构出发，提出一种树形多层的BP—LV Q神经网络组合分类器模型。
应用推荐