1) hierarchical self organizing neural network
层次自组织神经网络
1.
This paper presents a hierarchical self organizing neural network model and its application in the learning of the trajectory distribution patterns for event recognition.
提出一个层次自组织神经网络模型 ,并将其应用于基于事件识别的轨迹分布模式学习中 。
2) self-organizing neural network
自组织神经网络
1.
A study of some problems in pattern recognition by self-organizing neural network;
对自组织神经网络模式识别方法中若干问题的研究
2.
Combustion stability study based on statistic analysis and self-organizing neural network;
基于统计分析和自组织神经网络的燃烧稳定性研究
3.
Improved dynamical binary-tree based self-organizing neural network algorithm;
一种改进的动态二叉树的自组织神经网络算法
3) self-organized neural network
自组织神经网络
1.
Using self-organized neural network in CRM;
自组织神经网络在CRM中的应用
2.
In this paper,an aggregation method is presented,in which the multi induction motors are classified into different types using the self-organized neural network and each type of motor is aggregated with a new steady state model equivalence method.
文中提出一种基于自组织神经网络对电动机进行分类、并针对同一类型的电动机采用稳态模型进行等值的聚合方法。
3.
It is prove that the Self-organized neural network based on Rough Set perform better both in learning and pattern recognition.
自组织神经网络在学习过程中采取竞争机制选取最优匹配神经元获胜,然而实际情况可能有一组神经元都非常匹配输入向量。
4) SOM
自组织神经网络
1.
The SVV algorithm is based on support vector machine(SVM) and self-organizing mapping(SOM).
该算法是在无监督的自组织神经网络(SOM)的可视化功能的基础上,结合监督学习的支持向量机(SVM)的二分类算法,得到能够直观地显示高维数据、二分类数据分类边界以及数据与分类边界距离的二维映射图,提高了分类结果的可解释性。
2.
According to these limitations,this paper presents an automated pattern classification method of Self-Organizing Map Neural Network(SOMNN) combining with Generalized Regression Neural Network(GRNN).
针对这些缺陷,提出一种非监督自组织神经网络(SOMNN)和监督的广义回归网络(GRNN)结合的全自动模式分类新方法。
3.
Self Organizing Feature Maps(SOM)has been used as a tool for data clustering and dimensionality reduction.
作为一种优良的聚类和降维工具,自组织神经网络SOM(SelfOrganizingFeatureMaps)已经得到广泛应用。
5) self-organizing neural networks
自组织神经网络
1.
According to the basic principle of the self-organizing neural networks, combining the 55 slopes data to be the example, applying the matlab, this paper built up the neural network of the processing model of slope s factors classification, and made use of the model to classify different slopes.
文章根据自组织神经网络的基本原理,结合55个边坡实例,应用matlab进行编程,建立了边坡影响因素分类处理的神经网络模型,并运用该模型对不同的边坡进行了分类,分类结果提高了神经网络的边坡指标数据的学习效率,从而证明了自组织神经网络对提高用于预测边坡稳定性神经网络性能的有效性。
2.
A speech recognition method, which is based on self-organizing neural networks is presented.
建立了一种基于自组织神经网络的语音识别系统。
3.
It is based on wavelet transform and LPC method to extract the character of speech signal and the Self-Organizing Neural Networks(NN).
该文设计并实现了一种基于小波变换和线性预测的语音信号特征提取方法 (DWT -LPC)和自组织神经网络的与文本有关的说话人识别系统。
6) self-organization neural network
自组织神经网络
1.
The paper introduces a method to identify the log curve shape using self-organization neural network.
这里介绍一种利用自组织神经网络识别曲线形态的方法。
补充资料：组织性层次
组织性层次
organizational levels
组织性层次(organizational levels)与技术性层次相区别的概念。管理系统中，指组织中各类管理人员的配备与分布，包括管理人员分布的层级与跨度。组织正是通过他们，才能把组织的计划、决策、目标及有关资料灌输到技术性层次中。 (孙俊山撰张史审)
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条