自组织神经网络,self-organizing neural network
1)self-organizing neural network自组织神经网络
1.A study of some problems in pattern recognition byself-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
bustion stability study based on statistic analysis andself-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 basedself-organizing neural network algorithm;一种改进的动态二叉树的自组织神经网络算法
英文短句/例句
1.A Research of the Speech Recognition Based on the SOM Model;基于自组织神经网络的语音识别研究
2.Application of Fuzzy Self-organizing Neural Network in Clustering;模糊自组织神经网络在聚类中的应用
3.A Study on Improved SASONN;一种改进的结构自适应自组织神经网络的研究
4.The Speech Recognition System Based on the HMMNN Model;基于HMM与自组织神经网络相结合的语音识别
panies Credit Assessment Model Based on Self-Organizing Feature Map Neural Network;基于SOM自组织神经网络的企业信用评估模型
6.Clustering Analysis Based on Evolutionary Tree-Structured SOM Network;基于进化树型自组织神经网络聚类分析
7.Self-organizing Map for Content-based Image Recognition;自组织神经网络实现基于内容的图片识别
8.Utilizing self-organizational neural network to predict reservoir extended limits of Huangchang Oilfield for increasing oil production;用自组织神经网络预测黄场油田储层扩边增产
9.Models of Self-Organizing Neural Network for the Evaluation of WatershedWater Resources Abundance;流域水资源丰富度评价的自组织神经网络模型
10.Research on a Self-Organizing Fuzzy Neural Networks Algorithm;一种自组织模糊神经网络算法的研究
11.Word Clustering Based on Self-Organizing Map;基于自组织映射神经网络的词自动聚类
12.Vector Quantization Based on Self Organizing Feature Map Neural Network基于自组织特征映射神经网络的矢量量化
13.A SELF-ORGANIZATION FUZZY CONTROLLER WITH FAM NEURAL NETWORKS具有模糊联想神经网络的自组织模糊控制器
14.The color feature parameters for wood surface of four common tree species in Northeast China were determined and compared.按颜色参数用自组织竞争神经网络进行了分类。
15.The Design and Application of Neural Networks Self-organizing Fuzzy Controller;神经网络自组织模糊控制器的设计及应用
16.Medical Image Segmentation Based on Self-Organizing Map;基于自组织特征映射神经网络的医学图像分割
17.The Intelligent Traffic Phase Control Based on Self-organizing Competitive ANN;基于自组织竞争神经网络的智能交通相位控制
18.Sort of Zoology City Basen on Self-organizing Feature Map Neural Network;基于自组织特征映射神经网络的生态城市分类
相关短句/例句
self-organized neural network自组织神经网络
1.Usingself-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 theself-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。
3)self-organizing neural networks自组织神经网络
1.According to the basic principle of theself-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 onself-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。
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-organization neural network自组织神经网络
1.The paper introduces a method to identify the log curve shape usingself-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。
6)self-organizing competitive neural network自组织竞争神经网络
1.On the basis of the artificial neural networks(ANN),aself-organizing competitive neural network model was developed and used for automation recognition of dynamometer cards and fault diagnosis for suck rod pumping system.5进行编程,应用相同的数据对BP神经网络模型和自组织竞争神经网络模型的识别效率进行了对比。
2.Then,a two-layerself-organizing competitive neural network was built.从ECT传感器的输出中提取特征参数作为软测量模型的辅助变量,两相流流型为主导变量,构建二级自组织竞争神经网络,进而实现对两相流流型的在线判别。
3.Twenty-one absorption peak data from the first three principal componment compressed from the original data by PLS were taken as inputs of theself-organizing competitive neural network.用PLS法对原始数据进行主成分压缩,采用自组织竞争神经网络建模。
延伸阅读
Hopfield神经网络模型Hopfield神经网络模型Hopfield neural network model收敛于稳定状态或Han加Ing距离小于2的极限环。上述结论保证了神经网络并行计算的收敛性。连续氏pfield神经网络中，各个神经元状态取值是连续的，由于离散H6pfield神经网络中的神经元与生物神经元的主要差异是:①生物神经元的I/O关系是连续的;②生物神经元由于存在时延，因此其动力学行为必须由非线性微分方程来描述。为此，在1984年J.J.H叩fi酗提出了连续氏pfield神经网络，它可用图1所示的电路实现，其动态方程┌───┐│·T叮 │└───┘图1连续F砧pfield神经网络(a)Sigmoid非线性;(b)神经元模型可由下述微分方程式描述: 、，产 门J/r、l、1.。瓮一客、一佘Ii认=f(u￡)￡=l，2，…，n式中f(·)为连续可微的Sign101d函数;T，j=兀、i，j=1，2，“’，n几=0]=i1~.吞~·‘八文一Q*+，戮T，j‘一‘，2，”一”连续时间氏pfield神经网络式的计算能量函数定义为:一告客客几从砚石l「Vi_1，、，合，，，+乞古!‘厂‘(x)dx一乙I，从(4)’月R‘Jo“‘、一’一月一，” 对于式(3)，若f一‘为单调增且连续，C>0，T，j=几(i，j=1，2，一，n)，则沿系统的运动轨道有dE一。-丁丁足之Uat当且仅当贷一。时 箭一。式(3)的稳定平衡点就是能量函数E〔式(4)」的极小点，反之亦然。同时，连续氏pfield神经网络式(3)以大规模非线性连续时间并行方式处理信息。网络的稳定平衡点对应于其计算能量函数E的极小点，网络的计算时间就是它到达稳定的时间，网络的计算在系统趋于稳态的过程中也就完成了。这也是式(3)用于神经计算及联想记忆的基本原理，也即神经计算机的基本原理。HoPfield shenling wangluo moxingHopfield神经网络模型(Hopfieldne，Ine幻即0比m侧触l)一种单层全反馈的人工神经网络模型(后称之为氏p玉idd模型)，它对推动人工神经网络研究的复苏起了很重要的作用。且，lield对人工神经网络研究的贡献主要有:(l)把有反馈的神经网络看作一个非线性动力系统，提出了系统的全局Lyap阴lov函数(或称能量函数)的概念，用于系统稳定性的分析;(2)利用上述分析方法解决人工智能中的组合优化问题，如15护;(3)给出了利用模拟电子线路实现的连续Hopfidd网络的电路模型，为进一步研究神经计算机创造了条件。
