Gauss-Brown模型,Gauss-Brown model英语短句,例句大全

Gauss-Brown模型,Gauss-Brown model
1)Gauss-Brown modelGauss-Brown模型
2)Brown modelBrown模型
1.Cole-Cole model and Brown model of spectrum induced polarization are introduced.介绍了频谱激电法中的Cole Cole模型和Brown模型。
3)Brown-Lander ModelBrown-Lander模型
4)Gauss modelGauss模型
1.Critical properties of the Gauss model on a type of hierarchical lattice;一种等级晶格上Gauss模型的临界性质
2.In this paper,using the renormalization-group transformation technique,the phase transition and critical properties of the modified Gauss model on a type of hierarchical lattice are studied,and its fixed points is K=b33 obtained.Gauss模型的自旋可以连续取值,因此,研究该模型的相变对于更好地理解铁磁体的临界性质具有十分重要的意义。
5)Gauss-Markov modelGauss-Markov模型
1.By examining the good property of the ridge estimate of parameter β in general Gauss-Markov model and comparison to the estimate outcome of,the lower bound of efficiencies least square estimate with respect to the ridge estimate is discussed.考察一般Gauss-Markov模型中未知参数向量β的岭估计的优良性质,在文献[1]提出的估计β~相对于估计β^的(相对)效率e(β~β^)下,进一步讨论了最小二乘估计(LSE)相对于岭估计的效率下界,得到更好的结果。
2.Gauss-Markov model is frequently used in multivariate data analysis and processing, and its parameter estimation is always a hot issue.Gauss-Markov模型是多元数据分析处理工作中常用的模型,其参数估计与筛选一直是研究的热点。
3.In this paper,based on analyzing ordinary ridge estimation properties,a new biased estimation of unknown parameters called combining ridge and principal component(CRPC)estimation is generat-ed for Gauss-Markov model by using the principal component estimation method.在分析岭估计缺陷的基础上,运用主成分估计方法,提出了测量平差Gauss-Markov模型参数的一个新的有偏估计,称为岭-主成分组合估计,在均方误差意义下讨论了岭-主成分组合估计的优良性质及其岭-主成分组合估计与岭估计、主成分估计的比较问题,讨论了岭-主成分组合估计中偏参数的选取问题,得到了许多重要结论。

英文短句/例句

1.GENERALIZED SHRUNKEN T-TYPE ESTIMATION IN GUASS-MARKOV MODELGauss-Markov模型的广义压缩t型估计
2.The Minimax Adimissibility of the Linear Prediction with the Gauss-markov Model under Quadratic Loss Function;二次损失下一般Gauss-Markov模型的线性预测的Minimax的可容许性
3.The Minimax Adimissibility of the Linear Estimator in the Gauss-markov Model under the Quadratic Function;二次损失下一般Gauss-Markov模型中可估函数的Minimax可容许性
4.An admissible estimate proof for the parameter ridge estimation in general Gauss-Markov;一般Gauss-Markov模型中参数岭估计的可容许性的一个证明
5.The linear minimax estimation of regression coefficient in a general Gauss-Markov Model under balanced loss function平衡损失下一般Gauss-Markov模型中回归系数的线性Minimax估计
6.The Analysis to Bifurcation of Critical Points of Gaussian Scale Space Model图像Gauss尺度空间模型的临界点分岔分析
7.APPLICATION OF THE IMPROVED GAUSS ELIMINATION METHOD TO ORE PREDICTION MODEL改进的Gauss消去法在成矿预测模型中的应用
8.Insurance funds' investment model and its Markov chain simulation保险资金投资模型及其Markov链模拟
9.Discrete Markov Models for Measurement of Clinical Compliance临床依从性测量的离散型Markov模型
10.Embedded Hidden Markov Model and Neural Network for Face Recognition;嵌入式隐Markov模型和神经网络人脸识别
11.Study on Cutting Process Monitoring System Based on Hidden Markov Model;基于隐Markov模型切削过程监测系统研究
12.Medical Image Denoising Based on Wavelet-domain Hidden Markov Tree;基于小波域隐Markov模型的医学图像去噪
13.Building the General Model of Customer Relationship Development with Markov Chain;用Markov链建立客户关系发展的一般模型
14.Mining the Course Scheduling Data with Markov Chain;课程数据分析的Markov链模型
15.The Information Retrieval Model Based on Markov Concept;基于Markov概念的信息检索模型
16.Classification of SAR Image Based on Pairwise Markov Random Field Model;SAR图像分类的双Markov随机场模型研究
17.Gait Recognition Using Hide Markov Model;基于隐Markov模型的步态识别
18.The Research on Latent Semantic Markov Network Retrieval Model;潜在语义的Markov网络检索模型的研究

相关短句/例句

Brown modelBrown模型
1.Cole-Cole model and Brown model of spectrum induced polarization are introduced.介绍了频谱激电法中的Cole Cole模型和Brown模型。
3)Brown-Lander ModelBrown-Lander模型
4)Gauss modelGauss模型
1.Critical properties of the Gauss model on a type of hierarchical lattice;一种等级晶格上Gauss模型的临界性质
2.In this paper,using the renormalization-group transformation technique,the phase transition and critical properties of the modified Gauss model on a type of hierarchical lattice are studied,and its fixed points is K=b33 obtained.Gauss模型的自旋可以连续取值,因此,研究该模型的相变对于更好地理解铁磁体的临界性质具有十分重要的意义。
5)Gauss-Markov modelGauss-Markov模型
1.By examining the good property of the ridge estimate of parameter β in general Gauss-Markov model and comparison to the estimate outcome of,the lower bound of efficiencies least square estimate with respect to the ridge estimate is discussed.考察一般Gauss-Markov模型中未知参数向量β的岭估计的优良性质,在文献[1]提出的估计β~相对于估计β^的(相对)效率e(β~β^)下,进一步讨论了最小二乘估计(LSE)相对于岭估计的效率下界,得到更好的结果。
2.Gauss-Markov model is frequently used in multivariate data analysis and processing, and its parameter estimation is always a hot issue.Gauss-Markov模型是多元数据分析处理工作中常用的模型,其参数估计与筛选一直是研究的热点。
3.In this paper,based on analyzing ordinary ridge estimation properties,a new biased estimation of unknown parameters called combining ridge and principal component(CRPC)estimation is generat-ed for Gauss-Markov model by using the principal component estimation method.在分析岭估计缺陷的基础上,运用主成分估计方法,提出了测量平差Gauss-Markov模型参数的一个新的有偏估计,称为岭-主成分组合估计,在均方误差意义下讨论了岭-主成分组合估计的优良性质及其岭-主成分组合估计与岭估计、主成分估计的比较问题,讨论了岭-主成分组合估计中偏参数的选取问题,得到了许多重要结论。
6)Gauss-markoff modelGauss-markoff模型