Linear octrees offer a volume representation of 3-D objects, which is quite compactand lends itself to traditional object processing operations. However, the linear octree structurefor generating the representation of...Linear octrees offer a volume representation of 3-D objects, which is quite compactand lends itself to traditional object processing operations. However, the linear octree structurefor generating the representation of 3-D objects from three orthogonal silhouettes by using thevolume intersection technique is dependent on viewpoints. The recognition achieved from match-ing object representations to model representations requires that the representations of objectsare independent of viewpoints. In order to obtain independent representations of viewpoints,the three principal axes of the object should be obtained from the moment of inertia matrix bycomputing its eigenvectors. The linear octree is projected onto the image planes of the three prin-cipal views (along the principal axes) to obtain the three normalized linear quadtrees. The objectmatching procedure has two phases: the first phase is to match the normalized linear quadtrees ofthe unknown object to a subset of models contained in a library utilizing a measure of symmetricdifference; the second phase is to generate the normalized linear octrees of the object and theseselected models and then to match the normalized linear octree of the unknown object with themodel having the minimum symmetric difference.展开更多
In this paper, the normal Luenberger function observer design for second-order descriptor linear systems is considered. It is shown that the main procedure of the design is to solve a so-called second-order generalize...In this paper, the normal Luenberger function observer design for second-order descriptor linear systems is considered. It is shown that the main procedure of the design is to solve a so-called second-order generalized Sylvester-observer matrix equation. Based on an explicit parametric solution to this equation, a parametric solution to the normal Luenberger function observer design problem is given. The design degrees of freedom presented by explicit parameters can be further utilized to achieve some additional design requirements.展开更多
This paper proposes a method of simultaneous determination of the four layer parameters （mass density, longitudinal velocity, the thickness and attenuation） of an immersed linear-viscoelastic thin layer by using the...This paper proposes a method of simultaneous determination of the four layer parameters （mass density, longitudinal velocity, the thickness and attenuation） of an immersed linear-viscoelastic thin layer by using the normally-incident reflected and transmitted ultrasonic waves. The analytical formula of the layer thickness related to the measured trans- mitted transfer functions is derived. The two determination steps of the four layer parameters are developed, in which acoustic impedance, time-of-flight and attenuation are first determined by the reflected transfer functions. Using the derived formula, it successively calculates and determines the layer thickness, longitudinal velocity and mass density by the measured transmitted transfer functions. According to the two determination steps, a more feasible and simplified measurement setups is described. It is found that only three signals （the reference waves, the reflected and transmitted waves） need to be recorded in the whole measurement for the determination of the four layer parameters. A study of the stability of the determination method against the experimental noises and the error analysis of the four layer parameters are made. This study lays the theoretical foundation of the practical measurement of a linear-viscoelastic thin layer.展开更多
We study the quasi likelihood equation in Generalized Linear Models（GLM） with adaptive design ∑（i=1）^n xi（yi-h（x＇iβ））=0, where yi is a q=vector, and xi is a p×q random matrix. Under some assumptions, i...We study the quasi likelihood equation in Generalized Linear Models（GLM） with adaptive design ∑（i=1）^n xi（yi-h（x＇iβ））=0, where yi is a q=vector, and xi is a p×q random matrix. Under some assumptions, it is shown that the Quasi- Likelihood equation for the GLM has a solution which is asymptotic normal.展开更多
Consider the model Yt = βYt-1＋g（Yt-2）＋εt for 3 〈 t 〈 T. Hereg is anunknown function, β is an unknown parameter, εt are i.i.d, random errors with mean 0 andvariance σ2 and the fourth moment α4, and α4 are ...Consider the model Yt = βYt-1＋g（Yt-2）＋εt for 3 〈 t 〈 T. Hereg is anunknown function, β is an unknown parameter, εt are i.i.d, random errors with mean 0 andvariance σ2 and the fourth moment α4, and α4 are independent of Y8 for all t ≥ 3 and s = 1, 2.Pseudo-LS estimators σ, σ2T α4τ and D2T of σ^2,α4 and Var（ε2↑3） are respectively constructedbased on piecewise polynomial approximator of g. The weak consistency of α4T and D2T are proved. The asymptotic normality of σ2T is given, i.e., √T（σ2T -σ^2）/DT converges indistribution to N（0, 1）. The result can be used to establish large sample interval estimatesof σ^2 or to make large sample tests for σ^2.展开更多
Generalized linear mixed models (GLMMs) are typically constructed by incorporating random effects into the linear predictor. The random effects are usually assumed to be normally distributed with mean zero and varianc...Generalized linear mixed models (GLMMs) are typically constructed by incorporating random effects into the linear predictor. The random effects are usually assumed to be normally distributed with mean zero and variance-covariance identity matrix. In this paper, we propose to release random effects to non-normal distributions and discuss how to model the mean and covariance structures in GLMMs simultaneously. Parameter estimation is solved by using Quasi-Monte Carlo (QMC) method through iterative Newton-Raphson (NR) algorithm very well in terms of accuracy and stabilization, which is demonstrated by real binary salamander mating data analysis and simulation studies.展开更多
Medical research data are often skewed and heteroscedastic. It has therefore become practice to log-transform data in regression analysis, in order to stabilize the variance. Regression analysis on log-transformed dat...Medical research data are often skewed and heteroscedastic. It has therefore become practice to log-transform data in regression analysis, in order to stabilize the variance. Regression analysis on log-transformed data estimates the relative effect, whereas it is often the absolute effect of a predictor that is of interest. We propose a maximum likelihood (ML)-based approach to estimate a linear regression model on log-normal, heteroscedastic data. The new method was evaluated with a large simulation study. Log-normal observations were generated according to the simulation models and parameters were estimated using the new ML method, ordinary least-squares regression (LS) and weighed least-squares regression (WLS). All three methods produced unbiased estimates of parameters and expected response, and ML and WLS yielded smaller standard errors than LS. The approximate normality of the Wald statistic, used for tests of the ML estimates, in most situations produced correct type I error risk. Only ML and WLS produced correct confidence intervals for the estimated expected value. ML had the highest power for tests regarding β1.展开更多
In this paper, based on the invariant subspace theory and adjoint operator concept of linear operator, a new matrix representation method is proposed to calculate the normal forms of n order general nonlinear dyna...In this paper, based on the invariant subspace theory and adjoint operator concept of linear operator, a new matrix representation method is proposed to calculate the normal forms of n order general nonlinear dynamic systems. In the method, there is no need to determine the structure of the class of normal forms in advance. Because the subspace is not related to the dimensions of the system and the order of the normal forms directly, it is determined only by a given vector field. So the normal forms with high orders and dimensions can be calculated by the method without difficulties. In this paper, is used the method for selecting the minimal subspace and solving homological equations in the subspace, the examples show that the method is very effective.展开更多
典型的无网格方法采用移动最小二乘函数(moving least squares,MLS)作为近似函数,但由于MLS不具备Kronecker delta函数性质,本质边界施加困难。LRPIM是采用径向基点插值形函数的无网格方法,本质边界条件无需特殊处理,可以直接施加,在保...典型的无网格方法采用移动最小二乘函数(moving least squares,MLS)作为近似函数,但由于MLS不具备Kronecker delta函数性质,本质边界施加困难。LRPIM是采用径向基点插值形函数的无网格方法,本质边界条件无需特殊处理,可以直接施加,在保持高精度的前提下提高计算效率。将LRPIM应用于机械结合面接触问题的计算。根据位移连续条件推导了含接触特性的线性互补方程,建立了基于LRPIM的计算模型,采用线性互补算法利用数值积分计算了几种典型的接触问题,得到了接触面压力分布和接触变形,分析了插值函数形状参数和积分域尺寸对计算结果的影响。研究结果表明,插值函数形状参数α_(c)对接触力的影响较小,而形状参数q取-0.5~1.2时有较好的收敛效果;积分域无量纲尺寸a_(qx)、a_(qy)大于1.5时计算结果开始收敛,大于2.5时出现发散现象,取值2.1时收敛效果最佳。将计算结果与已有结果进行比较,表明本研究方法有较高的求解精度。展开更多
In order to reveal the complex network characteristics and evolution principle of China aviation network, the probability distribution and evolution trace of average degree of edge vertices of China aviation network w...In order to reveal the complex network characteristics and evolution principle of China aviation network, the probability distribution and evolution trace of average degree of edge vertices of China aviation network were studied based on the statistics data of China civil aviation network in 1988, 1994, 2001, 2008 and 2015. According to the theory and method of complex network, the network system was constructed with the city where the airport was located as the network node and the route between cities as the edge of the network. Based on the statistical data, the average degrees of edge vertices in China aviation network in 1988, 1994, 2001, 2008 and 2015 were calculated. Using the probability statistical analysis method and regression analysis approach, it was found that the average degree of edge vertices had the probability distribution of normal function and the position parameters and scale parameters of the probability distribution had linear evolution trace.展开更多
现有分阶段解码的实体关系抽取模型仍存在着阶段间特征融合不充分的问题,会增大曝光偏差对抽取性能的影响。为此,提出一种双关系预测和特征融合的实体关系抽取模型(entity relation extraction model with dual relation prediction and...现有分阶段解码的实体关系抽取模型仍存在着阶段间特征融合不充分的问题,会增大曝光偏差对抽取性能的影响。为此,提出一种双关系预测和特征融合的实体关系抽取模型(entity relation extraction model with dual relation prediction and feature fusion,DRPFF),该模型使用预训练的基于Transformer的双向编码表示模型(bidirectional encoder representation from transformers,BERT)对文本进行编码,并设计两阶段的双关系预测结构来减少抽取过程中错误三元组的生成。在阶段间通过门控线性单元(gated linear unit,GLU)和条件层规范化(conditional layer normalization,CLN)组合的结构来更好地融合实体之间的特征。在NYT和WebNLG这2个公开数据集上的试验结果表明,该模型相较于基线方法取得了更好的效果。展开更多
文摘Linear octrees offer a volume representation of 3-D objects, which is quite compactand lends itself to traditional object processing operations. However, the linear octree structurefor generating the representation of 3-D objects from three orthogonal silhouettes by using thevolume intersection technique is dependent on viewpoints. The recognition achieved from match-ing object representations to model representations requires that the representations of objectsare independent of viewpoints. In order to obtain independent representations of viewpoints,the three principal axes of the object should be obtained from the moment of inertia matrix bycomputing its eigenvectors. The linear octree is projected onto the image planes of the three prin-cipal views (along the principal axes) to obtain the three normalized linear quadtrees. The objectmatching procedure has two phases: the first phase is to match the normalized linear quadtrees ofthe unknown object to a subset of models contained in a library utilizing a measure of symmetricdifference; the second phase is to generate the normalized linear octrees of the object and theseselected models and then to match the normalized linear octree of the unknown object with themodel having the minimum symmetric difference.
基金This work was supported by National Natural Science Foundation of China(No.60710002)Program for Changjiang Scholars and Innovative Research Team in University(PCSIRT).
文摘In this paper, the normal Luenberger function observer design for second-order descriptor linear systems is considered. It is shown that the main procedure of the design is to solve a so-called second-order generalized Sylvester-observer matrix equation. Based on an explicit parametric solution to this equation, a parametric solution to the normal Luenberger function observer design problem is given. The design degrees of freedom presented by explicit parameters can be further utilized to achieve some additional design requirements.
基金supported by the National Natural Science Foundation of China (Grant Nos. 10534040 and 40674059)the State Key Laboratory of Acoustics (IACAS) (Grant No. 200807)
文摘This paper proposes a method of simultaneous determination of the four layer parameters （mass density, longitudinal velocity, the thickness and attenuation） of an immersed linear-viscoelastic thin layer by using the normally-incident reflected and transmitted ultrasonic waves. The analytical formula of the layer thickness related to the measured trans- mitted transfer functions is derived. The two determination steps of the four layer parameters are developed, in which acoustic impedance, time-of-flight and attenuation are first determined by the reflected transfer functions. Using the derived formula, it successively calculates and determines the layer thickness, longitudinal velocity and mass density by the measured transmitted transfer functions. According to the two determination steps, a more feasible and simplified measurement setups is described. It is found that only three signals （the reference waves, the reflected and transmitted waves） need to be recorded in the whole measurement for the determination of the four layer parameters. A study of the stability of the determination method against the experimental noises and the error analysis of the four layer parameters are made. This study lays the theoretical foundation of the practical measurement of a linear-viscoelastic thin layer.
文摘We study the quasi likelihood equation in Generalized Linear Models（GLM） with adaptive design ∑（i=1）^n xi（yi-h（x＇iβ））=0, where yi is a q=vector, and xi is a p×q random matrix. Under some assumptions, it is shown that the Quasi- Likelihood equation for the GLM has a solution which is asymptotic normal.
基金Supported by the National Natural Science Foundation of China（60375003） Supported by the Chinese Aviation Foundation（03153059）
文摘Consider the model Yt = βYt-1＋g（Yt-2）＋εt for 3 〈 t 〈 T. Hereg is anunknown function, β is an unknown parameter, εt are i.i.d, random errors with mean 0 andvariance σ2 and the fourth moment α4, and α4 are independent of Y8 for all t ≥ 3 and s = 1, 2.Pseudo-LS estimators σ, σ2T α4τ and D2T of σ^2,α4 and Var（ε2↑3） are respectively constructedbased on piecewise polynomial approximator of g. The weak consistency of α4T and D2T are proved. The asymptotic normality of σ2T is given, i.e., √T（σ2T -σ^2）/DT converges indistribution to N（0, 1）. The result can be used to establish large sample interval estimatesof σ^2 or to make large sample tests for σ^2.
文摘Generalized linear mixed models (GLMMs) are typically constructed by incorporating random effects into the linear predictor. The random effects are usually assumed to be normally distributed with mean zero and variance-covariance identity matrix. In this paper, we propose to release random effects to non-normal distributions and discuss how to model the mean and covariance structures in GLMMs simultaneously. Parameter estimation is solved by using Quasi-Monte Carlo (QMC) method through iterative Newton-Raphson (NR) algorithm very well in terms of accuracy and stabilization, which is demonstrated by real binary salamander mating data analysis and simulation studies.
文摘Medical research data are often skewed and heteroscedastic. It has therefore become practice to log-transform data in regression analysis, in order to stabilize the variance. Regression analysis on log-transformed data estimates the relative effect, whereas it is often the absolute effect of a predictor that is of interest. We propose a maximum likelihood (ML)-based approach to estimate a linear regression model on log-normal, heteroscedastic data. The new method was evaluated with a large simulation study. Log-normal observations were generated according to the simulation models and parameters were estimated using the new ML method, ordinary least-squares regression (LS) and weighed least-squares regression (WLS). All three methods produced unbiased estimates of parameters and expected response, and ML and WLS yielded smaller standard errors than LS. The approximate normality of the Wald statistic, used for tests of the ML estimates, in most situations produced correct type I error risk. Only ML and WLS produced correct confidence intervals for the estimated expected value. ML had the highest power for tests regarding β1.
文摘In this paper, based on the invariant subspace theory and adjoint operator concept of linear operator, a new matrix representation method is proposed to calculate the normal forms of n order general nonlinear dynamic systems. In the method, there is no need to determine the structure of the class of normal forms in advance. Because the subspace is not related to the dimensions of the system and the order of the normal forms directly, it is determined only by a given vector field. So the normal forms with high orders and dimensions can be calculated by the method without difficulties. In this paper, is used the method for selecting the minimal subspace and solving homological equations in the subspace, the examples show that the method is very effective.
文摘典型的无网格方法采用移动最小二乘函数(moving least squares,MLS)作为近似函数,但由于MLS不具备Kronecker delta函数性质,本质边界施加困难。LRPIM是采用径向基点插值形函数的无网格方法,本质边界条件无需特殊处理,可以直接施加,在保持高精度的前提下提高计算效率。将LRPIM应用于机械结合面接触问题的计算。根据位移连续条件推导了含接触特性的线性互补方程,建立了基于LRPIM的计算模型,采用线性互补算法利用数值积分计算了几种典型的接触问题,得到了接触面压力分布和接触变形,分析了插值函数形状参数和积分域尺寸对计算结果的影响。研究结果表明,插值函数形状参数α_(c)对接触力的影响较小,而形状参数q取-0.5~1.2时有较好的收敛效果;积分域无量纲尺寸a_(qx)、a_(qy)大于1.5时计算结果开始收敛,大于2.5时出现发散现象,取值2.1时收敛效果最佳。将计算结果与已有结果进行比较,表明本研究方法有较高的求解精度。
文摘In order to reveal the complex network characteristics and evolution principle of China aviation network, the probability distribution and evolution trace of average degree of edge vertices of China aviation network were studied based on the statistics data of China civil aviation network in 1988, 1994, 2001, 2008 and 2015. According to the theory and method of complex network, the network system was constructed with the city where the airport was located as the network node and the route between cities as the edge of the network. Based on the statistical data, the average degrees of edge vertices in China aviation network in 1988, 1994, 2001, 2008 and 2015 were calculated. Using the probability statistical analysis method and regression analysis approach, it was found that the average degree of edge vertices had the probability distribution of normal function and the position parameters and scale parameters of the probability distribution had linear evolution trace.
文摘现有分阶段解码的实体关系抽取模型仍存在着阶段间特征融合不充分的问题,会增大曝光偏差对抽取性能的影响。为此,提出一种双关系预测和特征融合的实体关系抽取模型(entity relation extraction model with dual relation prediction and feature fusion,DRPFF),该模型使用预训练的基于Transformer的双向编码表示模型(bidirectional encoder representation from transformers,BERT)对文本进行编码,并设计两阶段的双关系预测结构来减少抽取过程中错误三元组的生成。在阶段间通过门控线性单元(gated linear unit,GLU)和条件层规范化(conditional layer normalization,CLN)组合的结构来更好地融合实体之间的特征。在NYT和WebNLG这2个公开数据集上的试验结果表明,该模型相较于基线方法取得了更好的效果。
