A method of real-time data smoothness which is applied in a hardware-in-the-loop （HIL） simulation platform for a plug-in hybrid electric vehicle synthetical power device is described. The input signal of the platfor...A method of real-time data smoothness which is applied in a hardware-in-the-loop （HIL） simulation platform for a plug-in hybrid electric vehicle synthetical power device is described. The input signal of the platform comes from a AC/DC switch power with output containing noises. A linear slide average arithmetic is applied to smooth the noises. To average a certain number input sample signals, this method can decrease the noises voltage level, which meet the requirement of the simulation platform. The efficiency and signal delay time are presented to describe the result of this method, and a statistical index is used to judge the arithmetic＇ s efficiency. The tests results show that the arithmetic fit the requirement of the HIL simulation platform.展开更多
In the present paper,a new criterion is derived to obtain the optimum fitting curve while using Cubic B-spline basis functions to remove the statistical noise in the spectroscopic data.In this criterion,firstly,smooth...In the present paper,a new criterion is derived to obtain the optimum fitting curve while using Cubic B-spline basis functions to remove the statistical noise in the spectroscopic data.In this criterion,firstly,smoothed fitting curves using Cubic B-spline basis functions are selected with the increasing knot number.Then,the best fitting curves are selected according to the value of the minimum residual sum of squares(RSS)of two adjacent fitting curves.In the case of more than one best fitting curves,the authors use Reinsch's first condition to find a better one.The minimum residual sum of squares(RSS)of fitting curve with noisy data is not recommended as the criterion to determine the best fitting curve,because this value decreases to zero as the number of selected channels increases and the minimum value gives no smoothing effect.Compared with Reinsch's method,the derived criterion is simple and enables the smoothing conditions to be determined automatically without any initial input parameter.With the derived criterion,the satisfactory result was obtained for the experimental spectroscopic data to remove the statistical noise using Cubic B-spline basis functions.展开更多
This paper proposes a Graph regularized Lpsmooth non-negative matrix factorization(GSNMF) method by incorporating graph regularization and L_p smoothing constraint, which considers the intrinsic geometric information ...This paper proposes a Graph regularized Lpsmooth non-negative matrix factorization(GSNMF) method by incorporating graph regularization and L_p smoothing constraint, which considers the intrinsic geometric information of a data set and produces smooth and stable solutions. The main contributions are as follows: first, graph regularization is added into NMF to discover the hidden semantics and simultaneously respect the intrinsic geometric structure information of a data set. Second,the Lpsmoothing constraint is incorporated into NMF to combine the merits of isotropic(L_2-norm) and anisotropic(L_1-norm)diffusion smoothing, and produces a smooth and more accurate solution to the optimization problem. Finally, the update rules and proof of convergence of GSNMF are given. Experiments on several data sets show that the proposed method outperforms related state-of-the-art methods.展开更多
The receiver operating characteristic (ROC) curve has been widely used in scientific research fields. After using the random hot deck imputation, we propose the smoothed empirical likelihood ratio statistic for the RO...The receiver operating characteristic (ROC) curve has been widely used in scientific research fields. After using the random hot deck imputation, we propose the smoothed empirical likelihood ratio statistic for the ROC curve with missing data. Its asymptotic distribution is a scaled chi-square distribution and empirical likelihood confidence intervals for ROC curves are constructed. The simulation study shows that the proposed interval estimates perform well based on the coverage probability for different sample sizes and response rates.展开更多
针对相对重力观测过程中可能受到环境等因素影响而出现高频信号和局部异常的情况,以2021年漾濞6.4级地震前重力变化为例,通过时空平滑约束重构重力变化数据,对比重构前后重力变化情况。基于球坐标系下六面体模型模拟场源体介质,反演场...针对相对重力观测过程中可能受到环境等因素影响而出现高频信号和局部异常的情况,以2021年漾濞6.4级地震前重力变化为例,通过时空平滑约束重构重力变化数据,对比重构前后重力变化情况。基于球坐标系下六面体模型模拟场源体介质,反演场源视密度变化,分析场源区介质密度演化特征。结果显示:观测数据经过时空平滑重构后,在不改变总体变化趋势的情况下,标准差由17.86×10-8 m/s 2降到8.99×10-8 m/s 2,变化值区间从(-74.20~66.28)×10-8 m/s 2降到(-21.79~27.70)×10-8 m/s 2,数据离散程度得到有效压缩,并能压制高频信号和局部噪声,孕震区域内重力变化时空演化趋势更加连续,便于异常特征的识别。场源区视密度变化显示有一个明显的NW-SE向物质迁移过程,在经过震中位置后逐渐收缩,在震中位置形成一个“孤岛”形态。孕震过程中正负变化分界线从SW-NE向转为NW-SE向,在分界线与构造走向一致后随即发震。展开更多
Meshed surfaces are ubiquitous in digital geometry processing and computer graphics. The set of attributes associated with each vertex such as the vertex locations, curvature, temperature, pressure or saliency, can be...Meshed surfaces are ubiquitous in digital geometry processing and computer graphics. The set of attributes associated with each vertex such as the vertex locations, curvature, temperature, pressure or saliency, can be recognized as data living on mani- fold surfaces. So interpolation and approximation for these data are of general interest. This paper presents two approaches for mani- fold data interpolation and approximation through the properties of Laplace-Beltrami operator （Laplace operator defined on a mani- fold surface）. The first one is to use Laplace operator minimizing the membrane energy of a scalar function defined on a manifold. The second one is to use bi-Laplace operator minimizing the thin plate energy of a scalar function defined on a manifold. These two approaches can process data living on high genus meshed surfaces. The approach based on Laplace operator is more suitable for manifold data approximation and can be applied manifold data smoothing, while the one based on bi-Laplace operator is more suit- able for manifold data interpolation and can be applied image extremal envelope computation. All the application examples demon- strate that our procedures are robust and efficient.展开更多
文摘A method of real-time data smoothness which is applied in a hardware-in-the-loop （HIL） simulation platform for a plug-in hybrid electric vehicle synthetical power device is described. The input signal of the platform comes from a AC/DC switch power with output containing noises. A linear slide average arithmetic is applied to smooth the noises. To average a certain number input sample signals, this method can decrease the noises voltage level, which meet the requirement of the simulation platform. The efficiency and signal delay time are presented to describe the result of this method, and a statistical index is used to judge the arithmetic＇ s efficiency. The tests results show that the arithmetic fit the requirement of the HIL simulation platform.
基金Supported by the Science and Technology Development Fund of Macao(China)grant(No.042/2007/A3,No.003/2008/A1)partly supported by NSFC Project(No.10631080)National Key Basic Research Project of China grant(No.2004CB318000)
文摘In the present paper,a new criterion is derived to obtain the optimum fitting curve while using Cubic B-spline basis functions to remove the statistical noise in the spectroscopic data.In this criterion,firstly,smoothed fitting curves using Cubic B-spline basis functions are selected with the increasing knot number.Then,the best fitting curves are selected according to the value of the minimum residual sum of squares(RSS)of two adjacent fitting curves.In the case of more than one best fitting curves,the authors use Reinsch's first condition to find a better one.The minimum residual sum of squares(RSS)of fitting curve with noisy data is not recommended as the criterion to determine the best fitting curve,because this value decreases to zero as the number of selected channels increases and the minimum value gives no smoothing effect.Compared with Reinsch's method,the derived criterion is simple and enables the smoothing conditions to be determined automatically without any initial input parameter.With the derived criterion,the satisfactory result was obtained for the experimental spectroscopic data to remove the statistical noise using Cubic B-spline basis functions.
基金supported by the National Natural Science Foundation of China(61702251,61363049,11571011)the State Scholarship Fund of China Scholarship Council(CSC)(201708360040)+3 种基金the Natural Science Foundation of Jiangxi Province(20161BAB212033)the Natural Science Basic Research Plan in Shaanxi Province of China(2018JM6030)the Doctor Scientific Research Starting Foundation of Northwest University(338050050)Youth Academic Talent Support Program of Northwest University
文摘This paper proposes a Graph regularized Lpsmooth non-negative matrix factorization(GSNMF) method by incorporating graph regularization and L_p smoothing constraint, which considers the intrinsic geometric information of a data set and produces smooth and stable solutions. The main contributions are as follows: first, graph regularization is added into NMF to discover the hidden semantics and simultaneously respect the intrinsic geometric structure information of a data set. Second,the Lpsmoothing constraint is incorporated into NMF to combine the merits of isotropic(L_2-norm) and anisotropic(L_1-norm)diffusion smoothing, and produces a smooth and more accurate solution to the optimization problem. Finally, the update rules and proof of convergence of GSNMF are given. Experiments on several data sets show that the proposed method outperforms related state-of-the-art methods.
文摘The receiver operating characteristic (ROC) curve has been widely used in scientific research fields. After using the random hot deck imputation, we propose the smoothed empirical likelihood ratio statistic for the ROC curve with missing data. Its asymptotic distribution is a scaled chi-square distribution and empirical likelihood confidence intervals for ROC curves are constructed. The simulation study shows that the proposed interval estimates perform well based on the coverage probability for different sample sizes and response rates.
文摘针对相对重力观测过程中可能受到环境等因素影响而出现高频信号和局部异常的情况,以2021年漾濞6.4级地震前重力变化为例,通过时空平滑约束重构重力变化数据,对比重构前后重力变化情况。基于球坐标系下六面体模型模拟场源体介质,反演场源视密度变化,分析场源区介质密度演化特征。结果显示:观测数据经过时空平滑重构后,在不改变总体变化趋势的情况下,标准差由17.86×10-8 m/s 2降到8.99×10-8 m/s 2,变化值区间从(-74.20~66.28)×10-8 m/s 2降到(-21.79~27.70)×10-8 m/s 2,数据离散程度得到有效压缩,并能压制高频信号和局部噪声,孕震区域内重力变化时空演化趋势更加连续,便于异常特征的识别。场源区视密度变化显示有一个明显的NW-SE向物质迁移过程,在经过震中位置后逐渐收缩,在震中位置形成一个“孤岛”形态。孕震过程中正负变化分界线从SW-NE向转为NW-SE向,在分界线与构造走向一致后随即发震。
基金Supported by National Natural Science Foundation of China (No.61202261,No.61173102)NSFC Guangdong Joint Fund(No.U0935004)Opening Foundation of Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education of China(No.93K172012K02)
文摘Meshed surfaces are ubiquitous in digital geometry processing and computer graphics. The set of attributes associated with each vertex such as the vertex locations, curvature, temperature, pressure or saliency, can be recognized as data living on mani- fold surfaces. So interpolation and approximation for these data are of general interest. This paper presents two approaches for mani- fold data interpolation and approximation through the properties of Laplace-Beltrami operator （Laplace operator defined on a mani- fold surface）. The first one is to use Laplace operator minimizing the membrane energy of a scalar function defined on a manifold. The second one is to use bi-Laplace operator minimizing the thin plate energy of a scalar function defined on a manifold. These two approaches can process data living on high genus meshed surfaces. The approach based on Laplace operator is more suitable for manifold data approximation and can be applied manifold data smoothing, while the one based on bi-Laplace operator is more suit- able for manifold data interpolation and can be applied image extremal envelope computation. All the application examples demon- strate that our procedures are robust and efficient.
