Dimensionality reduction （DR） methods based on sparse representation as one of the hottest research topics have achieved remarkable performance in many applications in recent years. However, it＇s a challenge for ex...Dimensionality reduction （DR） methods based on sparse representation as one of the hottest research topics have achieved remarkable performance in many applications in recent years. However, it＇s a challenge for existing sparse representation based methods to solve nonlinear problem due to the limitations of seeking sparse representation of data in the original space. Motivated by kernel tricks, we proposed a new framework called empirical kernel sparse representation （EKSR） to solve nonlinear problem. In this framework, non- linear separable data are mapped into kernel space in which the nonlinear similarity can be captured, and then the data in kernel space is reconstructed by sparse representation to preserve the sparse structure, which is obtained by minimiz- ing a ~1 regularization-related objective function. EKSR pro- vides new insights into dimensionality reduction and extends two models： 1） empirical kernel sparsity preserving projec- tion （EKSPP）, which is a feature extraction method based on sparsity preserving projection （SPP）; 2） empirical kernel sparsity score （EKSS）, which is a feature selection method based on sparsity score （SS）. Both of the two methods can choose neighborhood automatically as the natural discrimi- native power of sparse representation. Compared with sev- eral existing approaches, the proposed framework can reduce computational complexity and be more convenient in prac- tice.展开更多
A new adaptive learning algorithm for constructing and training wavelet networks is proposed based on the time-frequency localization properties of wavelet frames and the adaptive projection algorithm. The exponential...A new adaptive learning algorithm for constructing and training wavelet networks is proposed based on the time-frequency localization properties of wavelet frames and the adaptive projection algorithm. The exponential convergence of the adaptive projection algorithm in finite-dimensional Hilbert spaces is constructively proved, with exponential decay ratios given with high accuracy. The learning algorithm can sufficiently utilize the time-frequency information contained in the training data, iteratively determines the number of the hidden layer nodes and the weights of wavelet networks, and solves the problem of structure optimization of wavelet networks. The algorithm is simple and efficient, as illustrated by examples of signal representation and denoising.展开更多
Non-isomorphic two dimensional indecomposable modules over infinite dimensional hereditary path algebras are described. We infer that none of them can be determined by their dimension vectors.
This paper deals with the conditional quantile estimation based on left-truncated and right-censored data.Assuming that the observations with multivariate covariates form a stationary α-mixing sequence,the authors de...This paper deals with the conditional quantile estimation based on left-truncated and right-censored data.Assuming that the observations with multivariate covariates form a stationary α-mixing sequence,the authors derive the strong convergence with rate,strong representation as well as asymptotic normality of the conditional quantile estimator.Also,a Berry-Esseen-type bound for the estimator is established.In addition,the finite sample behavior of the estimator is investigated via simulations.展开更多
为了实现对以往设计经验及知识的继承和重用,将知识工程(Knowledge based Engineering,KBE)技术应用到采煤机数字化设计中。建立了采煤机数字化设计系统体系结构,针对采煤机领域知识特点,运用面向对象及产生式知识表示模式建立了丰富的...为了实现对以往设计经验及知识的继承和重用,将知识工程(Knowledge based Engineering,KBE)技术应用到采煤机数字化设计中。建立了采煤机数字化设计系统体系结构,针对采煤机领域知识特点,运用面向对象及产生式知识表示模式建立了丰富的知识库,并将实例推理和规则推理的集成机制应用于采煤机设计中。以Unigraphics为平台开发了基于KBE的采煤机数字化设计系统(Digital Design System for Coal Mining Machine,DDS-CMM),实现了采煤机的概念设计和零部件设计的数字化过程,积累了设计经验和知识,缩短了产品生命周期。展开更多
Based on the method of symplectic geometry and variational calculation,the method for some PDEs to be ordered and analytically represented by Hamiltonian canonical system is discussed.Meanwhile some related necessar...Based on the method of symplectic geometry and variational calculation,the method for some PDEs to be ordered and analytically represented by Hamiltonian canonical system is discussed.Meanwhile some related necessary and sufficient conditions are obtained展开更多
To investigate the relationship between macro-plastic behavior and meso-deformation mechanism of Mg alloy AZ31, the mathematical models for various deformation mechanisms of slip, twinning and detwinning are establish...To investigate the relationship between macro-plastic behavior and meso-deformation mechanism of Mg alloy AZ31, the mathematical models for various deformation mechanisms of slip, twinning and detwinning are established, respectively. Furthermore, in order to capture the Bauschinger effect under cyclic loading, the back stress is introduced into the three independent deformation mechanisms, respectively. Finally, using the above-mentioned model, a new cyclic plastic constitutive model based on the constitutive theory of crystal deformation for magnesium alloy is established. On this basis, the numerical simulation for AZ31 under cyclic loading with the axial strain amplitude of 1.2% is carried out in accordance with the aforementioned crystal plas- ticity theory associated with the representative volume element model. The comparison between the stress-strain curves obtained from the simulation and the experiments shows that the macro- scopic mechanical responses predicted using the proposed model are in good agreement with the experimental results. In particular, the unique characteristics of cyclic macro-plastic behavior observed in the experiments can be satisfactorily captured by the presented crystal plasticity model. At the mesoscale, these features are caused by the alternate occurrence of twinning and detwinning mechanisms. The further analysis of meso-plastic behavior shows that there are het- erogeneous distributions of twinning, stress-strain and stress triaxiality in polycrystal under cyclic loading.展开更多
文摘Dimensionality reduction （DR） methods based on sparse representation as one of the hottest research topics have achieved remarkable performance in many applications in recent years. However, it＇s a challenge for existing sparse representation based methods to solve nonlinear problem due to the limitations of seeking sparse representation of data in the original space. Motivated by kernel tricks, we proposed a new framework called empirical kernel sparse representation （EKSR） to solve nonlinear problem. In this framework, non- linear separable data are mapped into kernel space in which the nonlinear similarity can be captured, and then the data in kernel space is reconstructed by sparse representation to preserve the sparse structure, which is obtained by minimiz- ing a ~1 regularization-related objective function. EKSR pro- vides new insights into dimensionality reduction and extends two models： 1） empirical kernel sparsity preserving projec- tion （EKSPP）, which is a feature extraction method based on sparsity preserving projection （SPP）; 2） empirical kernel sparsity score （EKSS）, which is a feature selection method based on sparsity score （SS）. Both of the two methods can choose neighborhood automatically as the natural discrimi- native power of sparse representation. Compared with sev- eral existing approaches, the proposed framework can reduce computational complexity and be more convenient in prac- tice.
基金This work was supported by the National Natural Science Foundation of China (Grant No. 69872030) the Natural Science Foundation of Shaanxi Province (Grant No. 98 × 08) Elite Young Teacher Foundation of Ministry of China (1997).
文摘A new adaptive learning algorithm for constructing and training wavelet networks is proposed based on the time-frequency localization properties of wavelet frames and the adaptive projection algorithm. The exponential convergence of the adaptive projection algorithm in finite-dimensional Hilbert spaces is constructively proved, with exponential decay ratios given with high accuracy. The learning algorithm can sufficiently utilize the time-frequency information contained in the training data, iteratively determines the number of the hidden layer nodes and the weights of wavelet networks, and solves the problem of structure optimization of wavelet networks. The algorithm is simple and efficient, as illustrated by examples of signal representation and denoising.
基金The NSF(11371307)of ChinaResearch Culture Funds(2014xmpy11)of Anhui Normal University
文摘Non-isomorphic two dimensional indecomposable modules over infinite dimensional hereditary path algebras are described. We infer that none of them can be determined by their dimension vectors.
基金supported by the National Natural Science Foundation of China(No.11271286)the Specialized Research Fund for the Doctor Program of Higher Education of China(No.20120072110007)a grant from the Natural Sciences and Engineering Research Council of Canada
文摘This paper deals with the conditional quantile estimation based on left-truncated and right-censored data.Assuming that the observations with multivariate covariates form a stationary α-mixing sequence,the authors derive the strong convergence with rate,strong representation as well as asymptotic normality of the conditional quantile estimator.Also,a Berry-Esseen-type bound for the estimator is established.In addition,the finite sample behavior of the estimator is investigated via simulations.
文摘为了实现对以往设计经验及知识的继承和重用,将知识工程(Knowledge based Engineering,KBE)技术应用到采煤机数字化设计中。建立了采煤机数字化设计系统体系结构,针对采煤机领域知识特点,运用面向对象及产生式知识表示模式建立了丰富的知识库,并将实例推理和规则推理的集成机制应用于采煤机设计中。以Unigraphics为平台开发了基于KBE的采煤机数字化设计系统(Digital Design System for Coal Mining Machine,DDS-CMM),实现了采煤机的概念设计和零部件设计的数字化过程,积累了设计经验和知识,缩短了产品生命周期。
基金Supported in part by the National Natural Science Foundation of China (1 0 0 71 0 2 1 ) the Foundationfor University Key Teacher by MEC and Shanghai Priority Academic Discipline Foundation
文摘Based on the method of symplectic geometry and variational calculation,the method for some PDEs to be ordered and analytically represented by Hamiltonian canonical system is discussed.Meanwhile some related necessary and sufficient conditions are obtained
文摘浅埋目标探测是低频超宽带合成孔径雷达(Synthetic Aperture Radar,SAR)的一个重要应用。地雷作为浅埋目标的一类,由于其回波微弱,且所处环境复杂,使得检测后图像中常常存在大量虚假目标。提取有效特征用于鉴别是降低虚警的关键所在,传统基于全孔径图像距离剖线进行时频表示的算法易受噪声影响,并且难以表示目标散射特性。本文提出一种基于重构回波稀疏时频表示提取特征及鉴别的方法。该方法基于感兴趣区域(Regions of Interest,ROI)重构目标各个方位角的回波,可以有效减少原来回波域相邻杂波影响,提取目标较为准确的散射特性。本文方法同时采用引入判决分量的稀疏时频表示,改善了特征提取的准确度并简化了鉴别流程。实测数据处理结果表明了本文所提方法在杂波抑制和目标鉴别方面的有效性。
基金Project （11462002） supported by the National Natural Science Foundation of China Project （2016GXNSFAA380218） supported by Guangxi Natural Science Foundation, China+1 种基金 Project （2014ZDK002） supported by the Open Project of Guangxi Key Laboratory of Disaster Prevention and Structural Safety at Guangxi University, China and Project （Z01） supported by the Science Foundation for Doctorate Research of Guangxi University of Science and Technology, China.
文摘To investigate the relationship between macro-plastic behavior and meso-deformation mechanism of Mg alloy AZ31, the mathematical models for various deformation mechanisms of slip, twinning and detwinning are established, respectively. Furthermore, in order to capture the Bauschinger effect under cyclic loading, the back stress is introduced into the three independent deformation mechanisms, respectively. Finally, using the above-mentioned model, a new cyclic plastic constitutive model based on the constitutive theory of crystal deformation for magnesium alloy is established. On this basis, the numerical simulation for AZ31 under cyclic loading with the axial strain amplitude of 1.2% is carried out in accordance with the aforementioned crystal plas- ticity theory associated with the representative volume element model. The comparison between the stress-strain curves obtained from the simulation and the experiments shows that the macro- scopic mechanical responses predicted using the proposed model are in good agreement with the experimental results. In particular, the unique characteristics of cyclic macro-plastic behavior observed in the experiments can be satisfactorily captured by the presented crystal plasticity model. At the mesoscale, these features are caused by the alternate occurrence of twinning and detwinning mechanisms. The further analysis of meso-plastic behavior shows that there are het- erogeneous distributions of twinning, stress-strain and stress triaxiality in polycrystal under cyclic loading.
