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Electrical Data Matrix Decomposition in Smart Grid 认领 引用 被引量：1
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作者 Qian Dang Huafeng Zhang +3 位作者 Bo Zhao Yanwen He Shiming He Hye-Jin Kim 《Journal on Internet of Things》 2019年第1期1-7,共7页
As the development of smart grid and energy internet, this leads to a significantincrease in the amount of data transmitted in real time. Due to the mismatch withcommunication networks that were not designed to carry ... As the development of smart grid and energy internet, this leads to a significantincrease in the amount of data transmitted in real time. Due to the mismatch withcommunication networks that were not designed to carry high-speed and real time data,data losses and data quality degradation may happen constantly. For this problem,according to the strong spatial and temporal correlation of electricity data which isgenerated by human’s actions and feelings, we build a low-rank electricity data matrixwhere the row is time and the column is user. Inspired by matrix decomposition, we dividethe low-rank electricity data matrix into the multiply of two small matrices and use theknown data to approximate the low-rank electricity data matrix and recover the missedelectrical data. Based on the real electricity data, we analyze the low-rankness of theelectricity data matrix and perform the Matrix Decomposition-based method on the realdata. The experimental results verify the efficiency and efficiency of the proposed scheme. 展开更多
关键词 Electrical data recovery matrix decomposition low-rankness smart grid
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A Unified Co-Processor Architecture for Matrix Decomposition 认领 引用 被引量：1
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作者 窦勇 周杰 +3 位作者 邬贵明 姜晶菲 雷元武 倪时策 《Journal of Computer Science & Technology》 SCIE EI 2010年第4期874-885,共12页
QR and LU decompositions are the most important matrix decomposition algorithms. Many studies work on accelerating these algorithms by FPGA or ASIC in a case by case style. In this paper, we propose a unified framewor... QR and LU decompositions are the most important matrix decomposition algorithms. Many studies work on accelerating these algorithms by FPGA or ASIC in a case by case style. In this paper, we propose a unified framework for the matrix decomposition algorithms, combining three QR decomposition algorithms and LU algorithm with pivoting into a unified linear array structure. The QR and LU decomposition algorithms exhibit the same two-level loop structure and the same data dependency. Utilizing the similarities in loop structure and data dependency of matrix decomposition, we unify a fine-grained algorithm for all four matrix decomposition algorithms. Furthermore, we present a unified co-processor structure with a scalable linear array of processing elements （PEs）, in which four types of PEs are same in the structure of memory channels and PE connections, but the only difference exists in the internal structure of data path. Our unified co-processor, which is IEEE 32-bit floating-point precision, is implemented and mapped onto a Xilinx Virtex5 FPGA chip. Experimental results show that our co-processors can achieve speedup of 2.3 to 14.9 factors compared to a Pentium Dual CPU with double SSE threads. 展开更多
关键词 co-processor matrix decomposition fine-grained parallel FPGA
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Modeling mechanism of a novel fractional grey mode based on matrix analysis 认领 引用 被引量：3
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作者 shuhua mao min zhu +2 位作者 xinping yan mingyun gao xinping xiao 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2016年第5期1040-1053,共14页
To fully display the modeling mechanism of the novelfractional order grey model （FGM （q,1））, this paper decomposesthe data matrix of the model into the mean generation matrix, theaccumulative generation matrix and... To fully display the modeling mechanism of the novelfractional order grey model （FGM （q,1））, this paper decomposesthe data matrix of the model into the mean generation matrix, theaccumulative generation matrix and the raw data matrix, whichare consistent with the fractional order accumulative grey model（FAGM （1,1））. Following this, this paper decomposes the accumulativedata difference matrix into the accumulative generationmatrix, the q-order reductive accumulative matrix and the rawdata matrix, and then combines the least square method, findingthat the differential order affects the model parameters only byaffecting the formation of differential sequences. This paper thensummarizes matrix decomposition of some special sequences,such as the sequence generated by the strengthening and weakeningoperators, the jumping sequence, and the non-equidistancesequence. Finally, this paper expresses the influences of the rawdata transformation, the accumulation sequence transformation,and the differential matrix transformation on the model parametersas matrices, and takes the non-equidistance sequence as an exampleto show the modeling mechanism. 展开更多
关键词 fractional order grey model generalized accumulativegeneration matrix decomposition non-equidistance sequence,modeling mechanism.
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Cryptanalysis of Schemes Based on Pseudoinverse Matrix 认领 引用
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作者 LIU Jinhui ZHANG Huanguo JIA Jianwei 《Wuhan University Journal of Natural Sciences》 CAS CSCD 2016年第3期209-213,共5页
Advances in quantum computation threaten to break public key eryptosystems that are based on the difficulty of fac- torization or the difficulty of discrete logariths, although , no quantum algorithms have been found ... Advances in quantum computation threaten to break public key eryptosystems that are based on the difficulty of fac- torization or the difficulty of discrete logariths, although , no quantum algorithms have been found to be able to solve certain mathematical problems on non-commutative algebraic structures up to now. The proposed new quasi-inverse based cryptography scheme is vulnerable to a linear algebra attack based on the probable occurrence of weak keys in the generation process. In this paper, we illustrate that two of the quasi-inverse based cryptography are vulnerable to a structural attack and that it only requires polynomial time to obtain the equivalent keys for some given public keys. In addition, we conduct a detailed analysis on attack methods and provide some improved suggestions on these two schemes. 展开更多
关键词 cryptography post-quantum computational cryptography key exchange protocol cryptanalysis matrix decomposition
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Mobility and equilibrium stability analysis of pin-jointed mechanisms with equilibrium matrix SVD 认领 引用
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作者 LU Jin-yu LUO Yao-zhi LI Na 《Journal of Zhejiang University-SCIENCE A》 SCIE EI CAS 2007年第7期1091-1100,共10页
Under certain load pattern, the geometrically indeterminate pin-jointed mechanisms will present certain shapes to keep static equalization. This paper proposes a matrix-based method to determine the mobility and equil... Under certain load pattern, the geometrically indeterminate pin-jointed mechanisms will present certain shapes to keep static equalization. This paper proposes a matrix-based method to determine the mobility and equilibrium stability of mechanisms according to the effects of the external loads. The first and second variations of the potential energy function of mechanisms under conservative force field are analyzed. Based on the singular value decomposition (SVD) method, a new crite- rion for the mobility and equilibrium stability of mechanisms can be concluded by analyzing the equilibrium matrix. The mobility and stability of mechanisms can be classified by unified matrix formulae. A number of examples are given to demonstrate the proposed criterion. In the end, criteria are summarized in a table. 展开更多
关键词 Pin-jointed mechanisms Criteria for stability of equilibrium Criteria for mobility Potential energy function Equilibrium matrix. Singular value decomposition （SVD） method
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Elliptical vectorial metrics for physically plausible polarization information analysis 认领 引用
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作者 Runchen Zhang Xuke Qiu +7 位作者 Yifei Ma Zimo Zhao An Aloysius Wang Jinge Guo Ji Qin Steve J.Elston Stephen M.Morris Chao He 《Advanced Photonics Nexus》 CSCD 2025年第6期141-148,共8页
The Mueller matrix polar decomposition method decomposes a Mueller matrix into a diattenuator,a retarder,and a depolarizer.Among these elements,the retarder,which plays a key role in medical and material characterizat... The Mueller matrix polar decomposition method decomposes a Mueller matrix into a diattenuator,a retarder,and a depolarizer.Among these elements,the retarder,which plays a key role in medical and material characterization,is usually modelled as a circular retarder followed by a linear retarder.However,this model may not accurately reflect the actual structure of the retarder in certain cases as many practical retarders do not have a layered structure or consist of multiple(unknown)layers.Misinterpretation,therefore,may occur when the actual structure differs from the model.Here,we circumvent this limitation by proposing to use an elliptical retarder parameter set that includes the axis orientation angleφ,the degree of ellipticityχ,and the elliptical retardanceρ.By working with this set of parameters,an overall characterization of any retarder is provided,encompassing its full optical response without making any assumptions about the structure of the material.In this study,experiments were carried out on liquid crystalline samples to validate the feasibility of our approach,demonstrating that the elliptical retarder parameter set adopted provides a useful tool for a broader range of applications in optical material analysis. 展开更多
关键词 Mueller matrix polarimetry Mueller matrix polar decomposition retarder liquid crystal.
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Parameters Compressing in Deep Learning 认领 引用 被引量：16
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作者 Shiming He Zhuozhou Li +3 位作者 Yangning Tang Zhuofan Liao Feng Li Se-Jung Lim 《Computers, Materials & Continua》 SCIE EI 2020年第1期321-336,共16页
With the popularity of deep learning tools in image decomposition and natural language processing,how to support and store a large number of parameters required by deep learning algorithms has become an urgent problem... With the popularity of deep learning tools in image decomposition and natural language processing,how to support and store a large number of parameters required by deep learning algorithms has become an urgent problem to be solved.These parameters are huge and can be as many as millions.At present,a feasible direction is to use the sparse representation technique to compress the parameter matrix to achieve the purpose of reducing parameters and reducing the storage pressure.These methods include matrix decomposition and tensor decomposition.To let vector take advance of the compressing performance of matrix decomposition and tensor decomposition,we use reshaping and unfolding to let vector be the input and output of Tensor-Factorized Neural Networks.We analyze how reshaping can get the best compress ratio.According to the relationship between the shape of tensor and the number of parameters,we get a lower bound of the number of parameters.We take some data sets to verify the lower bound. 展开更多
关键词 Deep neural network parameters compressing matrix decomposition tensor decomposition
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Note on Implementation of Three-Qubit SWAP Gate 认领 引用 被引量：4
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作者 魏海瑞 狄尧民 +1 位作者 王艳 张洁 《Communications in Theoretical Physics》 SCIE CAS 2010年第1期78-82,共5页
In this paper, the synthesis and implementation of three-qubit SWAP gate is discussed. The three-qubit SWAP gate can be decomposed into product of 2 two-qubit SWAP gates, and it can be realized by 6 CNOT gates. Resear... In this paper, the synthesis and implementation of three-qubit SWAP gate is discussed. The three-qubit SWAP gate can be decomposed into product of 2 two-qubit SWAP gates, and it can be realized by 6 CNOT gates. Research illustrated that although the result is very simple, the current methods of matrix decomposition for multi-qubit gate can not get that. Then the implementation of three-qubit SWAP gate in the three spin system with Ising interaction is investigated and the sequence of control pulse and drift process to implement the gate is given. It needs 23 control pulses and 12 drift processes. Since the interaction can not be switched on and off at will, the realization of three-qubit SWAP gate in specific quantum system also can not simply come down to 2 two-qubit SWAP gates. 展开更多
关键词 three-qubit SWAP gate matrix decomposition three spin system Ising interaction
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A multiscale Galerkin method for the hypersingular integral equation reduced by the harmonic equation 认领 引用
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作者 LI Song-hua XIAN Jun 《Applied Mathematics(A Journal of Chinese Universities)》 SCIE CSCD 2013年第1期75-89,共15页
The aim of this paper is to investigate the numerical solution of the hypersingular integral equation reduced by the harmonic equation. First, we transform the hypersingular integral equation into 2π-periodic hypersi... The aim of this paper is to investigate the numerical solution of the hypersingular integral equation reduced by the harmonic equation. First, we transform the hypersingular integral equation into 2π-periodic hypersingular integral equation with the map x=cot（θ/2）. Second, we initiate the study of the multiscale Galerkin method for the 2π-periodic hypersingular integral equation. The trigonometric wavelets are used as trial functions. Consequently, the 2j＋1 × 2j＋1 stiffness matrix Kj can be partitioned j×j block matrices. Furthermore, these block matrices are zeros except main diagonal block matrices. These main diagonal block matrices are symmetrical and circulant matrices, and hence the solution of the associated linear algebraic system can be solved with the fast Fourier transform and the inverse fast Fourier transform instead of the inverse matrix. Finally, we provide several numerical examples to demonstrate our method has good accuracy even though the exact solutions are multi-peak and almost singular. 展开更多
关键词 Trigonometric wavelet multiscale Galerkin method matrix decomposition FFT hypersingular integral equation harmonic equation.
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Event-Triggered Control of Positive Semi-Markovian Jump Systems Without/with Input Saturation 认领 引用
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作者 ZHANG Suhuan ZHANG Junfeng +1 位作者 LI Shuo YU Shanen 《Journal of Shanghai Jiaotong university(Science)》 EI 2022年第5期723-736,共14页
This paper is concerned with the event-triggered control of positive semi-Markovian jump systems without/with input saturation.The considered systems are subject to a stochastic semi-Markovian process whose sojourn ti... This paper is concerned with the event-triggered control of positive semi-Markovian jump systems without/with input saturation.The considered systems are subject to a stochastic semi-Markovian process whose sojourn time is dependent on a non-exponential distribution.First,an event-triggering condition is introduced in a linear form for the systems.A class of event-triggered feedback controllers is proposed using matrix decomposition technique.By using a stochastic co-positive Lyapunov function,the systems’positivity and stability are guaranteed.Then,the obtained results are developed for the systems with input saturation.A cone set is chosen as the attraction domain and the corresponding attraction domain gain matrix is designed in terms of standard linear programming approach.Finally,two numerical examples are provided to verify the validity and effectiveness of the presented theoretical findings. 展开更多
关键词 event-triggered control positive semi-Markovian jump systems input saturation matrix decomposition linear programming
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COMPARISON OF OPTICAL POLARIMETRY AND DIFFUSION TENSOR MR IMAGING FOR ASSESSING MYOCARDIAL ANISOTROPY 认领 引用
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作者 MARIKA A.WALLENBURG MIHAELA POP +3 位作者 MICHAEL F.G.WOOD NIRMALYA GHOSH GRAHAM A.WRIGHT I.ALEX VITKIN 《Journal of Innovative Optical Health Sciences》 SCIE EI 2010年第2期109-121,共13页
We have recently proposed an optical method for assessing heart structure that uses polarized light measurement of birefringence as an indicator of tissue anisotropy.The highly aligned nature of healthy cardiac muscle... We have recently proposed an optical method for assessing heart structure that uses polarized light measurement of birefringence as an indicator of tissue anisotropy.The highly aligned nature of healthy cardiac muscle tissue has a detectable effect on the polarization of light,resulting in a measurable phase shift(“retardance”).When this organized tissue structure is perturbed,for example after cardiac infarction(heart attack),scar tissue containing disorganized collagen is formed,causing a decrease in the measured retardance values.However,these are dependent not only on tissue anisotropy,but also on the angle between the tissue’s optical anisotropy direction and the beam interrogating the sample.To remove this experimental ambiguity,we present a method that interrogates the sample at two different incident beam angles,thus yielding enough information to uniquely determine the true magnitude and orientation of the tissue optical anisotropy.We use an infarcted porcine heart model to compare these polarimetryderived anisotropy metrics with those obtained with diffusion tensor magnetic resonance imaging(DT-MRI).The latter yields the anisotropy and the direction of tissue water diffusivity,providing an independent measure of tissue anisotropy.The optical and MR results are thus directly compared in a common ex vivo biological model of interest,yielding reasonable agreement but also highlighting some technique-specific differences. 展开更多
关键词 Birefringence Mueller matrix decomposition fractional anisotropy diffusion tensor magnetic resonance imaging myocardial infarction
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The G^3 spline basis functions 认领 引用
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作者 Diao Luhong Cao Huan +1 位作者 Zhang Zhenmeng Lu Xiaoyan 《Computer Aided Drafting,Design and Manufacturing》 2016年第1期41-46,共6页
The explicit expression of the G3 basis function is presented in this paper. It is derived by constructing the conversion matrix between G3 basis function and Brzier representation. After the matrix decomposition, equ... The explicit expression of the G3 basis function is presented in this paper. It is derived by constructing the conversion matrix between G3 basis function and Brzier representation. After the matrix decomposition, equations for constructing G3 splines can be presented independently of geometric shape parameters＇ values. It makes the equation＇s solving easier. It is also known that the general form of the G3spline basis function is given in the first time. Its geometric construction method is presented. 展开更多
关键词 geometric continuity G3 spline basis functions splines B6zier representation matrix decomposition
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The Haar Wavelet Analysis of Matrices and Its Applications 认领 引用
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作者 Xiquan SHI 《Journal of Mathematical Research with Applications》 CSCD 2017年第1期19-28,共10页
It is well known that Fourier analysis or wavelet analysis is a very powerful and useful tool for a function since they convert time-domain problems into frequency-domain problems. Are there similar tools for a matrix... It is well known that Fourier analysis or wavelet analysis is a very powerful and useful tool for a function since they convert time-domain problems into frequency-domain problems. Are there similar tools for a matrix？ By pairing a matrix to a piecewise function,a Haar-like wavelet is used to set up a similar tool for matrix analyzing, resulting in new methods for matrix approximation and orthogonal decomposition. By using our method, one can approximate a matrix by matrices with different orders. Our method also results in a new matrix orthogonal decomposition, reproducing Haar transformation for matrices with orders of powers of two. The computational complexity of the new orthogonal decomposition is linear. That is, for an m × n matrix, the computational complexity is O（mn）. In addition,when the method is applied to k-means clustering, one can obtain that k-means clustering can be equivalently converted to the problem of finding a best approximation solution of a function. In fact, the results in this paper could be applied to any matrix related problems.In addition, one can also employ other wavelet transformations and Fourier transformation to obtain similar results. 展开更多
关键词 wavelet analysis Fourier analysis matrix decomposition k-means clustering linear equation
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An iterative algorithm for solving ill-conditioned linear least squares problems 认领 引用 被引量：9
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作者 Deng Xingsheng Yin Liangbo +1 位作者 Peng Sichun Ding Meiqing 《Geodesy and Geodynamics》 2015年第6期453-459,共7页
Linear Least Squares（LLS） problems are particularly difficult to solve because they are frequently ill-conditioned, and involve large quantities of data. Ill-conditioned LLS problems are commonly seen in mathematics... Linear Least Squares（LLS） problems are particularly difficult to solve because they are frequently ill-conditioned, and involve large quantities of data. Ill-conditioned LLS problems are commonly seen in mathematics and geosciences, where regularization algorithms are employed to seek optimal solutions. For many problems, even with the use of regularization algorithms it may be impossible to obtain an accurate solution. Riley and Golub suggested an iterative scheme for solving LLS problems. For the early iteration algorithm, it is difficult to improve the well-conditioned perturbed matrix and accelerate the convergence at the same time. Aiming at this problem, self-adaptive iteration algorithm（SAIA） is proposed in this paper for solving severe ill-conditioned LLS problems. The algorithm is different from other popular algorithms proposed in recent references. It avoids matrix inverse by using Cholesky decomposition, and tunes the perturbation parameter according to the rate of residual error decline in the iterative process. Example shows that the algorithm can greatly reduce iteration times, accelerate the convergence,and also greatly enhance the computation accuracy. 展开更多
关键词 Severe ill-conditioned matrix Linear least squares problems Self-adaptive Iterative scheme Cholesky decomposition Regularization parameter Tikhonov solution Truncated SVD solution
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A Geometric View on Inner Transformation between the Variables of a Linear Regression Model 认领 引用 被引量：1
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作者 Zhaoyang Li Bostjan Antoncic 《Applied Mathematics》 2021年第10期931-938,共8页
In the teaching and researching of linear regression analysis, it is interesting and enlightening to explore how the dependent variable vector can be inner-transformed into regression coefficient estimator vector from... In the teaching and researching of linear regression analysis, it is interesting and enlightening to explore how the dependent variable vector can be inner-transformed into regression coefficient estimator vector from a visible geometrical view. As an example, the roadmap of such inner transformation is presented based on a simple multiple linear regression model in this work. By applying the matrix algorithms like singular value decomposition (SVD) and Moore-Penrose generalized matrix inverse, the dependent variable vector lands into the right space of the independent variable matrix and is metamorphosed into regression coefficient estimator vector through the three-step of inner transformation. This work explores the geometrical relationship between the dependent variable vector and regression coefficient estimator vector as well as presents a new approach for vector rotating. 展开更多
关键词 Matrix Singular Value Decomposition Moore-Penrose Generalized Inverse Matrix Inner Transformation Regression Analysis
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Advanced Bayesian kernel machine regression for large-scale exposome studies:Making the impossible possible 认领 引用
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作者 Yi Guo Huixun Jia +7 位作者 Ziwei Peng Xinming Xu Zhicheng Zhang Keyu Pan Yuqin Zhou Haidong Kan Zhenyu Wu Cong Liu 《The Innovation》 EI 2026年第4期69-79,共11页
Exposome studies involve analyzing numerous exposures with complex interactions and potential collinearity,presenting challenges for conventional statistical methods.While Bayesian kernel machine regression(BKMR)has e... Exposome studies involve analyzing numerous exposures with complex interactions and potential collinearity,presenting challenges for conventional statistical methods.While Bayesian kernel machine regression(BKMR)has emerged as a promising solution,its widespread adoption has been hindered by high computational costs and restricted interpretability.To address these critical limitations in large-scale exposome studies,we developed an advanced BKMR(A-BKMR)model.The Gaussian predictive process and matrix decomposition were used to reduce both processing time and memory requirements.Additionally,we employed the parametric g-formula to generate interpretable statistics,including joint and univariate effects as well as bivariate and multivariate interactions.Across various scenarios with different sample sizes and numbers of exposures,A-BKMR demonstrated both high computational efficiency and model performance.Previously,analyzing datasets with sample sizes of 100,000 was unfeasible for traditional BKMR.The current A-BKMR can complete such analyses in 1 h on a personal computer,making it over 700,000 times faster than conventional BKMR implementations.Additionally,A-BKMR can accurately identify important exposure while preserving an area under the curve(AUC)>0.99 and an R2>0.97 across scenarios with varying sample sizes and numbers of exposures.Furthermore,A-BKMR introduces novel quantitative metrics for effect estimates and interaction analyses,substantially enhancing interpretability.These advancements establish A-BKMR as an excellent statistical framework for future large-scale exposome studies. 展开更多
关键词 gaussian predictive process matrix decompos exposome studies Bayesian Kernel Machine Regression Gaussian Predictive Process bayesian kernel machine regression bkmr analyzing numerous exposures Parametric G Formula Matrix Decomposition
Research and Implementation of Task Management Model in Product Development Process Management 认领 引用 被引量：1
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作者 Liu Qinghua Wan Li Zhong Yifang 《Computer Aided Drafting,Design and Manufacturing》 2000年第1期63-73,共11页
The implementation of product development process management (PDPM) is an effective means of developing products with higher quality in shorter lead time. It is argued in this paper that product, data, person and acti... The implementation of product development process management (PDPM) is an effective means of developing products with higher quality in shorter lead time. It is argued in this paper that product, data, person and activity are basic factors in PDPM With detailed analysis of these basic factors and their relations in product developmed process, all product development activities are considered as tasks and the management of product development process is regarded as the management of task execution A task decomposition based product development model is proposed with methods of constructing task relation matrix from layer model and constraint model resulted from task decomposition. An algorithm for constructing directed task graph is given and is used in the management of tasks. Finally, the usage and limitation of the proposed PDPM model is given with further work proposed. 展开更多
关键词 product development process management task decomposition,task relation matrix
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Unified calculation of eigen-solutions in power systems based on matrix perturbation theory 认领 引用
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作者 LI Yan GAO WenZhong +2 位作者 JIANG JiuChun WANG ChenShan MULJADI Eduard 《Science China(Technological Sciences)》 SCIE EI CAS 2014年第8期1594-1601,共8页
Calculation of eigen-solutions plays an important role in the small signal stability analysis of power systems.In this paper,a novel approach based on matrix perturbation theory is proposed for the calculation of eige... Calculation of eigen-solutions plays an important role in the small signal stability analysis of power systems.In this paper,a novel approach based on matrix perturbation theory is proposed for the calculation of eigen-solutions in a perturbed system.Rigorous theoretical analysis is conducted on the solution of distinct,multiple,and close eigen-solutions,respectively,under perturbations of parameters.The computational flowchart of the unified solution of eigen-solutions is then proposed,aimed toward obtaining eigen-solutions of a perturbed system directly with algebraic formulas without solving an eigenvalue problem repeatedly.Finally,the effectiveness of the matrix perturbation based approach for eigen-solutions’calculation in power systems is verified by numerical examples on a two-area four-machine system. 展开更多
关键词 matrix perturbation matrix spectrum decomposition shift method unified solution approach eigen-solutions
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Modeling the Correlations of Relations for Knowledge Graph Embedding 认领 引用 被引量：8
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作者 Ji-Zhao Zhu Yan-Tao Jia +2 位作者 Jun Xu Jian-Zhong Qiao Xue-Qi Cheng 《Journal of Computer Science & Technology》 SCIE EI CSCD 2018年第2期323-334,共12页
Knowledge graph embedding, which maps the entities and relations into low-dimensional vector spaces, has demonstrated its effectiveness in many tasks such as link prediction and relation extraction. Typical methods in... Knowledge graph embedding, which maps the entities and relations into low-dimensional vector spaces, has demonstrated its effectiveness in many tasks such as link prediction and relation extraction. Typical methods include TransE, TransH, and TransR. All these methods map different relations into the vector space separately and the intrinsic correlations of these relations are ignored. It is obvious that there exist some correlations among relations because different relations may connect to a common entity. For example, the triples （Steve Jobs, PlaceOfBrith, California） and （Apple Inc., Location, California） share the same entity California as their tail entity. We analyze the embedded relation matrices learned by TransE/TransH/TransR, and find that the correlations of relations do exist and they are showed as low-rank structure over the embedded relation matrix. It is natural to ask whether we can leverage these correlations to learn better embeddings for the entities and relations in a knowledge graph. In this paper, we propose to learn the embedded relation matrix by decomposing it as a product of two low-dimensional matrices, for characterizing the low-rank structure. The proposed method, called TransCoRe （Translation-Based Method via Modeling the Correlations of Relations）, learns the embeddings of entities and relations with translation-based framework. Experimental results based on the benchmark datasets of WordNet and Freebase demonstrate that our method outperforms the typical baselines on link prediction and triple classification tasks. 展开更多
关键词 knowledge graph embedding low-rank matrix decomposition
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Psycho-visual modulation based information display:introduction and survey 认领 引用
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作者 Ning LIU Zhongpai GAO +1 位作者 Jia WANG Guangtao ZHAI 《Frontiers of Computer Science》 SCIE EI CSCD 2021年第3期15-32,共18页
Industry and academia have been making great efforts in improving refresh rates and resolutions of display devices to meet the ever increasing needs of consumers for better visual quality.As a result,many modem displa... Industry and academia have been making great efforts in improving refresh rates and resolutions of display devices to meet the ever increasing needs of consumers for better visual quality.As a result,many modem displays have spatial and temporal resolutions far beyond the discern capability of human visual systems.Thus,leading to the possibility of using those display-eye redundancies for innovative usages.Tempo-ral/spatial psycho-visual modulation(TPVM/SPVM)was proposed to exploit those redundancies to generate multiple visual percepts for different viewers or to transmit non-visual data to computing devices without affecting normal viewing.This paper reviews the STPVM technology from both conceptual and algorithmic perspectives,with exemplary applications in multiview display,display with visible light communication,etc.Some possible future research directions are also identified. 展开更多
关键词 information display human visual system spatial frequency temporal frequency non-negative matrix decomposition
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