检索结果-南通市图书馆

Coherence migration in high-dimensional bipartite systems

在线全文

学校读者我要写书评

暂无评论

Chinese Physics B 2022年第6期31卷 228-234页

作者： Zhi-Yong Ding Pan-Feng Zhou Xiao-Gang Fan Cheng-Cheng Liu Juan He Liu Ye School of Physics and Electronic Engineering Fuyang Normal UniversityFuyang 236037China Key Laboratory of Functional Materials and Devices for Informatics of Anhui Educational Institutions Fuyang Normal UniversityFuyang 236037China School of Physics and Optoelectronics Engineering Anhui UniversityHefei 230039China

The conservation law for first-order coherence and mutual correlation of a bipartite qubit state was firstly proposed by Svozil′?k et al.,and their theories laid the foundation for the study of coherence migration under unitary *** this paper,we generalize the framework of first-order coherence and mutual correlation to an arbitrary(m■n)-dimensional bipartite composite state by introducing an extended Bloch decomposition form of the *** also generalize two kinds of unitary operators in high-dimensional systems,which can bring about coherence migration and help to obtain the maximum or minimum first-order ***,the coherence migration in open quantum systems is *** take depolarizing channels as examples and establish that the reduced first-order coherence of the principal system over time is completely transformed into mutual correlation of the(2■4)-dimensional system-environment bipartite composite *** is expected that our results may provide a valuable idea or method for controlling the quantum resource such as coherence and quantum correlations.

关键词： first-order coherence mutual correlation coherence migration high-dimensional

Differentially private high-dimensional data publication via grouping and truncating techniques

在线全文

学校读者我要写书评

暂无评论

Frontiers of Computer Science 2019年第2期13卷 382-395页

作者： Ning WANG Yu GU Jia XU Fangfang LI Ge YU School of Computer Science and Engineering Northeastern University Shenyang 110819 China School of Computer Electronics and Information Guangxi University Guangxi 530004 China

The count of one column for high-dimensional datasets, i.e., the number of records containing this column, has been widely used in nuinerous applications such as analyzing popular spots based on check-in location information and mining valuable items from shopping records. However, this poses a privacy threat when directly publishing this information. Differential privacy (DP), as a notable paradigm for strong privacy guarantees, is thereby adopted to publish all column counts. Prior studies have verified that truncating records or grouping columns can effectively improve the accuracy of published results. To leverage the advantages of the two techniques, we combine these studies to further boost the accuracy of published results. However, the traditional penalty function, which measures the error imported by a given pair of parameters including truncating length and group size, is so sensitive that the derived parameters deviate from the optimal parameters significantly. To output preferable parameters, we first design a smart penalty function that is less sensitive than the traditional function. Moreover, a two-phase selection method is proposed to compute these parameters efficiently, together with the improvement in accuracy. Extensive experiments on a broad spectrum of real-world datasets validate the effectiveness of our proposals.

关键词： differential privacy high-dimensional data truncation optimization grouping penalty function

Multi-Objective Equilibrium Optimizer for Feature Selection in high-dimensional English Speech Emotion Recognition

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第2期78卷 1957-1975页

作者： Liya Yue Pei Hu Shu-Chuan Chu Jeng-Shyang Pan Fanli Business School Nanyang Institute of TechnologyNanyang473004China School of Computer and Software Nanyang Institute of TechnologyNanyang473004China College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao266590China Department of Information Management Chaoyang University of TechnologyTaichung413310Taiwan

Speech emotion recognition(SER)uses acoustic analysis to find features for emotion recognition and examines variations in voice that are caused by *** number of features acquired with acoustic analysis is extremely high,so we introduce a hybrid filter-wrapper feature selection algorithm based on an improved equilibrium optimizer for constructing an emotion recognition *** proposed algorithm implements multi-objective emotion recognition with the minimum number of selected features and maximum ***,we use the information gain and Fisher Score to sort the features extracted from ***,we employ a multi-objective ranking method to evaluate these features and assign different importance to *** with high rankings have a large probability of being ***,we propose a repair strategy to address the problem of duplicate solutions in multi-objective feature selection,which can improve the diversity of solutions and avoid falling into local *** random forest and K-nearest neighbor classifiers,four English speech emotion datasets are employed to test the proposed algorithm(MBEO)as well as other multi-objective emotion identification *** results illustrate that it performs well in inverted generational distance,hypervolume,Pareto solutions,and execution time,and MBEO is appropriate for high-dimensional English SER.

关键词： Speech emotion recognition filter-wrapper high-dimensional feature selection equilibrium optimizer multi-objective

Empirical Likelihood of Quantile Difference with Missing Response When high-dimensional Covariates Are Present

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Acta Mathematica Sinica,English Series 2021年第12期37卷 1803-1825页

作者： Cui Juan KONG Han Ying LIANG School of Mathematical Sciences Tongji UniversityShanghai 200092P.R.China

We,in this paper,investigate two-sample quantile difference by empirical likelihood method when the responses with high-dimensional covariates of the two populations are missing at *** particular,based on sufficient dimension reduction technique,we construct three empirical log-likelihood ratios for the quantile difference between two samples by using inverse probability weighting imputation,regression imputation as well as augmented inverse probability weighting imputation,respectively,and prove their asymptotic *** the same time,we give a test to check whether two populations have the same distribution.A simulation study is carried out to investigate finite sample behavior of the proposed methods too.

关键词： Empirical likelihood high-dimensional missing at random sufficient dimension reduction two-sample quantile difference

A combined p-value test for the mean difference of high-dimensional data

在线全文

学校读者我要写书评

暂无评论

Science China Mathematics 2019年第5期62卷 961-978页

作者： Wei Yu Wangli Xu Lixing Zhu Center for Applied Statistics School of Statistics Renmin University of China School of Statistics Beijing Normal University Department of Mathematics Hong Kong Baptist University

This paper proposes a novel method for testing the equality of high-dimensional means using a multiple hypothesis test. The proposed method is based on the maximum of standardized partial sums of logarithmic p-values statistic. Numerical studies show that the method performs well for both normal and non-normal data and has a good power performance under both dense and sparse alternative hypotheses. For illustration, a real data analysis is implemented.

关键词： high-dimensional data equality of means multiple hypothesis testing sparse alternatives

Efficient Distributed Estimation of high-dimensional Sparse Precision Matrix for Transelliptical Graphical Models

在线全文

学校读者我要写书评

暂无评论

Acta Mathematica Sinica,English Series 2021年第5期37卷 689-706页

作者： Guan Peng WANG Heng Jian CUI School of Mathematical Sciences Capital Normal UniversityBeijing 100048P.R.China

In this paper,distributed estimation of high-dimensional sparse precision matrix is proposed based on the debiased D-trace loss penalized lasso and the hard threshold method when samples are distributed into different machines for transelliptical graphical *** a certain level of sparseness,this method not only achieves the correct selection of non-zero elements of sparse precision matrix,but the error rate can be comparable to the estimator in a non-distributed *** numerical results further prove that the proposed distributed method is more effective than the usual average method.

关键词： Distributed estimator sparse precision matrix high-dimensional hard threshold efficient communication

Attacking a high-dimensional quantum key distribution system with wavelength-dependent beam splitter

在线全文

学校读者我要写书评

暂无评论

Chinese Physics B 2019年第9期28卷 87-92页

作者： Ge-Hai Du Hong-Wei Li Yang Wang Wan-Su Bao Henan Key Laboratory of Quantum Information and Cryptography PLA SSF IEUZhengzhou 450001China Synergetic Innovation Center of Quantum Information and Quantum Physics University of Science and Technology of ChinaHefei 230026China

The unconditional security of quantum key distribution(QKD) can be guaranteed by the nature of quantum *** with the traditional two-dimensional BB84 QKD protocol, high-dimensional quantum key distribution(HDQKD) can be applied to generate much more secret ***, practical imperfections in realistic systems can be exploited by the third party to eavesdrop the secret *** practical beam splitter has a correlation with wavelength,where different wavelengths have different coupling *** this property, we propose a wavelength-dependent attack towards time-bin high-dimensional QKD *** is more, we demonstrate that this attacking protocol can be applied to arbitrary d-dimensional QKD system, and higher-dimensional QKD system is more vulnerable to this attacking strategy.

关键词： high-dimensional quantum key distribution beam splitter wavelength attack

Finite-Key Analysis for a Practical high-dimensional Quantum Key Distribution System Based on Time-Phase States

在线全文

学校读者我要写书评

暂无评论

Chinese Physics Letters 2019年第4期36卷 5-9页

作者： Ya-Hui Gan Yang Wang Wan-Su Bao Ru-Shi He Chun Zhou Mu-Sheng Jiang Henan Key Laboratory of Quantum Information and Cryptography Zhengzhou Information Science and Technology Institute Synergetic Innovation Center of Quantum Information and Quantum Physics University of Science and Technology of China

high-dimensional quantum states key distribution(HD-QKD) can enable more than one bit per photon and tolerate more noise. Recently, a practical HD-QKD system based on time-phase states has provided a secret key at Mbps over metropolitan distances. For the purposes of further improving the secret key rate of a practical HD-QKD system, we make two main contributions in this work. Firstly, we present an improved parameter estimation for this system in the finite-key scenario based on the Chernoff bound and the improved Chernoff bound. Secondly, we analyze how the dimension d affects the performance of the practical HD-QKD *** present numerical simulations about the secret key rate of the practical HD-QKD system based on different parameter estimation methods. It is found that using the improved Chernoff bound can improve the secret key rate and maximum channel loss of the practical HD-QKD system. In addition, a mixture of the 4-level and 8-level practical HD-QKD system can provide better performance in terms of the key generation rate over metropolitan distances.

关键词： high-dimensional quantum states key distribution contributions practical

A Sequence Image Matching Method Based on Improved high-dimensional Combined Features

在线全文

学校读者我要写书评

暂无评论

Transactions of Nanjing University of Aeronautics and Astronautics 2018年第5期35卷 820-828页

作者： Leng Xuefei Gong Zhe Fu Runzhe Liu Yang College of Astronautics Nanjing University of Aeronautics and Astronautics

Image matching technology is theoretically significant and practically promising in the field of autonomous *** shortcomings of existing image matching navigation technologies,the concept of high-dimensional combined feature is presented based on sequence image matching *** balance between the distribution of high-dimensional combined features and the shortcomings of the only use of geometric relations,we propose a method based on Delaunay triangulation to improve the feature,and add the regional characteristics of the features together with their geometric ***,k-nearest neighbor(KNN)algorithm is adopted to optimize searching *** results show that the matching can be realized at the rotation angle of-8°to 8°and the scale factor of 0.9 to 1.1,and when the image size is 160 pixel×160 pixel,the matching time is less than 0.5 ***,the proposed algorithm can substantially reduce computational complexity,improve the matching speed,and exhibit robustness to the rotation and scale changes.

关键词： sequence image matching navigation Delaunay triangulation high-dimensional combined feature k-nearest neighbor