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On convergence of covariance matrix of empirical Bayes hyper-parameter estimator

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Control Theory and Technology 2024年第2期22卷 149-162页

作者： Yue Ju Biqiang Mu Tianshi Chen School of data science and Shenzhen Research institute of Big data The Chinese University of Hong KongShenzhenShenzhen518172GuangdongChina Division of Decision and Control Systems School of Electrical Engineering and Computer ScienceKTH Royal Institute of Technology10044StockholmSweden Key Laboratory of Systems and Control Institute of Systems ScienceAcademy of Mathematics and System ScienceChinese Academy of SciencesBeijing100190China

Regularized system identification has become the research frontier of system identification in the past decade.One related core subject is to study the convergence properties of various hyper-parameter estimators as the sample size goes to infinity.In this paper,we consider one commonly used hyper-parameter estimator,the empirical Bayes(EB).Its convergence in distribution has been studied,and the explicit expression of the covariance matrix of its limiting distribution has been given.However,what we are truly interested in are factors contained in the covariance matrix of the EB hyper-parameter estimator,and then,the convergence of its covariance matrix to that of its limiting distribution is required.In general,the convergence in distribution of a sequence of random variables does not necessarily guarantee the convergence of its covariance matrix.Thus,the derivation of such convergence is a necessary complement to our theoretical analysis about factors that influence the convergence properties of the EB hyper-parameter estimator.In this paper,we consider the regularized finite impulse response(FIR)model estimation with deterministic inputs,and show that the covariance matrix of the EB hyper-parameter estimator converges to that of its limiting distribution.Moreover,we run numerical simulations to demonstrate the efficacy of ourtheoretical results.

关键词： Regularized system identification Hyper-parameter estimator Empirical Bayes Convergence of covariance matrix

On the Pathwise Uniqueness of Solutions of One-dimensional Reflected Stochastic Differential Equations with Jumps

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Acta Mathematicae Applicatae Sinica 2024年第1期40卷 149-163页

作者： Hua Zhang School of Statistics and data science&Key Laboratory of data science in Finance and Economics Jiangxi University of Finance and EconomicsNanchang330013China

In this paper, we are concerned with the problem of the pathwise uniqueness of one-dimensional reflected stochastic differential equations with jumps under the assumption of non-Lipschitz continuous coefficients whose... 详细信息

关键词： reflected diffusion processes with jumps pathwise uniqueness local time Meyer It?'s formula

Compressed data Separation via ?q-Split Analysis with ?∞-Constraint

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Acta Mathematica Sinica,English Series 2024年第7期40卷 1655-1673页

作者： Ming Yang GU Song LI Jun Hong LIN School of Mathematical science Zhejiang University Center for data science Zhejiang University

In this paper, we study compressed data separation（CDS） problem, i.e., sparse data separation from a few linear random measurements. We propose the nonconvex ?q-split analysis with ?∞-constraint and 0 < q ≤ 1. We call the algorithm ?q-split-analysis Dantzig selector（?q-split-analysis DS）. We show that the two distinct subcomponents that are approximately sparse in terms of two different dictionaries could be stably approximated via the ?q-split-analysis DS, provided that the measurement matrix satisfies either a classical D-RIP（Restricted Isometry Property with respect to Dictionaries and ?2norm） or a relatively new（D, q）-RIP（RIP with respect to Dictionaries and ?q-quasi norm） condition and the two different dictionaries satisfy a mutual coherence condition between them.For the Gaussian random measurements, the measurement number needed for the（D, q）-RIP condition is far less than those needed for the D-RIP condition and the（D, 1）-RIP condition when q is small enough.

关键词： data separation ℓ q -split analysis Dantzig selector frames restricted isometry property compressed sensing 94A12 41A29 65T99 94A20

Simple real-time high-sensitivity heterodyne coherent optical transceiver at intraplane satellite communication

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Chinese Optics Letters 2024年第3期22卷 7-13页

作者：曲元哲张倩武王演祎陈彦昊龚乐为刘紫玥张俊杰李迎春陈健宋英雄 Key Laboratory of Specialty Optics and Optical Access Networks Shanghai Institute for Advanced Communication and Data ScienceShanghai UniversityShanghai 200444China

In this paper,we demonstrate a high-sensitivity and real-time heterodyne coherent optical transceiver for intraplane satellite communication,without digital-to-analog converter(DAC)devices and an optical phase lock loop(OPLL).Based on the scheme,a real-time sensitivity of-49 dBm is achieved at 5 Gbps QPSK.Because DAC is not needed at the transmitter,as well as OPLL at the receiver,this reduces the system cost.Furthermore,the least required Rx ADC bit-width is also discussed.Through theoretical analysis and experimental results,our cost-effective transceiver satisfies the scenario and could be a promising component for future application.

关键词： real-time coherent transceiver heterodyning intraplane satellite optical communication

Sensitivity impacts owing to the variations in the type of zero-range pairing forces on the fission properties using the density functional theory

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Nuclear science and Techniques 2024年第3期35卷 198-207页

作者： Yang Su Ze-Yu Li Li-Le Liu Guo-Xiang Dong Xiao-Bao Wang Yong-Jing Chen China Nuclear data Center China Institute of Atomic EnergyBeijing 102413China School of science Huzhou UniversityHuzhou 313000China

Using the Skyrme density functional theory,potential energy surfaces of^(240)Pu with constraints on the axial quadrupole and octupole deformations(q_(20)and q_(30))were calculated.The volume-like and surface-like pairing forces,as well as a combination of these two forces,were used for the Hartree–Fock–Bogoliubov approximation.Variations in the least-energy fission path,fission barrier,pairing energy,total kinetic energy,scission line,and mass distribution of the fission fragments based on the different forms of the pairing forces were analyzed and discussed.The fission dynamics were studied based on the timedependent generator coordinate method plus the Gaussian overlap approximation.The results demonstrated a sensitivity of the mass and charge distributions of the fission fragments on the form of the pairing force.Based on the investigation of the neutron-induced fission of^(239)Pu,among the volume,mixed,and surface pairing forces,the mixed pairing force presented a good reproduction of the experimental data.

关键词： Nuclear fission Density functional theory Pairing force Potential energy surfaces Fission fragment distribution

False Negative Sample Detection for Graph Contrastive Learning

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Tsinghua science and Technology 2024年第2期29卷 529-542页

作者： Binbin Zhang Li Wang College of data science Taiyuan University of TechnologyJinzhong 030600China

Recently,self-supervised learning has shown great potential in Graph Neural Networks (GNNs) through contrastive learning,which aims to learn discriminative features for each node without label information. The key to graph contrastive learning is data augmentation. The anchor node regards its augmented samples as positive samples,and the rest of the samples are regarded as negative samples,some of which may be positive samples. We call these mislabeled samples as “false negative” samples,which will seriously affect the final learning effect. Since such semantically similar samples are ubiquitous in the graph,the problem of false negative samples is very significant. To address this issue,the paper proposes a novel model,False negative sample Detection for Graph Contrastive Learning (FD4GCL),which uses attribute and structure-aware to detect false negative samples. Experimental results on seven datasets show that FD4GCL outperforms the state-of-the-art baselines and even exceeds several supervised methods.

关键词： graph representation learning contrastive learning false negative sample detection

Flexible, efficient, and accurate tests for epidemics

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science China Mathematics 2024年第8期67卷 1881-1898页

作者： Linjiajie Fang Bing-Yi Jing Shen Ling Qiyue Wang Qing Yang data science and Analytics Thrust The Hong Kong University of Science and Technology Department of Statistics and data science Southern University of Science and Technology Department of Mathematics and Statistics Dalhousie University Department of Mathematics The Hong Kong University of Science and Technology

Group testing involves discovering a small subset of distinguished subjects from a large population while efficiently reducing the total number of tests. It has been widely used for industrial testing, information technology, and biology, especially epidemic screening. Tests, in reality, are noisy for the presence of false outcomes. Some tests are accurate but time-consuming, while others are cheaper but less accurate. Exactly which test to use is constrained by various considerations, such as availability, cost, accuracy, and efficiency.In this paper, we propose flexible, efficient, and accurate tests(FEATs). FEATs are based on group testing with simple but careful designs by incorporating ideas such as close contact cliques and repeated tests. FEATs could dramatically improve the efficiency or accuracy of existing tests. For example, for accurate but slow tests, the FEAT can improve efficiency multiple times without compromising accuracy. On the other hand,for fast but inaccurate tests, the FEAT can sharply reduce the false-negative rate(FNR) and significantly increase efficiency. Theoretical justifications are provided. We point out some scenarios where the FEAT can be effectively employed.

关键词： epidemiology control blood testing testing efficiency testing accuracy

Cohomology groups of a new class of Kadison-Singer algebras

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science China Mathematics 2024年第3期67卷 593-606页

作者： Guangyu An Xing Cheng Jun Sheng School of Mathematics and data science Shaanxi University of Science and TechnologyXi’an 710021China

Let N be a maximal discrete nest on an infinite-dimensional separable Hilbert space H,ξ=∑^(∞)_(n=1)en/2n be a separating vector for the commutant N',E_(ξ)be the projection from H onto the subspace[Cξ]spanned by the vectorξ,and Q be the projection from K=H⊕H⊕H onto the closed subspace{(η,η,η)^(T):η∈H}.Suppose that L is the projection lattice generated by the projections(E_(ξ) 0 0 0 0 0 0 0 0),{(E 0 0 0 0 0 0 0 0):E∈N},(I 0 0 0 I 0 0 0 0) and Q.We show that L is a Kadison-Singer lattice with the trivial commutant.Moreover,we prove that every n-th bounded cohomology group H~n(AlgL,B(K))with coefficients in B(K)is trivial for n≥1.

关键词： Kadison-Singer algebra Kadison-Singer lattice derivation cohomology group

Novel Rifle Number Recognition Based on Improved YOLO in Military Environment

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Computers, Materials & Continua 2024年第1期78卷 249-263页

作者： Hyun Kwon Sanghyun Lee Department of Artificial Intelligence and data science Korea Military AcademySeoulKorea Graduate School of Information Security Korea Advanced Institute of Science and TechnologyDaejeonKorea

Deep neural networks perform well in image recognition,object recognition,pattern analysis,and speech recog-nition.In military applications,deep neural networks can detect equipment and recognize objects.In military equipment,it is necessary to detect and recognize rifle management,which is an important piece of equipment,using deep neural networks.There have been no previous studies on the detection of real rifle numbers using real rifle image datasets.In this study,we propose a method for detecting and recognizing rifle numbers when rifle image data are insufficient.The proposed method was designed to improve the recognition rate of a specific dataset using data fusion and transfer learningmethods.In the proposed method,real rifle images and existing digit images are fusedas trainingdata,andthe final layer is transferredto theYolov5 algorithmmodel.The detectionand recognition performance of rifle numbers was improved and analyzed using rifle image and numerical datasets.We used actual rifle image data(K-2 rifle)and numeric image datasets,as an experimental environment.TensorFlow was used as the machine learning library.Experimental results show that the proposed method maintains 84.42% accuracy,73.54% precision,81.81% recall,and 77.46% F1-score in detecting and recognizing rifle numbers.The proposed method is effective in detecting rifle numbers.

关键词： Machine learning deep neural network rifle number recognition detection