The Poisson point process(PPP) has been widely used in wireless network modeling and performance analysis due to the independence between its nodes. Therefore, it may not be a suitable model for many of the exclusive ...The Poisson point process(PPP) has been widely used in wireless network modeling and performance analysis due to the independence between its nodes. Therefore, it may not be a suitable model for many of the exclusive networks between the nodes. This paper analyzes the energy efficiency(EE) and optimizes the two-tier heterogeneous cellular networks(Het Nets). Considering the mutual exclusion between macro base stations(MBSs) distribution, the deployment of MBSs is modeled by the Matérn hard-core point process(MHCPP), and the deployment of pico base stations(PBSs) is modeled by the PPP. We adopt a simple approximation method to study the signal to interference ratio(SIR) distribution in two-tier MHCPP-PPP networks and then derive the coverage probabilities, the average data rates and the energy efficiency of Het Nets. Finally, an optimization algorithm is proposed to improve the EE of Het Nets by controlling the transmit power of PBSs. The simulation results show that the EE of a system can be effectively improved by selecting the appropriate transmit power for the PBSs. In addition, two-tier MHCPP-PPP Het Nets have higher energy efficiency than two-tier PPP-PPP Het Nets.展开更多
Let {Xi}i=1^∞ be a standardized stationary Gaussian sequence with covariance function τ（n） =EX1Xn＋1, Sn =∑i=1^nXi,and X^-n=Sn/n.And let Nn be the point process formed by the exceedances of random level （x/√2 l...Let {Xi}i=1^∞ be a standardized stationary Gaussian sequence with covariance function τ（n） =EX1Xn＋1, Sn =∑i=1^nXi,and X^-n=Sn/n.And let Nn be the point process formed by the exceedances of random level （x/√2 log n＋√2 log n-log（4π log n）/2√log n） √1-τ（n） ＋ X^-n by X1,X2,…, Xn. Under some mild conditions, Nn and Sn are asymptotically independent, and Nn converges weakly to a Poisson process on （0,1].展开更多
In order to analyze the failure data from repairable systems, the homogeneous Poisson process (HPP) is usually used. In general, HPP cannot be applied to analyze the entire life cycle of a complex, re-pairable system ...In order to analyze the failure data from repairable systems, the homogeneous Poisson process (HPP) is usually used. In general, HPP cannot be applied to analyze the entire life cycle of a complex, re-pairable system because the rate of occurrence of failures (ROCOF) of the system changes over time rather than remains stable. However, from a practical point of view, it is always preferred to apply the simplest method to address problems and to obtain useful practical results. Therefore, we attempted to use the HPP model to analyze the failure data from real repairable systems. A graphic method and the Laplace test were also used in the analysis. Results of numerical applications show that the HPP model may be a useful tool for the entire life cycle of repairable systems.展开更多
A engineering system is usually repairable, and failure process of a repairable by a failure point process. The power law model is a commonly used approach to model syst the em is often described failure point process...A engineering system is usually repairable, and failure process of a repairable by a failure point process. The power law model is a commonly used approach to model syst the em is often described failure point process. This paper introduces the concept and model for the failure process of repairable system. The method of parameter estimation is developed, and failure observations are fitted into a power-law model by using the least square method. Two applications of the pressent model are discussed according to the practical failure data of the central cooling system of a nuclear power plant. One application is determining the optimal overhaul time, and the other is evaluating the quality of maintenance. This paper provides references for the overhaul decision making and maintenance quality evaluation in reality.展开更多
Willing to work in reliability theory in a general set up, under stochastically dependence conditions, we intend to characterize a not identically spare standby redundancy operation through compensator transform under...Willing to work in reliability theory in a general set up, under stochastically dependence conditions, we intend to characterize a not identically spare standby redundancy operation through compensator transform under a complete information level, the physic approach, that is, observing its component lifetime. We intend to optimize system reliability under standby redundancy allocation of its components, particularly, under minimal standby redundancy. To get results, we will use a coherent system representation through a signature point process.展开更多
In this study,we investigate the well-posedness of exponential growth backward stochastic differcntial cquations(BSDEs)drivcn by a markcd point process(MPP)under unbounded terminal conditions.Our analysis utilizes a f...In this study,we investigate the well-posedness of exponential growth backward stochastic differcntial cquations(BSDEs)drivcn by a markcd point process(MPP)under unbounded terminal conditions.Our analysis utilizes a fixed-point argument,the O-method,and an approximation procedurc.Additionally,wc cstablish the solvability of mean-reflected exponential growth BSDEs driven by the MPP using the-method.展开更多
A drought is when reduced rainfall leads to a water crisis,impacting daily life.Over recent decades,droughts have affected various regions,including South Sulawesi,Indonesia.This study aims to map the probability of m...A drought is when reduced rainfall leads to a water crisis,impacting daily life.Over recent decades,droughts have affected various regions,including South Sulawesi,Indonesia.This study aims to map the probability of meteo-rological drought months using the 1-month Standardized Precipitation Index(SPI)in South Sulawesi.Based on SPI,meteorological drought characteristics are inversely proportional to drought event intensity,which can be modeled using a Non-Homogeneous Poisson Process,specifically the Power Law Process.The estimation method employs Maximum Likelihood Estimation(MLE),where drought event intensities are treated as random variables over a set time interval.Future drought months are estimated using the cumulative Power Law Process function,with theβandγparameters more significant than 0.The probability of drought months is determined using the Non-Homogeneous Poisson Process,which models event occurrence over time,considering varying intensities.The results indicate that,of the 24 districts/cities in South Sulawesi,14 experienced meteorological drought based on the SPI and Power Law Process model.The estimated number of months of drought occurrence in the next 12 months is one month of drought with an occurrence probability value of 0.37 occurring in November in the Selayar,Bulukumba,Bantaeng,Jeneponto,Takalar and Gowa areas,in October in the Sinjai,Barru,Bone,Soppeng,Pinrang and Pare-pare areas,as well as in December in the Maros and Makassar areas.展开更多
Let N, N1, N2 be simple point processes on a LCCB space (E,) such that N=N1+N2, and p() be a measurable function with 0<p()<1 on (E,). Then any two of the following statements yield another two:(Ⅰ) N is a Poiss...Let N, N1, N2 be simple point processes on a LCCB space (E,) such that N=N1+N2, and p() be a measurable function with 0<p()<1 on (E,). Then any two of the following statements yield another two:(Ⅰ) N is a Poisson process;(Ⅱ) N1 is the p( )thinning of N, N2 is the (1-p())-thinning of N;(Ⅲ) N1 and N2 are independent;(Ⅳ) N1, N2 are Poisson processes with respect to a filtration {F(A), A}, whereF(A)={N1(B), N2(B), B, BA},i.e., for each bounded set A, N1(A) and N2(A) are Poisson variables, independent of F(A ).Indeed, only the fact, (Ⅱ)+(Ⅲ)(Ⅳ)+(Ⅰ), is new.展开更多
Airborne LiDAR(Light Detection and Ranging)is an evolving high-tech active remote sensing technology that has the capability to acquire large-area topographic data and can quickly generate DEM(Digital Elevation Model)...Airborne LiDAR(Light Detection and Ranging)is an evolving high-tech active remote sensing technology that has the capability to acquire large-area topographic data and can quickly generate DEM(Digital Elevation Model)products.Combined with image data,this technology can further enrich and extract spatial geographic information.However,practically,due to the limited operating range of airborne LiDAR and the large area of task,it would be necessary to perform registration and stitching process on point clouds of adjacent flight strips.By eliminating grow errors,the systematic errors in the data need to be effectively reduced.Thus,this paper conducts research on point cloud registration methods in urban building areas,aiming to improve the accuracy and processing efficiency of airborne LiDAR data.Meanwhile,an improved post-ICP(Iterative Closest Point)point cloud registration method was proposed in this study to determine the accurate registration and efficient stitching of point clouds,which capable to provide a potential technical support for applicants in related field.展开更多
In this paper, we study the joint limit distributions of point processes of exceedances and partial sums of multivariate Gaussian sequences and show that the point processes and partial sums are asymptotically indepen...In this paper, we study the joint limit distributions of point processes of exceedances and partial sums of multivariate Gaussian sequences and show that the point processes and partial sums are asymptotically independent under some mild conditions. As a result, for a sequence of standardized stationary Gaussian vectors, we obtain that the point process of exceedances formed by the sequence （centered at the sample mean） converges in distribution to a Poisson process and it is asymptotically independent of the partial sums. The asymptotic joint limit distributions of order statistics and partial sums are also investigated under different conditions.展开更多
Aims Recent mechanistic explanations for community assembly focus on the debates surrounding niche-based deterministic and dispersalbased stochastic models.This body of work has emphasized the importance of both habit...Aims Recent mechanistic explanations for community assembly focus on the debates surrounding niche-based deterministic and dispersalbased stochastic models.This body of work has emphasized the importance of both habitat filtering and dispersal limitation,and many of these works have utilized the assumption of species spatial independence to simplify the complexity of the spatial modeling in natural communities when given dispersal limitation and/or habitat filtering.One potential drawback of this simplification is that it does not consider species interactions and how they may influence the spatial distribution of species,phylogenetic and functional diversity.Here,we assess the validity of the assumption of species spatial independence using data from a subtropical forest plot in southeastern China.Methods We use the four most commonly employed spatial statistical models—the homogeneous Poisson process representing pure random effect,the heterogeneous Poisson process for the effect of habitat heterogeneity,the homogenous Thomas process for sole dispersal limitation and the heterogeneous Thomas process for joint effect of habitat heterogeneity and dispersal limitation—to investigate the contribution of different mechanisms in shaping the species,phylogenetic and functional structures of communities.Important Findings Our evidence from species,phylogenetic and functional diversity demonstrates that the habitat filtering and/or dispersal-based models perform well and the assumption of species spatial independence is relatively valid at larger scales(50×50 m).Conversely,at local scales(10×10 and 20×20 m),the models often fail to predict the species,phylogenetic and functional diversity,suggesting that the assumption of species spatial independence is invalid and that biotic interactions are increasingly important at these spatial scales.展开更多
Let D be a convolution semigroup of random measures or point processes on a locally compact second countable T 2space. There is a topological isomorphism from D into a subsemigroup of product topological semigroup (R ...Let D be a convolution semigroup of random measures or point processes on a locally compact second countable T 2space. There is a topological isomorphism from D into a subsemigroup of product topological semigroup (R +,+) N.D is a sequentially stable and D-separable ZH-semigroup, as well as a metrizable, stable and normable Hun semigroup, so it has the corresponding properties. In particular the author has a new and simple proof byZH-semigroup approach or Hun semigroup approach to show that D has property ILID (an infinitesimal array limit is infinitely divisible), and know the Baire types which some subsets of D belong in.展开更多
We show that the central limit theorem for linear statistics over determinantal point processes with J-Hermitian kernels holds under fairly general conditions.In particular,we establish the Gaussian limit for linear s...We show that the central limit theorem for linear statistics over determinantal point processes with J-Hermitian kernels holds under fairly general conditions.In particular,we establish the Gaussian limit for linear statistics over determinantal point processes on the union of two copies of Rdwhen the correlation kernels are J-Hermitian translation-invariant.展开更多
In this paper,we study a class of stochastic differential equations with additive noise that contains a non-stationary multifractional Brownian motion(mBm)with a Hurst parameter as a function of time and a Poisson poi...In this paper,we study a class of stochastic differential equations with additive noise that contains a non-stationary multifractional Brownian motion(mBm)with a Hurst parameter as a function of time and a Poisson point process of class(QL).The differential equation of this kind is motivated by the reserve processes in a general insurance model,in which between the claim payment and the past history of liability present the long term dependence.By using the variable order fractional calculus on the fractional Wiener-Poisson space and a multifractional derivative operator,and employing Girsanov theorem for multifractional Brownian motion,we prove the existence of weak solutions to the SDEs under consideration,As a consequence,we deduce the uniqueness in law and the pathwise uniqueness.展开更多
In this paper, we study the point process of state transitions in a regular Markov chain.Under a weaker condition, we prove that the point process is a 1-memory self-exciting point process and again obtain four useful...In this paper, we study the point process of state transitions in a regular Markov chain.Under a weaker condition, we prove that the point process is a 1-memory self-exciting point process and again obtain four useful formulas of the transition frequency, the absorbing distribution,the renewal distribution and the entering probability. As an applicstion, using these formulas we derive the LS transform of the busy period for the M/M/∞ queue.展开更多
As 3D acquisition technology develops and 3D sensors become increasingly affordable,large quantities of 3D point cloud data are emerging.How to effectively learn and extract the geometric features from these point clo...As 3D acquisition technology develops and 3D sensors become increasingly affordable,large quantities of 3D point cloud data are emerging.How to effectively learn and extract the geometric features from these point clouds has become an urgent problem to be solved.The point cloud geometric information is hidden in disordered,unstructured points,making point cloud analysis a very challenging problem.To address this problem,we propose a novel network framework,called Tree Graph Network(TGNet),which can sample,group,and aggregate local geometric features.Specifically,we construct a Tree Graph by explicit rules,which consists of curves extending in all directions in point cloud feature space,and then aggregate the features of the graph through a cross-attention mechanism.In this way,we incorporate more point cloud geometric structure information into the representation of local geometric features,which makes our network perform better.Our model performs well on several basic point clouds processing tasks such as classification,segmentation,and normal estimation,demonstrating the effectiveness and superiority of our network.Furthermore,we provide ablation experiments and visualizations to better understand our network.展开更多
In this paper, the least square estimator in the problem of multiple change points estimation is studied. Here, the moving-average processes of ALNQD sequence in the mean shifts are discussed. When the number of chang...In this paper, the least square estimator in the problem of multiple change points estimation is studied. Here, the moving-average processes of ALNQD sequence in the mean shifts are discussed. When the number of change points is known, the rate of convergence of change-points estimation is derived. The result is also true for p-mixing, φ-mixing, a-mixing, associated and negatively associated sequences under suitable conditions.展开更多
Light detection and ranging(LiDAR)sensors play a vital role in acquiring 3D point cloud data and extracting valuable information about objects for tasks such as autonomous driving,robotics,and virtual reality(VR).Howe...Light detection and ranging(LiDAR)sensors play a vital role in acquiring 3D point cloud data and extracting valuable information about objects for tasks such as autonomous driving,robotics,and virtual reality(VR).However,the sparse and disordered nature of the 3D point cloud poses significant challenges to feature extraction.Overcoming limitations is critical for 3D point cloud processing.3D point cloud object detection is a very challenging and crucial task,in which point cloud processing and feature extraction methods play a crucial role and have a significant impact on subsequent object detection performance.In this overview of outstanding work in object detection from the 3D point cloud,we specifically focus on summarizing methods employed in 3D point cloud processing.We introduce the way point clouds are processed in classical 3D object detection algorithms,and their improvements to solve the problems existing in point cloud processing.Different voxelization methods and point cloud sampling strategies will influence the extracted features,thereby impacting the final detection performance.展开更多
To address the current issues of inaccurate segmentation and the limited applicability of segmentation methods for building facades in point clouds, we propose a facade segmentation algorithm based on optimal dual-sca...To address the current issues of inaccurate segmentation and the limited applicability of segmentation methods for building facades in point clouds, we propose a facade segmentation algorithm based on optimal dual-scale feature descriptors. First, we select the optimal dual-scale descriptors from a range of feature descriptors. Next, we segment the facade according to the threshold value of the chosen optimal dual-scale descriptors. Finally, we use RANSAC (Random Sample Consensus) to fit the segmented surface and optimize the fitting result. Experimental results show that, compared to commonly used facade segmentation algorithms, the proposed method yields more accurate segmentation results, providing a robust data foundation for subsequent 3D model reconstruction of buildings.展开更多
基金partly supported by the National Natural Science Foundation of China(Grant No.61871241,No.61701221)the Natural Science Foundation of Jiangsu Province(No.BK20160781)+1 种基金Nantong Science and Technology Project(No.JC2018127,No.JC2019117)the Research Innovation Project for College Graduates of Jiangsu Province(No.KYLX16_0662)。
文摘The Poisson point process(PPP) has been widely used in wireless network modeling and performance analysis due to the independence between its nodes. Therefore, it may not be a suitable model for many of the exclusive networks between the nodes. This paper analyzes the energy efficiency(EE) and optimizes the two-tier heterogeneous cellular networks(Het Nets). Considering the mutual exclusion between macro base stations(MBSs) distribution, the deployment of MBSs is modeled by the Matérn hard-core point process(MHCPP), and the deployment of pico base stations(PBSs) is modeled by the PPP. We adopt a simple approximation method to study the signal to interference ratio(SIR) distribution in two-tier MHCPP-PPP networks and then derive the coverage probabilities, the average data rates and the energy efficiency of Het Nets. Finally, an optimization algorithm is proposed to improve the EE of Het Nets by controlling the transmit power of PBSs. The simulation results show that the EE of a system can be effectively improved by selecting the appropriate transmit power for the PBSs. In addition, two-tier MHCPP-PPP Het Nets have higher energy efficiency than two-tier PPP-PPP Het Nets.
基金Supported by the Program for Excellent Talents in Chongqing Higher Education Institutions (120060-20600204)
文摘Let {Xi}i=1^∞ be a standardized stationary Gaussian sequence with covariance function τ（n） =EX1Xn＋1, Sn =∑i=1^nXi,and X^-n=Sn/n.And let Nn be the point process formed by the exceedances of random level （x/√2 log n＋√2 log n-log（4π log n）/2√log n） √1-τ（n） ＋ X^-n by X1,X2,…, Xn. Under some mild conditions, Nn and Sn are asymptotically independent, and Nn converges weakly to a Poisson process on （0,1].
文摘In order to analyze the failure data from repairable systems, the homogeneous Poisson process (HPP) is usually used. In general, HPP cannot be applied to analyze the entire life cycle of a complex, re-pairable system because the rate of occurrence of failures (ROCOF) of the system changes over time rather than remains stable. However, from a practical point of view, it is always preferred to apply the simplest method to address problems and to obtain useful practical results. Therefore, we attempted to use the HPP model to analyze the failure data from real repairable systems. A graphic method and the Laplace test were also used in the analysis. Results of numerical applications show that the HPP model may be a useful tool for the entire life cycle of repairable systems.
基金supported by the National Natural Science Foundation of China(71771029)
文摘A engineering system is usually repairable, and failure process of a repairable by a failure point process. The power law model is a commonly used approach to model syst the em is often described failure point process. This paper introduces the concept and model for the failure process of repairable system. The method of parameter estimation is developed, and failure observations are fitted into a power-law model by using the least square method. Two applications of the pressent model are discussed according to the practical failure data of the central cooling system of a nuclear power plant. One application is determining the optimal overhaul time, and the other is evaluating the quality of maintenance. This paper provides references for the overhaul decision making and maintenance quality evaluation in reality.
文摘Willing to work in reliability theory in a general set up, under stochastically dependence conditions, we intend to characterize a not identically spare standby redundancy operation through compensator transform under a complete information level, the physic approach, that is, observing its component lifetime. We intend to optimize system reliability under standby redundancy allocation of its components, particularly, under minimal standby redundancy. To get results, we will use a coherent system representation through a signature point process.
基金supported by NSFC(Grant No.12371473)by the Tianyuan Fund for Mlathematics of NSFC(Grant No.12326603)。
文摘In this study,we investigate the well-posedness of exponential growth backward stochastic differcntial cquations(BSDEs)drivcn by a markcd point process(MPP)under unbounded terminal conditions.Our analysis utilizes a fixed-point argument,the O-method,and an approximation procedurc.Additionally,wc cstablish the solvability of mean-reflected exponential growth BSDEs driven by the MPP using the-method.
基金funded by Hasanuddin University,grant number 00309/UN4.22/PT.01.03/2024.
文摘A drought is when reduced rainfall leads to a water crisis,impacting daily life.Over recent decades,droughts have affected various regions,including South Sulawesi,Indonesia.This study aims to map the probability of meteo-rological drought months using the 1-month Standardized Precipitation Index(SPI)in South Sulawesi.Based on SPI,meteorological drought characteristics are inversely proportional to drought event intensity,which can be modeled using a Non-Homogeneous Poisson Process,specifically the Power Law Process.The estimation method employs Maximum Likelihood Estimation(MLE),where drought event intensities are treated as random variables over a set time interval.Future drought months are estimated using the cumulative Power Law Process function,with theβandγparameters more significant than 0.The probability of drought months is determined using the Non-Homogeneous Poisson Process,which models event occurrence over time,considering varying intensities.The results indicate that,of the 24 districts/cities in South Sulawesi,14 experienced meteorological drought based on the SPI and Power Law Process model.The estimated number of months of drought occurrence in the next 12 months is one month of drought with an occurrence probability value of 0.37 occurring in November in the Selayar,Bulukumba,Bantaeng,Jeneponto,Takalar and Gowa areas,in October in the Sinjai,Barru,Bone,Soppeng,Pinrang and Pare-pare areas,as well as in December in the Maros and Makassar areas.
文摘Let N, N1, N2 be simple point processes on a LCCB space (E,) such that N=N1+N2, and p() be a measurable function with 0<p()<1 on (E,). Then any two of the following statements yield another two:(Ⅰ) N is a Poisson process;(Ⅱ) N1 is the p( )thinning of N, N2 is the (1-p())-thinning of N;(Ⅲ) N1 and N2 are independent;(Ⅳ) N1, N2 are Poisson processes with respect to a filtration {F(A), A}, whereF(A)={N1(B), N2(B), B, BA},i.e., for each bounded set A, N1(A) and N2(A) are Poisson variables, independent of F(A ).Indeed, only the fact, (Ⅱ)+(Ⅲ)(Ⅳ)+(Ⅰ), is new.
基金Guangxi Key Laboratory of Spatial Information and Geomatics(21-238-21-12)Guangxi Young and Middle-aged Teachers’Research Fundamental Ability Enhancement Project(2023KY1196).
文摘Airborne LiDAR(Light Detection and Ranging)is an evolving high-tech active remote sensing technology that has the capability to acquire large-area topographic data and can quickly generate DEM(Digital Elevation Model)products.Combined with image data,this technology can further enrich and extract spatial geographic information.However,practically,due to the limited operating range of airborne LiDAR and the large area of task,it would be necessary to perform registration and stitching process on point clouds of adjacent flight strips.By eliminating grow errors,the systematic errors in the data need to be effectively reduced.Thus,this paper conducts research on point cloud registration methods in urban building areas,aiming to improve the accuracy and processing efficiency of airborne LiDAR data.Meanwhile,an improved post-ICP(Iterative Closest Point)point cloud registration method was proposed in this study to determine the accurate registration and efficient stitching of point clouds,which capable to provide a potential technical support for applicants in related field.
基金Supported by National Natural Science Foundation of China(Grant No.11171275)the Program for Excellent Talents in Chongqing Higher Education Institutions(Grant No.120060-20600204)supported by the Swiss National Science Foundation Project(Grant No.200021-134785)
文摘In this paper, we study the joint limit distributions of point processes of exceedances and partial sums of multivariate Gaussian sequences and show that the point processes and partial sums are asymptotically independent under some mild conditions. As a result, for a sequence of standardized stationary Gaussian vectors, we obtain that the point process of exceedances formed by the sequence （centered at the sample mean） converges in distribution to a Poisson process and it is asymptotically independent of the partial sums. The asymptotic joint limit distributions of order statistics and partial sums are also investigated under different conditions.
基金NSFC grant of National Natural Science Foundation of China(31170401)Dimensions of biodiversity grant of Natural Science Fundation(NSF 1046113)Natural Science Foundation of Zhejiang Province(Y5100361).
文摘Aims Recent mechanistic explanations for community assembly focus on the debates surrounding niche-based deterministic and dispersalbased stochastic models.This body of work has emphasized the importance of both habitat filtering and dispersal limitation,and many of these works have utilized the assumption of species spatial independence to simplify the complexity of the spatial modeling in natural communities when given dispersal limitation and/or habitat filtering.One potential drawback of this simplification is that it does not consider species interactions and how they may influence the spatial distribution of species,phylogenetic and functional diversity.Here,we assess the validity of the assumption of species spatial independence using data from a subtropical forest plot in southeastern China.Methods We use the four most commonly employed spatial statistical models—the homogeneous Poisson process representing pure random effect,the heterogeneous Poisson process for the effect of habitat heterogeneity,the homogenous Thomas process for sole dispersal limitation and the heterogeneous Thomas process for joint effect of habitat heterogeneity and dispersal limitation—to investigate the contribution of different mechanisms in shaping the species,phylogenetic and functional structures of communities.Important Findings Our evidence from species,phylogenetic and functional diversity demonstrates that the habitat filtering and/or dispersal-based models perform well and the assumption of species spatial independence is relatively valid at larger scales(50×50 m).Conversely,at local scales(10×10 and 20×20 m),the models often fail to predict the species,phylogenetic and functional diversity,suggesting that the assumption of species spatial independence is invalid and that biotic interactions are increasingly important at these spatial scales.
文摘Let D be a convolution semigroup of random measures or point processes on a locally compact second countable T 2space. There is a topological isomorphism from D into a subsemigroup of product topological semigroup (R +,+) N.D is a sequentially stable and D-separable ZH-semigroup, as well as a metrizable, stable and normable Hun semigroup, so it has the corresponding properties. In particular the author has a new and simple proof byZH-semigroup approach or Hun semigroup approach to show that D has property ILID (an infinitesimal array limit is infinitely divisible), and know the Baire types which some subsets of D belong in.
基金supported by National Natural Science Foundation of China (Grant Nos.Y7116335K1,11801547 and 11688101)supported by National Natural Science Foundation of China (Grant Nos.11722102 and 12026250)+1 种基金Shanghai Technology Innovation Project (Grant No.21JC1400800)Laboratory of Mathematics for Nonlinear Science,Ministry of Education of China。
文摘We show that the central limit theorem for linear statistics over determinantal point processes with J-Hermitian kernels holds under fairly general conditions.In particular,we establish the Gaussian limit for linear statistics over determinantal point processes on the union of two copies of Rdwhen the correlation kernels are J-Hermitian translation-invariant.
文摘In this paper,we study a class of stochastic differential equations with additive noise that contains a non-stationary multifractional Brownian motion(mBm)with a Hurst parameter as a function of time and a Poisson point process of class(QL).The differential equation of this kind is motivated by the reserve processes in a general insurance model,in which between the claim payment and the past history of liability present the long term dependence.By using the variable order fractional calculus on the fractional Wiener-Poisson space and a multifractional derivative operator,and employing Girsanov theorem for multifractional Brownian motion,we prove the existence of weak solutions to the SDEs under consideration,As a consequence,we deduce the uniqueness in law and the pathwise uniqueness.
文摘In this paper, we study the point process of state transitions in a regular Markov chain.Under a weaker condition, we prove that the point process is a 1-memory self-exciting point process and again obtain four useful formulas of the transition frequency, the absorbing distribution,the renewal distribution and the entering probability. As an applicstion, using these formulas we derive the LS transform of the busy period for the M/M/∞ queue.
基金supported by the National Natural Science Foundation of China (Grant Nos.91948203,52075532).
文摘As 3D acquisition technology develops and 3D sensors become increasingly affordable,large quantities of 3D point cloud data are emerging.How to effectively learn and extract the geometric features from these point clouds has become an urgent problem to be solved.The point cloud geometric information is hidden in disordered,unstructured points,making point cloud analysis a very challenging problem.To address this problem,we propose a novel network framework,called Tree Graph Network(TGNet),which can sample,group,and aggregate local geometric features.Specifically,we construct a Tree Graph by explicit rules,which consists of curves extending in all directions in point cloud feature space,and then aggregate the features of the graph through a cross-attention mechanism.In this way,we incorporate more point cloud geometric structure information into the representation of local geometric features,which makes our network perform better.Our model performs well on several basic point clouds processing tasks such as classification,segmentation,and normal estimation,demonstrating the effectiveness and superiority of our network.Furthermore,we provide ablation experiments and visualizations to better understand our network.
基金Supported by the National Natural Science Foundation of China（10471126）.
文摘In this paper, the least square estimator in the problem of multiple change points estimation is studied. Here, the moving-average processes of ALNQD sequence in the mean shifts are discussed. When the number of change points is known, the rate of convergence of change-points estimation is derived. The result is also true for p-mixing, φ-mixing, a-mixing, associated and negatively associated sequences under suitable conditions.
文摘Light detection and ranging(LiDAR)sensors play a vital role in acquiring 3D point cloud data and extracting valuable information about objects for tasks such as autonomous driving,robotics,and virtual reality(VR).However,the sparse and disordered nature of the 3D point cloud poses significant challenges to feature extraction.Overcoming limitations is critical for 3D point cloud processing.3D point cloud object detection is a very challenging and crucial task,in which point cloud processing and feature extraction methods play a crucial role and have a significant impact on subsequent object detection performance.In this overview of outstanding work in object detection from the 3D point cloud,we specifically focus on summarizing methods employed in 3D point cloud processing.We introduce the way point clouds are processed in classical 3D object detection algorithms,and their improvements to solve the problems existing in point cloud processing.Different voxelization methods and point cloud sampling strategies will influence the extracted features,thereby impacting the final detection performance.
文摘To address the current issues of inaccurate segmentation and the limited applicability of segmentation methods for building facades in point clouds, we propose a facade segmentation algorithm based on optimal dual-scale feature descriptors. First, we select the optimal dual-scale descriptors from a range of feature descriptors. Next, we segment the facade according to the threshold value of the chosen optimal dual-scale descriptors. Finally, we use RANSAC (Random Sample Consensus) to fit the segmented surface and optimize the fitting result. Experimental results show that, compared to commonly used facade segmentation algorithms, the proposed method yields more accurate segmentation results, providing a robust data foundation for subsequent 3D model reconstruction of buildings.
