Most prevailing attention mechanism modules in contemporary research are convolutionbased modules,and while these modules contribute to enhancing the accuracy of deep learning networks in visual tasks,they concurrentl...Most prevailing attention mechanism modules in contemporary research are convolutionbased modules,and while these modules contribute to enhancing the accuracy of deep learning networks in visual tasks,they concurrently augment the overall model complexity.To address the problem,this paper proposes a plug-and-play algorithm that does not increase the complexity of the model,Laplacian attention(LA).The LA algorithm first calculates the similarity distance between feature points in the feature space and feature channel and constructs the residual Laplacian matrix between feature points through the similarity distance and Gaussian kernel.This construction serves to segregate non-similar feature points while aggregating those with similarities.Ultimately,the LA algorithm allocates the outputs of the feature channel and the feature space adaptively to derive the final LA outputs.Crucially,the LA algorithm is confined to the forward computation process and does not involve backpropagation or any parameter learning.The LA algorithm undergoes comprehensive experimentation on three distinct datasets—namely Cifar-10,miniImageNet,and Pascal VOC 2012.The experimental results demonstrate that,compared with the advanced attention mechanism modules in recent years,such as SENet,CBAM,ECANet,coordinate attention,and triplet attention,the LA algorithm exhibits superior performance across image classification,object detection and semantic segmentation tasks.展开更多
In this paper,we investigate the weighted Dirichlet eigenvalue problem of polynomial operator of the drifting Laplacian on the cigar soliton■as follows■where is a positive continuous function on,denotes the outward ...In this paper,we investigate the weighted Dirichlet eigenvalue problem of polynomial operator of the drifting Laplacian on the cigar soliton■as follows■where is a positive continuous function on,denotes the outward unit normal to the boundary,and are two nonnegative constants.We establish some universal inequalities for eigenvalues of this problem.展开更多
In this paper,we consider the p-Laplacian Schrödinger-Poisson equation with L^(2)-norm constraint-Δ_(p)u+|u|^(p-2)u+λu+(1/4π|x|*|u|^(2))u=|u|^(q-2)u,x∈R^(3),where 2≤p<3,5p/3<q<p*=3p/3-p,λ>0 is a...In this paper,we consider the p-Laplacian Schrödinger-Poisson equation with L^(2)-norm constraint-Δ_(p)u+|u|^(p-2)u+λu+(1/4π|x|*|u|^(2))u=|u|^(q-2)u,x∈R^(3),where 2≤p<3,5p/3<q<p*=3p/3-p,λ>0 is a Lagrange multiplier.We obtain the critical point of the corresponding functional of the problem on mass constraint by the variational method and the Mountain pass lemma,and then find a normalized solution to this equation.展开更多
A graph G possesses Hamiltonian s-properties when G is Hamilton-connected if s=1,Hamiltonian if s=0,and traceable if s=-1.Let S_A(G)=λ_n(G)-λ_1(G)and S_L(G)=μ_n(G)-μ_2(G)be the spread and the Laplacian spread of G...A graph G possesses Hamiltonian s-properties when G is Hamilton-connected if s=1,Hamiltonian if s=0,and traceable if s=-1.Let S_A(G)=λ_n(G)-λ_1(G)and S_L(G)=μ_n(G)-μ_2(G)be the spread and the Laplacian spread of G,respectively,whereλ_n(G)andλ_1(G)are the largest and smallest eigenvalues of G,andμ_n(G)andμ_2(G)are the largest and second smallest Laplacian eigenvalues of G,respectively.In this paper,we shall present two sufficient conditions involving S_A(G)and S_L(G)for a k-connected graph to possess Hamiltonian s-properties,respectively.We also derive a sufficient condition on the Laplacian eigenratio μ2(G)/μ(G) for a k-connected graph to possess Hamiltonian s-properties.展开更多
基金National Natural Science Foundation of China,Grant/Award Number:61967012。
文摘Most prevailing attention mechanism modules in contemporary research are convolutionbased modules,and while these modules contribute to enhancing the accuracy of deep learning networks in visual tasks,they concurrently augment the overall model complexity.To address the problem,this paper proposes a plug-and-play algorithm that does not increase the complexity of the model,Laplacian attention(LA).The LA algorithm first calculates the similarity distance between feature points in the feature space and feature channel and constructs the residual Laplacian matrix between feature points through the similarity distance and Gaussian kernel.This construction serves to segregate non-similar feature points while aggregating those with similarities.Ultimately,the LA algorithm allocates the outputs of the feature channel and the feature space adaptively to derive the final LA outputs.Crucially,the LA algorithm is confined to the forward computation process and does not involve backpropagation or any parameter learning.The LA algorithm undergoes comprehensive experimentation on three distinct datasets—namely Cifar-10,miniImageNet,and Pascal VOC 2012.The experimental results demonstrate that,compared with the advanced attention mechanism modules in recent years,such as SENet,CBAM,ECANet,coordinate attention,and triplet attention,the LA algorithm exhibits superior performance across image classification,object detection and semantic segmentation tasks.
基金Supported by National Natural Science Foundation of China(11001130,12272062)Fundamental Research Funds for the Central Universities(30917011335).
文摘In this paper,we investigate the weighted Dirichlet eigenvalue problem of polynomial operator of the drifting Laplacian on the cigar soliton■as follows■where is a positive continuous function on,denotes the outward unit normal to the boundary,and are two nonnegative constants.We establish some universal inequalities for eigenvalues of this problem.
基金supported by the National Natural Science Foundation of China(No.12461024)the Natural Science Research Project of Department of Education of Guizhou Province(Nos.QJJ2023012,QJJ2023061,QJJ2023062)the Natural Science Research Project of Guizhou Minzu University(No.GZMUZK[2022]YB06)。
文摘In this paper,we consider the p-Laplacian Schrödinger-Poisson equation with L^(2)-norm constraint-Δ_(p)u+|u|^(p-2)u+λu+(1/4π|x|*|u|^(2))u=|u|^(q-2)u,x∈R^(3),where 2≤p<3,5p/3<q<p*=3p/3-p,λ>0 is a Lagrange multiplier.We obtain the critical point of the corresponding functional of the problem on mass constraint by the variational method and the Mountain pass lemma,and then find a normalized solution to this equation.
基金Supported by NSFC(Nos.12171089,12271235)NSF of Fujian Province(No.2021J02048)。
文摘A graph G possesses Hamiltonian s-properties when G is Hamilton-connected if s=1,Hamiltonian if s=0,and traceable if s=-1.Let S_A(G)=λ_n(G)-λ_1(G)and S_L(G)=μ_n(G)-μ_2(G)be the spread and the Laplacian spread of G,respectively,whereλ_n(G)andλ_1(G)are the largest and smallest eigenvalues of G,andμ_n(G)andμ_2(G)are the largest and second smallest Laplacian eigenvalues of G,respectively.In this paper,we shall present two sufficient conditions involving S_A(G)and S_L(G)for a k-connected graph to possess Hamiltonian s-properties,respectively.We also derive a sufficient condition on the Laplacian eigenratio μ2(G)/μ(G) for a k-connected graph to possess Hamiltonian s-properties.
基金Supported by Natural Science Foundation of Xinjiang Uygur Autonomous Region(2021D01B35)Natural Science Foundation of colleges and universities in Xinjiang Uygur Au-tonomous Region(XJEDU2021Y048)Doctoral Initiation Fund of Xinjiang Institute of Engineering(2020xgy012302).
基金Natural Science Foundation of Xinjiang Uygur Autonomous Region(2021D01B35)Natural Science Foundation of colleges and universities in Xinjiang Uygur Autonomous Region(XJEDU2021Y048)。
