In this article, authors study the growth of Laplace-Stieltjes transform with zero order convergent in the right half-plane, define the exponential order and the exponential low order, and find the relations between t...In this article, authors study the growth of Laplace-Stieltjes transform with zero order convergent in the right half-plane, define the exponential order and the exponential low order, and find the relations between them. Some results similar to Dirichlet series are obtained.展开更多
The first aim of this paper is to investigate the growth of the entire function defined by the Laplace-Stieltjes transform converges on the whole complex plane.By introducing the concept of generalized order,we obtain...The first aim of this paper is to investigate the growth of the entire function defined by the Laplace-Stieltjes transform converges on the whole complex plane.By introducing the concept of generalized order,we obtain two equivalence theorems of Laplace-Stiettjes transforms related to the generalized order,A_(n)^(*)andλ_(n).The second purpose of this paper is to study the problem on the approximation of this Laplace-Stieltjes transform.We also obtain some theorems about the generalized order,the error,and the coefficients of Laplace-Stieltjes transforms,which are generalization and improvement of the previous results.展开更多
In the present paper,we have considered the approximation of analytic functions represented by Laplace-Stieltjes transformations using sequence of definite integrals. We have characterized their order and type in term...In the present paper,we have considered the approximation of analytic functions represented by Laplace-Stieltjes transformations using sequence of definite integrals. We have characterized their order and type in terms of the rate of decrease of E;(F,β) where E;(F,β) is the error in approximating of the function F(s) by definite integral polynomials in the half plane Res≤β<α.展开更多
针对无人机场景下行人重识别所呈现的多视角多尺度特点,以及传统的基于卷积神经网络的行人重识别算法受限于局部感受野结构和下采样操作,很难对行人图像的全局特征进行提取且图像空间特征分辨率不高。提出一种无人机场景下基于Transfor...针对无人机场景下行人重识别所呈现的多视角多尺度特点,以及传统的基于卷积神经网络的行人重识别算法受限于局部感受野结构和下采样操作,很难对行人图像的全局特征进行提取且图像空间特征分辨率不高。提出一种无人机场景下基于Transformer的轻量化行人重识别(Lightweight Transformer-based Person Re-Identification,LTReID)算法,利用多头多注意力机制从全局角度提取人体不同部分特征,使用Circle损失和边界样本挖掘损失,以提高图像特征提取和细粒度图像检索性能,并利用快速掩码搜索剪枝算法对Transformer模型进行训练后轻量化,以提高模型的无人机平台部署能力。更进一步,提出一种可学习的面向无人机场景的空间信息嵌入,在训练过程中通过学习获得优化的非视觉信息,以提取无人机多视角下行人的不变特征,提升行人特征识别的鲁棒性。最后,在实际的无人机行人重识别数据库中,讨论了在不同量级主干网和不同剪枝率情况下所提LTReID算法的行人重识别性能,并与多种行人重识别算法进行了性能对比,结果表明了所提算法的有效性和优越性。展开更多
文摘In this article, authors study the growth of Laplace-Stieltjes transform with zero order convergent in the right half-plane, define the exponential order and the exponential low order, and find the relations between them. Some results similar to Dirichlet series are obtained.
基金supported by the National Natural Science Foundation of China (11561033)the Natural Science Foundation of Jiangxi Province in China (20181BAB201001)+4 种基金the Foundation of Education Department of Jiangxi (GJJ190876, GJJ190895,GJJ202303) of Chinasupported by Guangdong Natural Science Foundation(2018A030313954)Guangdong University (New Generation Information Technology) Key Field Project(2020ZDZX3019)Project of Guangdong Province Innovative Team (2020WCXTD011)Guangdong Provincial Government’s project “Promoting the construction of the Guangdong-Hong Kong-Macao Greater Bay Area and building a new open economic system”.
文摘The first aim of this paper is to investigate the growth of the entire function defined by the Laplace-Stieltjes transform converges on the whole complex plane.By introducing the concept of generalized order,we obtain two equivalence theorems of Laplace-Stiettjes transforms related to the generalized order,A_(n)^(*)andλ_(n).The second purpose of this paper is to study the problem on the approximation of this Laplace-Stieltjes transform.We also obtain some theorems about the generalized order,the error,and the coefficients of Laplace-Stieltjes transforms,which are generalization and improvement of the previous results.
文摘In the present paper,we have considered the approximation of analytic functions represented by Laplace-Stieltjes transformations using sequence of definite integrals. We have characterized their order and type in terms of the rate of decrease of E;(F,β) where E;(F,β) is the error in approximating of the function F(s) by definite integral polynomials in the half plane Res≤β<α.
文摘针对无人机场景下行人重识别所呈现的多视角多尺度特点,以及传统的基于卷积神经网络的行人重识别算法受限于局部感受野结构和下采样操作,很难对行人图像的全局特征进行提取且图像空间特征分辨率不高。提出一种无人机场景下基于Transformer的轻量化行人重识别(Lightweight Transformer-based Person Re-Identification,LTReID)算法,利用多头多注意力机制从全局角度提取人体不同部分特征,使用Circle损失和边界样本挖掘损失,以提高图像特征提取和细粒度图像检索性能,并利用快速掩码搜索剪枝算法对Transformer模型进行训练后轻量化,以提高模型的无人机平台部署能力。更进一步,提出一种可学习的面向无人机场景的空间信息嵌入,在训练过程中通过学习获得优化的非视觉信息,以提取无人机多视角下行人的不变特征,提升行人特征识别的鲁棒性。最后,在实际的无人机行人重识别数据库中,讨论了在不同量级主干网和不同剪枝率情况下所提LTReID算法的行人重识别性能,并与多种行人重识别算法进行了性能对比,结果表明了所提算法的有效性和优越性。