AIM:To conduct a bibliometric analysis of research on artificial intelligence(AI)in the field of glaucoma to gain a comprehensive understanding of the current state of research and identify potential new directions fo...AIM:To conduct a bibliometric analysis of research on artificial intelligence(AI)in the field of glaucoma to gain a comprehensive understanding of the current state of research and identify potential new directions for future studies.METHODS:Relevant articles on the application of AI in the field of glaucoma from the Web of Science Core Collection were retrieved,covering the period from January 1,2013,to December 31,2022.In order to assess the contributions and co-occurrence relationships among different countries/regions,institutions,authors,and journals,CiteSpace and VOSviewer software were employed and the research hotspots and future trends within the field were identified.RESULTS:A total of 750 English articles published between 2013 and 2022 were collected,and the number of publications exhibited an overall increasing trend.The majority of the articles were from China,followed by the United States and India.National University of Singapore,Chinese Academy of Sciences,and Sun Yat-sen University made significant contributions to the published works.Weinreb RN and Fu HZ ranked first among authors and cited authors.American Journal of Ophthalmology is the most impactful academic journal in the field of AI application in glaucoma.The disciplinary scope of this field includes ophthalmology,computer science,mathematics,molecular biology,genetics,and other related disciplines.The clustering and identification of keyword nodes in the co-occurrence network reveal the evolving landscape of AI application in the field of glaucoma.Initially,the hot topics in this field were primarily“segmentation”,“classification”and“diagnosis”.However,in recent years,the focus has shifted to“deep learning”,“convolutional neural network”and“artificial intelligence”.CONCLUSION:With the rapid development of AI technology,scholars have shown increasing interest in its application in the field of glaucoma.Moreover,the application of AI in assisting treatment and predicting prognosis in glaucoma may become a future research hotspot.However,the reliability and interpretability of AI data remain pressing issues that require resolution.展开更多
Recently, M. Hanke and M. Neumann([4]) have derived a necessary and sufficient condition on a splitting of A = U-V, which leads to a fixed point system, such that the iterative sequence converges to the least squares ...Recently, M. Hanke and M. Neumann([4]) have derived a necessary and sufficient condition on a splitting of A = U-V, which leads to a fixed point system, such that the iterative sequence converges to the least squares solution of minimum a-norm of the system Ax = b. In this paper, we give a necessary and sufficient condition on the splitting such that the iterative sequence converges to the weighted Moore-Penrose solution of the system Ax = b for every to is an element of C-n and every b is an element of C-m. We also provide a necessary and sufficient condition such that the iterative sequence is convergent for every to x(0) is an element of C-n.展开更多
The order of weighted sum of noise sequence for stochastic system is estimated by using limit theory in probability. Then the divergence rates of state of unstable AR system driven by noise of martingale difference se...The order of weighted sum of noise sequence for stochastic system is estimated by using limit theory in probability. Then the divergence rates of state of unstable AR system driven by noise of martingale difference sequence are established.展开更多
针对半球共形阵体制下进行低空风切变检测时会受到强地杂波信号的干扰,导致风切变信号难以检测的问题,提出了一种基于空时自回归的直接数据域算法(Space-Time Autoregressive Direct Data Domain,D3AR)的低空风切变风速估计方法。该方...针对半球共形阵体制下进行低空风切变检测时会受到强地杂波信号的干扰,导致风切变信号难以检测的问题,提出了一种基于空时自回归的直接数据域算法(Space-Time Autoregressive Direct Data Domain,D3AR)的低空风切变风速估计方法。该方法首先将待检测距离单元的数据从空域、时域以及空时域进行信号对消处理;然后将处理后的数据矩阵描述为空时自回归(Autoregression,AR)模型并估计模型参数;再通过构造与杂波子空间正交的空间来实现对杂波的抑制,最后通过提取待检测单元的最大多普勒频率来估计风场速度。根据仿真结果显示,该方法有效地实现了地杂波抑制,并且能够精确估计风速。展开更多
基金Supported by National Natural Science Foundation of China(No.82074335).
文摘AIM:To conduct a bibliometric analysis of research on artificial intelligence(AI)in the field of glaucoma to gain a comprehensive understanding of the current state of research and identify potential new directions for future studies.METHODS:Relevant articles on the application of AI in the field of glaucoma from the Web of Science Core Collection were retrieved,covering the period from January 1,2013,to December 31,2022.In order to assess the contributions and co-occurrence relationships among different countries/regions,institutions,authors,and journals,CiteSpace and VOSviewer software were employed and the research hotspots and future trends within the field were identified.RESULTS:A total of 750 English articles published between 2013 and 2022 were collected,and the number of publications exhibited an overall increasing trend.The majority of the articles were from China,followed by the United States and India.National University of Singapore,Chinese Academy of Sciences,and Sun Yat-sen University made significant contributions to the published works.Weinreb RN and Fu HZ ranked first among authors and cited authors.American Journal of Ophthalmology is the most impactful academic journal in the field of AI application in glaucoma.The disciplinary scope of this field includes ophthalmology,computer science,mathematics,molecular biology,genetics,and other related disciplines.The clustering and identification of keyword nodes in the co-occurrence network reveal the evolving landscape of AI application in the field of glaucoma.Initially,the hot topics in this field were primarily“segmentation”,“classification”and“diagnosis”.However,in recent years,the focus has shifted to“deep learning”,“convolutional neural network”and“artificial intelligence”.CONCLUSION:With the rapid development of AI technology,scholars have shown increasing interest in its application in the field of glaucoma.Moreover,the application of AI in assisting treatment and predicting prognosis in glaucoma may become a future research hotspot.However,the reliability and interpretability of AI data remain pressing issues that require resolution.
文摘Recently, M. Hanke and M. Neumann([4]) have derived a necessary and sufficient condition on a splitting of A = U-V, which leads to a fixed point system, such that the iterative sequence converges to the least squares solution of minimum a-norm of the system Ax = b. In this paper, we give a necessary and sufficient condition on the splitting such that the iterative sequence converges to the weighted Moore-Penrose solution of the system Ax = b for every to is an element of C-n and every b is an element of C-m. We also provide a necessary and sufficient condition such that the iterative sequence is convergent for every to x(0) is an element of C-n.
基金This research is supported by Beijing Natural Science Foundation (1042007, 1052007).
文摘The order of weighted sum of noise sequence for stochastic system is estimated by using limit theory in probability. Then the divergence rates of state of unstable AR system driven by noise of martingale difference sequence are established.
文摘针对半球共形阵体制下进行低空风切变检测时会受到强地杂波信号的干扰,导致风切变信号难以检测的问题,提出了一种基于空时自回归的直接数据域算法(Space-Time Autoregressive Direct Data Domain,D3AR)的低空风切变风速估计方法。该方法首先将待检测距离单元的数据从空域、时域以及空时域进行信号对消处理;然后将处理后的数据矩阵描述为空时自回归(Autoregression,AR)模型并估计模型参数;再通过构造与杂波子空间正交的空间来实现对杂波的抑制,最后通过提取待检测单元的最大多普勒频率来估计风场速度。根据仿真结果显示,该方法有效地实现了地杂波抑制,并且能够精确估计风速。
