为了解决部分均匀环境中训练数据不足时的子空间信号检测难题,采用贝叶斯理论,将噪声协方差矩阵建模为逆威沙特分布,并采用广义似然比准则(generalized likelihood ratio test,GLRT)、Rao准则和Wald准则设计自适应检测器,结果表明3种准...为了解决部分均匀环境中训练数据不足时的子空间信号检测难题,采用贝叶斯理论,将噪声协方差矩阵建模为逆威沙特分布,并采用广义似然比准则(generalized likelihood ratio test,GLRT)、Rao准则和Wald准则设计自适应检测器,结果表明3种准则得到相同的结果。基于仿真及实测数据验证了所提检测器的有效性,并得出了影响检测性能的关键物理量。展开更多
This paper proposes an improved You Only Look Once(YOLOv3)algorithm for automatically detecting damaged apples to promote the automation of the fruit processing industry.In the proposed method,a clustering method base...This paper proposes an improved You Only Look Once(YOLOv3)algorithm for automatically detecting damaged apples to promote the automation of the fruit processing industry.In the proposed method,a clustering method based on Rao-1 algorithm is introduced to optimize anchor box sizes.The clustering method uses the intersection over the union to form the objective function and the most representative anchor boxes are generated for normal and damaged apple detection.To verify the feasibility and effectiveness of the proposed method,real apple images collected from the Internet are employed.Compared with the generic YOLOv3 and Fast Region-based Convolutional Neural Network(Fast R-CNN)algorithms,the proposed method yields the highest mean average precision value for the test dataset.Therefore,it is practical to apply the proposed method for intelligent apple detection and classification tasks.展开更多
In the envisioned smart grid, high penetration of uncertain renewables, unpredictable participation of(industrial) customers, and purposeful manipulation of smart meter readings, all highlight the need for accurate,fa...In the envisioned smart grid, high penetration of uncertain renewables, unpredictable participation of(industrial) customers, and purposeful manipulation of smart meter readings, all highlight the need for accurate,fast, and robust power system state estimation(PSSE). Nonetheless, most real-time data available in the current and upcoming transmission/distribution systems are nonlinear in power system states(i.e., nodal voltage phasors).Scalable approaches to dealing with PSSE tasks undergo a paradigm shift toward addressing the unique modeling and computational challenges associated with those nonlinear measurements. In this study, we provide a contemporary overview of PSSE and describe the current state of the art in the nonlinear weighted least-squares and least-absolutevalue PSSE. To benchmark the performance of unbiased estimators, the Cramér-Rao lower bound is developed.Accounting for cyber attacks, new corruption models are introduced, and robust PSSE approaches are outlined as well. Finally, distribution system state estimation is discussed along with its current challenges. Simulation tests corroborate the effectiveness of the developed algorithms as well as the practical merits of the theory.展开更多
文摘为了解决部分均匀环境中训练数据不足时的子空间信号检测难题,采用贝叶斯理论,将噪声协方差矩阵建模为逆威沙特分布,并采用广义似然比准则(generalized likelihood ratio test,GLRT)、Rao准则和Wald准则设计自适应检测器,结果表明3种准则得到相同的结果。基于仿真及实测数据验证了所提检测器的有效性,并得出了影响检测性能的关键物理量。
基金National Nature Science and Foundation of China under Grants 62202044 and 62002016the Guangdong Basic and Applied Basic Research Foundation under Grant 2020A1515110431+4 种基金Scientific and Technological Innovation Foundation of Foshan under Grant BK22BF009the NSFC Youth Scientist Fund under Grant 52007160the Beijing Natural Science Foundation under Grant L211020the Interdisciplinary Research Project for Young Teachers of USTB(Fundamental Research Funds for the Central Universities)under Grant FRF-IDRY-21-003the Fundamental Research Funds for the Central Universities and the Youth Teacher International Exchange&Growth Program(No.QNXM20220040).
文摘This paper proposes an improved You Only Look Once(YOLOv3)algorithm for automatically detecting damaged apples to promote the automation of the fruit processing industry.In the proposed method,a clustering method based on Rao-1 algorithm is introduced to optimize anchor box sizes.The clustering method uses the intersection over the union to form the objective function and the most representative anchor boxes are generated for normal and damaged apple detection.To verify the feasibility and effectiveness of the proposed method,real apple images collected from the Internet are employed.Compared with the generic YOLOv3 and Fast Region-based Convolutional Neural Network(Fast R-CNN)algorithms,the proposed method yields the highest mean average precision value for the test dataset.Therefore,it is practical to apply the proposed method for intelligent apple detection and classification tasks.
基金Wang G and Giannakis GB were supported by the National Natural Science Foundation of China(NSFC)(Nos.1514056,1505970,and 1711471)Chen J and Sun J were supported by the NSFC(Nos.61621063 and 61522303)+2 种基金the NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization(No.61720106011)the Projects of Major International(Regional)Joint Research Program NSFC(No.61720106011)the Program for Changjiang Scholars and Innovative Research Team in University(No.IRT1208)
文摘In the envisioned smart grid, high penetration of uncertain renewables, unpredictable participation of(industrial) customers, and purposeful manipulation of smart meter readings, all highlight the need for accurate,fast, and robust power system state estimation(PSSE). Nonetheless, most real-time data available in the current and upcoming transmission/distribution systems are nonlinear in power system states(i.e., nodal voltage phasors).Scalable approaches to dealing with PSSE tasks undergo a paradigm shift toward addressing the unique modeling and computational challenges associated with those nonlinear measurements. In this study, we provide a contemporary overview of PSSE and describe the current state of the art in the nonlinear weighted least-squares and least-absolutevalue PSSE. To benchmark the performance of unbiased estimators, the Cramér-Rao lower bound is developed.Accounting for cyber attacks, new corruption models are introduced, and robust PSSE approaches are outlined as well. Finally, distribution system state estimation is discussed along with its current challenges. Simulation tests corroborate the effectiveness of the developed algorithms as well as the practical merits of the theory.
