Compared with accurate diagnosis, the system’s selfdiagnosing capability can be greatly increased through the t/kdiagnosis strategy at most k vertexes to be mistakenly identified as faulty under the comparison model,...Compared with accurate diagnosis, the system’s selfdiagnosing capability can be greatly increased through the t/kdiagnosis strategy at most k vertexes to be mistakenly identified as faulty under the comparison model, where k is typically a small number. Based on the Preparata, Metze, and Chien(PMC)model, the n-dimensional hypercube network is proved to be t/kdiagnosable. In this paper, based on the Maeng and Malek(MM)*model, a novel t/k-fault diagnosis(1≤k≤4) algorithm of ndimensional hypercube, called t/k-MM*-DIAG, is proposed to isolate all faulty processors within the set of nodes, among which the number of fault-free nodes identified wrongly as faulty is at most k. The time complexity in our algorithm is only O(2~n n~2).展开更多
基于Hunter and Lange(2000)提出的MM迭代算法,构造了一个代替L1目标函数的新的目标函数Qε(ββk);在此基础上研究了非线性LAD回归影响分析的若干问题.基于新的目标函数和MM迭代算法,证明了LAD回归模型中数据删除模型和均值漂移模型参...基于Hunter and Lange(2000)提出的MM迭代算法,构造了一个代替L1目标函数的新的目标函数Qε(ββk);在此基础上研究了非线性LAD回归影响分析的若干问题.基于新的目标函数和MM迭代算法,证明了LAD回归模型中数据删除模型和均值漂移模型参数估计的等价性定理,并提出了一种新的影响度量.最后,几个数据实例说明了方法的有效性.展开更多
The mixed distribution model is often used to extract information from heteroge-neous data and perform modeling analysis.When the density function of mixed distribution is complicated or the variable dimension is high...The mixed distribution model is often used to extract information from heteroge-neous data and perform modeling analysis.When the density function of mixed distribution is complicated or the variable dimension is high,it usually brings challenges to the parameter es-timation of the mixed distribution model.The application of MM algorithm can avoid complex expectation calculations,and can also solve the problem of high-dimensional optimization by decomposing the objective function.In this paper,MM algorithm is applied to the parameter estimation problem of mixed distribution model.The method of assembly and decomposition is used to construct the substitute function with separable parameters,which avoids the problems of complex expectation calculations and the inversion of high-dimensional matrices.展开更多
Mixture of Experts(MoE)regression models are widely studied in statistics and machine learning for modeling heterogeneity in data for regression,clustering and classification.Laplace distribution is one of the most im...Mixture of Experts(MoE)regression models are widely studied in statistics and machine learning for modeling heterogeneity in data for regression,clustering and classification.Laplace distribution is one of the most important statistical tools to analyze thick and tail data.Laplace Mixture of Linear Experts(LMoLE)regression models are based on the Laplace distribution which is more robust.Similar to modelling variance parameter in a homogeneous population,we propose and study a new novel class of models:heteroscedastic Laplace mixture of experts regression models to analyze the heteroscedastic data coming from a heterogeneous population in this paper.The issues of maximum likelihood estimation are addressed.In particular,Minorization-Maximization(MM)algorithm for estimating the regression parameters is developed.Properties of the estimators of the regression coefficients are evaluated through Monte Carlo simulations.Results from the analysis of two real data sets are presented.展开更多
主要介绍了0.05级高精度光学电压互感器的技术方案、关键技术以及装置的实现。目前,该装置已经通过了国家高压电器质量监督检验中心的精度试验,准确级达到0.05/3P;光学电压互感器作为标准源已在广西钦州排岭220 k V智能变电站挂网应用,...主要介绍了0.05级高精度光学电压互感器的技术方案、关键技术以及装置的实现。目前,该装置已经通过了国家高压电器质量监督检验中心的精度试验,准确级达到0.05/3P;光学电压互感器作为标准源已在广西钦州排岭220 k V智能变电站挂网应用,实现了对榄坪II线A相电子式电压互感器的在线校验,校验数据通过MMS网络向后台发布,结果表明,被校电子式电压互感器与标准光学电压互感器比值误差小于0.2%,相位误差小于10′,满足0.2级准确度要求。展开更多
基金supported by the National Natural Science Foundation of China(61363002)
摘要Compared with accurate diagnosis, the system’s selfdiagnosing capability can be greatly increased through the t/kdiagnosis strategy at most k vertexes to be mistakenly identified as faulty under the comparison model, where k is typically a small number. Based on the Preparata, Metze, and Chien(PMC)model, the n-dimensional hypercube network is proved to be t/kdiagnosable. In this paper, based on the Maeng and Malek(MM)*model, a novel t/k-fault diagnosis(1≤k≤4) algorithm of ndimensional hypercube, called t/k-MM*-DIAG, is proposed to isolate all faulty processors within the set of nodes, among which the number of fault-free nodes identified wrongly as faulty is at most k. The time complexity in our algorithm is only O(2~n n~2).
摘要基于Hunter and Lange(2000)提出的MM迭代算法,构造了一个代替L1目标函数的新的目标函数Qε(ββk);在此基础上研究了非线性LAD回归影响分析的若干问题.基于新的目标函数和MM迭代算法,证明了LAD回归模型中数据删除模型和均值漂移模型参数估计的等价性定理,并提出了一种新的影响度量.最后,几个数据实例说明了方法的有效性.
基金Supported by the National Natural Science Foundation of China(12261108)the General Program of Basic Research Programs of Yunnan Province(202401AT070126)+1 种基金the Yunnan Key Laboratory of Modern Analytical Mathematics and Applications(202302AN360007)the Cross-integration Innovation team of modern Applied Mathematics and Life Sciences in Yunnan Province,China(202405AS350003).
摘要The mixed distribution model is often used to extract information from heteroge-neous data and perform modeling analysis.When the density function of mixed distribution is complicated or the variable dimension is high,it usually brings challenges to the parameter es-timation of the mixed distribution model.The application of MM algorithm can avoid complex expectation calculations,and can also solve the problem of high-dimensional optimization by decomposing the objective function.In this paper,MM algorithm is applied to the parameter estimation problem of mixed distribution model.The method of assembly and decomposition is used to construct the substitute function with separable parameters,which avoids the problems of complex expectation calculations and the inversion of high-dimensional matrices.
基金the National Natural Science Foundation of China(11861041,11261025).
摘要Mixture of Experts(MoE)regression models are widely studied in statistics and machine learning for modeling heterogeneity in data for regression,clustering and classification.Laplace distribution is one of the most important statistical tools to analyze thick and tail data.Laplace Mixture of Linear Experts(LMoLE)regression models are based on the Laplace distribution which is more robust.Similar to modelling variance parameter in a homogeneous population,we propose and study a new novel class of models:heteroscedastic Laplace mixture of experts regression models to analyze the heteroscedastic data coming from a heterogeneous population in this paper.The issues of maximum likelihood estimation are addressed.In particular,Minorization-Maximization(MM)algorithm for estimating the regression parameters is developed.Properties of the estimators of the regression coefficients are evaluated through Monte Carlo simulations.Results from the analysis of two real data sets are presented.
摘要主要介绍了0.05级高精度光学电压互感器的技术方案、关键技术以及装置的实现。目前,该装置已经通过了国家高压电器质量监督检验中心的精度试验,准确级达到0.05/3P;光学电压互感器作为标准源已在广西钦州排岭220 k V智能变电站挂网应用,实现了对榄坪II线A相电子式电压互感器的在线校验,校验数据通过MMS网络向后台发布,结果表明,被校电子式电压互感器与标准光学电压互感器比值误差小于0.2%,相位误差小于10′,满足0.2级准确度要求。