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
波达方向(Direction of Arrival,DOA)估计是阵列观测数据研究领域的一个基本问题.对于观测数据服从复椭球对称分布的应用场景,现有的方法多采用l1-范数惩罚项来实现信号波达方向的稀疏估计,其中的l1-范数惩罚项仅考虑信号的稀疏性而没...波达方向(Direction of Arrival,DOA)估计是阵列观测数据研究领域的一个基本问题.对于观测数据服从复椭球对称分布的应用场景,现有的方法多采用l1-范数惩罚项来实现信号波达方向的稀疏估计,其中的l1-范数惩罚项仅考虑信号的稀疏性而没有考虑信号的多样性,从而造成这些估计方法一般将弱信号(具有较低功率的信号)略去,可能无法准确地估计弱信号的波达方向.为解决这个问题,本文通过引入一个组合范数惩罚项构建了一个新的估计(模型)方法,其中的组合范数惩罚项是l1-范数惩罚项与l2-范数平方惩罚项的线性组合,其组合系数(惩罚参数)互不相关,l2-范数平方惩罚项则可以保留弱信号的多样性.然后,本文基于Majorization-Minimization(MM)算法设计了模型的求解算法,并证明该方法是收敛的.数值实验表明,相较于那些基于l1-惩罚项的估计方法,本方法具有更高的精度.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
To overcome the mutual coupling (MC) of multiple antennas in millimeter wave (mmWave) communication systems, a novel beam design method with low complexity is proposed in this paper. Firstly, an equivalent channel mod...To overcome the mutual coupling (MC) of multiple antennas in millimeter wave (mmWave) communication systems, a novel beam design method with low complexity is proposed in this paper. Firstly, an equivalent channel model incorporating the effect of MC is analyzed and established, and then an optimal precoding / combiner vector for beamforming is derived. On this basis, by using greedy geometric (GG) algorithm, a novel hybrid beam design method is proposed. Finally, the performance of proposed method is analyzed and compared with other traditional ones. The simulation results show that the proposed method has better suppression of the MC effect as well as lower complexity.展开更多
基金supported by the National Natural Science Foundation of China(61363002)
文摘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).
文摘基于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.
文摘波达方向(Direction of Arrival,DOA)估计是阵列观测数据研究领域的一个基本问题.对于观测数据服从复椭球对称分布的应用场景,现有的方法多采用l1-范数惩罚项来实现信号波达方向的稀疏估计,其中的l1-范数惩罚项仅考虑信号的稀疏性而没有考虑信号的多样性,从而造成这些估计方法一般将弱信号(具有较低功率的信号)略去,可能无法准确地估计弱信号的波达方向.为解决这个问题,本文通过引入一个组合范数惩罚项构建了一个新的估计(模型)方法,其中的组合范数惩罚项是l1-范数惩罚项与l2-范数平方惩罚项的线性组合,其组合系数(惩罚参数)互不相关,l2-范数平方惩罚项则可以保留弱信号的多样性.然后,本文基于Majorization-Minimization(MM)算法设计了模型的求解算法,并证明该方法是收敛的.数值实验表明,相较于那些基于l1-惩罚项的估计方法,本方法具有更高的精度.
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).
文摘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supported by Aeronautical Science Foundation of China (2017ZC52021)the Major Program of National Natural Science Foundation of China (61827801)
文摘To overcome the mutual coupling (MC) of multiple antennas in millimeter wave (mmWave) communication systems, a novel beam design method with low complexity is proposed in this paper. Firstly, an equivalent channel model incorporating the effect of MC is analyzed and established, and then an optimal precoding / combiner vector for beamforming is derived. On this basis, by using greedy geometric (GG) algorithm, a novel hybrid beam design method is proposed. Finally, the performance of proposed method is analyzed and compared with other traditional ones. The simulation results show that the proposed method has better suppression of the MC effect as well as lower complexity.
