In dealing with the square lattice model,we replace the traditionally needed Born-Von Karmann periodic boundary condition with additional Hamiltonian terms to make up a ring lattice.In doing so,the lattice Green's...In dealing with the square lattice model,we replace the traditionally needed Born-Von Karmann periodic boundary condition with additional Hamiltonian terms to make up a ring lattice.In doing so,the lattice Green's function of an infinite square lattice in the second nearest-neighbour interaction approximation can be derived by means of the matrix Green's function method.It is shown that the density of states may change when the second nearest-neighbour interaction is turned on.展开更多
Using the method of the Jordan-Wigner transformation for solving different spin-spin correlation functions, we have investigated the generation of next-nearest-neighbouring entanglement in a one-dimensional quantum Is...Using the method of the Jordan-Wigner transformation for solving different spin-spin correlation functions, we have investigated the generation of next-nearest-neighbouring entanglement in a one-dimensional quantum Ising spin chain with the Gaussian distribution impurities of exchange couplings and external magnetic fields taken into account. The maximal value of entanglement between the next-nearest-neighbouring qubits in the transverse Ising model was analysed in detail by varying the effectively controlled parameters such as interchange coupling, magnetic field and the system impurity. For such systems, where both exchange couplings and external magnetic field disorder appear, we show that it is possible to achieve next-nearest-neighbouring entanglement better than the previously discussed pure Ising spin chain case. We also show that the Gaussian distribution impurity can induce next-nearest-neighbouring entanglement, which can be used as a means to characterize quantum phase transition.展开更多
The problem addressed in this paper concerns the prototype generation for a cluster-based nearest-neighbour classifier. It considers, to classify a test pattern, the lines that link the patterns of the training set an...The problem addressed in this paper concerns the prototype generation for a cluster-based nearest-neighbour classifier. It considers, to classify a test pattern, the lines that link the patterns of the training set and a set of prototypes. An efficient method based on clustering is here used for finding subgroups of similar patterns with centroid being used as prototype. A learning method is used for iteratively adjusting both position and local-metric of the prototypes. Finally, we show that a simple adaptive distance measure improves the performance of our nearest-neighbour-based classifier. The performance improvement with respect to other nearest-neighbour-based classifiers is validated by testing our method on a lightning classification task using data acquired from the Fast On-orbit Recording of Transient Events （FORTE） satellite, moreover the performance improvement is validated through experiments with several benchmark datasets. The performance of the proposed methods are also validated using the Wilcoxon Signed-Rank test.展开更多
数据缺失在各个研究领域中普遍存在,缺失的数据会对计算的性能与结果产生严重的影响。为提高填补缺失数据的准确度,提出一种基于聚类分析的缺失数据最近邻填补算法。该算法在对数据聚类分析后根据类别分配权重,在MGNN(MahalanobisGray a...数据缺失在各个研究领域中普遍存在,缺失的数据会对计算的性能与结果产生严重的影响。为提高填补缺失数据的准确度,提出一种基于聚类分析的缺失数据最近邻填补算法。该算法在对数据聚类分析后根据类别分配权重,在MGNN(MahalanobisGray and Nearest Neighbor)算法的基础上改进了计算方法和填充值的计算方式。实验结果表明,该方法填补的准确度比传统KNN和MGNN算法要高。展开更多
文摘In dealing with the square lattice model,we replace the traditionally needed Born-Von Karmann periodic boundary condition with additional Hamiltonian terms to make up a ring lattice.In doing so,the lattice Green's function of an infinite square lattice in the second nearest-neighbour interaction approximation can be derived by means of the matrix Green's function method.It is shown that the density of states may change when the second nearest-neighbour interaction is turned on.
基金supported by the Foundation for Scientific and Technological Research Programme,Education Department of Hubei Province,China (Grant No Z200722001)the Postgraduate Programme of Hubei Normal University of China (Grant No 2007D20)
文摘Using the method of the Jordan-Wigner transformation for solving different spin-spin correlation functions, we have investigated the generation of next-nearest-neighbouring entanglement in a one-dimensional quantum Ising spin chain with the Gaussian distribution impurities of exchange couplings and external magnetic fields taken into account. The maximal value of entanglement between the next-nearest-neighbouring qubits in the transverse Ising model was analysed in detail by varying the effectively controlled parameters such as interchange coupling, magnetic field and the system impurity. For such systems, where both exchange couplings and external magnetic field disorder appear, we show that it is possible to achieve next-nearest-neighbouring entanglement better than the previously discussed pure Ising spin chain case. We also show that the Gaussian distribution impurity can induce next-nearest-neighbouring entanglement, which can be used as a means to characterize quantum phase transition.
基金the European Commission IST-2002-507634 Biosecure NoE Projects.
文摘The problem addressed in this paper concerns the prototype generation for a cluster-based nearest-neighbour classifier. It considers, to classify a test pattern, the lines that link the patterns of the training set and a set of prototypes. An efficient method based on clustering is here used for finding subgroups of similar patterns with centroid being used as prototype. A learning method is used for iteratively adjusting both position and local-metric of the prototypes. Finally, we show that a simple adaptive distance measure improves the performance of our nearest-neighbour-based classifier. The performance improvement with respect to other nearest-neighbour-based classifiers is validated by testing our method on a lightning classification task using data acquired from the Fast On-orbit Recording of Transient Events （FORTE） satellite, moreover the performance improvement is validated through experiments with several benchmark datasets. The performance of the proposed methods are also validated using the Wilcoxon Signed-Rank test.
文摘数据缺失在各个研究领域中普遍存在,缺失的数据会对计算的性能与结果产生严重的影响。为提高填补缺失数据的准确度,提出一种基于聚类分析的缺失数据最近邻填补算法。该算法在对数据聚类分析后根据类别分配权重,在MGNN(MahalanobisGray and Nearest Neighbor)算法的基础上改进了计算方法和填充值的计算方式。实验结果表明,该方法填补的准确度比传统KNN和MGNN算法要高。
