It is said that a graph G is independent-set-deletable factor-critical （in short, ID-factor-critical）, if, for everyindependent-set I which has the same parity as ｜V（G）｜, G - I has a perfect matching. A graph G ...It is said that a graph G is independent-set-deletable factor-critical （in short, ID-factor-critical）, if, for everyindependent-set I which has the same parity as ｜V（G）｜, G - I has a perfect matching. A graph G is strongly IM-extendable, if for every spanning supergraph H of G, every induced matching of H is included in a perfect matching of H. The κ-th power of G, denoted by G^κ, is the graph with vertex set V（G） in which two vertices are adjacent if and only if they have distance at most k in G. ID-factor-criticality and IM-extendability of power graphs are discussed in this article. The author shows that, if G is a connected graph, then G^3 and T（G） （the total graph of G） are ID-factor-critical, and G^4 （when ｜V（G）｜ is even） is strongly IM-extendable; if G is 2-connected, then D^2 is ID-factor-critical.展开更多
Particle swarm optimization （PSO） is a new heuristic algorithm which has been applied to many optimization problems successfully. Attribute reduction is a key studying point of the rough set theory, and it has been ...Particle swarm optimization （PSO） is a new heuristic algorithm which has been applied to many optimization problems successfully. Attribute reduction is a key studying point of the rough set theory, and it has been proven that computing minimal reduc- tion of decision tables is a non-derterministic polynomial （NP）-hard problem. A new cooperative extended attribute reduction algorithm named Co-PSAR based on improved PSO is proposed, in which the cooperative evolutionary strategy with suitable fitness func- tions is involved to learn a good hypothesis for accelerating the optimization of searching minimal attribute reduction. Experiments on Benchmark functions and University of California, Irvine （UCI） data sets, compared with other algorithms, verify the superiority of the Co-PSAR algorithm in terms of the convergence speed, efficiency and accuracy for the attribute reduction.展开更多
The data association problem of multiple extended target tracking is very challenging because each target may generate multiple measurements.Recently,the belief propagation based multiple target tracking algorithms wi...The data association problem of multiple extended target tracking is very challenging because each target may generate multiple measurements.Recently,the belief propagation based multiple target tracking algorithms with high efficiency have been a research focus.Different from the belief propagation based Extended Target tracking based on Belief Propagation(ET-BP)algorithm proposed in our previous work,a new graphical model formulation of data association for multiple extended target tracking is proposed in this paper.The proposed formulation can be solved by the Loopy Belief Propagation(LBP)algorithm.Furthermore,the simplified measurement set in the ET-BP algorithm is modified to improve tracking accuracy.Finally,experiment results show that the proposed algorithm has better performance than the ET-BP and joint probabilistic data association based on the simplified measurement set algorithms in terms of accuracy and efficiency.Additionally,the convergence of the proposed algorithm is verified in the simulations.展开更多
在现代处理器体系架构中,缓存是解决存储墙瓶颈的重要手段,但是缓存访问需求是随程序甚至是程序片段的切换而变化的,这导致传统的固定参数配置的缓存架构难以在长时间或在程序间依然保持高效性能。文中提出一种缓存组相联度的自适应扩...在现代处理器体系架构中,缓存是解决存储墙瓶颈的重要手段,但是缓存访问需求是随程序甚至是程序片段的切换而变化的,这导致传统的固定参数配置的缓存架构难以在长时间或在程序间依然保持高效性能。文中提出一种缓存组相联度的自适应扩展方法,能根据程序运行时缓存组活跃状态,利用短时非活跃缓存组的存储空间,来扩展当前活跃缓存组的组相联数目,并可实时动态调整组与组之间的扩展互联关系,有效提升缓存空间的整体利用效率。文中在Gem5软件中对所提出的缓存组相联自适应扩展架构进行了仿真,并基于SPEC CPU 2017基准测试集进行了性能测试,结果显示所提方法明显改善了缓存组访问的均匀性,对典型程序缓存组使用频次的均匀性最大提升23.14%左右,降低缓存访问缺失数最大可达54.2%。硬件实现和仿真结果显示,与HY-Way等低功耗可重构缓存架构相比,文中所述缓存架构资源消耗减少了7.66%以上,在嵌入式处理器设计中有较大的应用价值。展开更多
Manufacturing network flow （MNF） is a generalized network model that overcomes the limitation of an ordinary network flow in modeling more complicated manufacturing scenarios, in particular the synthesis of differen...Manufacturing network flow （MNF） is a generalized network model that overcomes the limitation of an ordinary network flow in modeling more complicated manufacturing scenarios, in particular the synthesis of different materials into one product and/or the distilling of one type of material into many different products. Though a network simplex method for solving a simplified version of MNF has been outlined in the literature, more research work is still needed to give a complete answer whether some classical duality and optimality results of the classical network flow problem can be extended in MNF. In this paper, we propose an algorithmic method for obtaining an initial basic feasible solution to start the existing network simplex algorithm, and present a network-based approach to checking the dual feasibility conditions. These results are an extension of those of the ordinary network flow problem.展开更多
In order to improve the control performance of three-phase permanent magnet synchronous motor(PMSM)system,an active disturbance rejection finite control set-mode predictive control(FCS-MPC)strategy based on improved e...In order to improve the control performance of three-phase permanent magnet synchronous motor(PMSM)system,an active disturbance rejection finite control set-mode predictive control(FCS-MPC)strategy based on improved extended state observer(ESO)is proposed in this paper.ESO is designed based on the arc-hyperbolic sine function to obtain estimations of rotating speed and back electromotive force(EMF)term of motor speed.Active disturbance rejection control(ADRC)is applied as speed controller.The proposed FCS-MPC strategy aims to reduce the electromagnetic torque ripple and the complexity and calculation of the algorithm.Compared with the FCS-MPC strategy based on PI controller,the constructed control strategy can guarantee the reliable and stable operation of PMSM system,and has good speed tracking,anti-interference ability and robustness.展开更多
基金Project supported by NSFC(10371112)NSFHN (0411011200)SRF for ROCS,SEM
文摘It is said that a graph G is independent-set-deletable factor-critical （in short, ID-factor-critical）, if, for everyindependent-set I which has the same parity as ｜V（G）｜, G - I has a perfect matching. A graph G is strongly IM-extendable, if for every spanning supergraph H of G, every induced matching of H is included in a perfect matching of H. The κ-th power of G, denoted by G^κ, is the graph with vertex set V（G） in which two vertices are adjacent if and only if they have distance at most k in G. ID-factor-criticality and IM-extendability of power graphs are discussed in this article. The author shows that, if G is a connected graph, then G^3 and T（G） （the total graph of G） are ID-factor-critical, and G^4 （when ｜V（G）｜ is even） is strongly IM-extendable; if G is 2-connected, then D^2 is ID-factor-critical.
基金supported by the National Natural Science Foundation of China (60873069 61171132)+3 种基金the Jiangsu Government Scholarship for Overseas Studies (JS-2010-K005)the Funding of Jiangsu Innovation Program for Graduate Education (CXZZ11 0219)the Open Project Program of Jiangsu Provincial Key Laboratory of Computer Information Processing Technology (KJS1023)the Applying Study Foundation of Nantong (BK2011062)
文摘Particle swarm optimization （PSO） is a new heuristic algorithm which has been applied to many optimization problems successfully. Attribute reduction is a key studying point of the rough set theory, and it has been proven that computing minimal reduc- tion of decision tables is a non-derterministic polynomial （NP）-hard problem. A new cooperative extended attribute reduction algorithm named Co-PSAR based on improved PSO is proposed, in which the cooperative evolutionary strategy with suitable fitness func- tions is involved to learn a good hypothesis for accelerating the optimization of searching minimal attribute reduction. Experiments on Benchmark functions and University of California, Irvine （UCI） data sets, compared with other algorithms, verify the superiority of the Co-PSAR algorithm in terms of the convergence speed, efficiency and accuracy for the attribute reduction.
基金supported by the National Natural Science Foundation of China(No.61871301)National Natural Science Foundation of Shaanxi Province,China(No.2018JQ6059)Postdoctoral Science Foundation of China(No.2018M633470)。
文摘The data association problem of multiple extended target tracking is very challenging because each target may generate multiple measurements.Recently,the belief propagation based multiple target tracking algorithms with high efficiency have been a research focus.Different from the belief propagation based Extended Target tracking based on Belief Propagation(ET-BP)algorithm proposed in our previous work,a new graphical model formulation of data association for multiple extended target tracking is proposed in this paper.The proposed formulation can be solved by the Loopy Belief Propagation(LBP)algorithm.Furthermore,the simplified measurement set in the ET-BP algorithm is modified to improve tracking accuracy.Finally,experiment results show that the proposed algorithm has better performance than the ET-BP and joint probabilistic data association based on the simplified measurement set algorithms in terms of accuracy and efficiency.Additionally,the convergence of the proposed algorithm is verified in the simulations.
文摘在现代处理器体系架构中,缓存是解决存储墙瓶颈的重要手段,但是缓存访问需求是随程序甚至是程序片段的切换而变化的,这导致传统的固定参数配置的缓存架构难以在长时间或在程序间依然保持高效性能。文中提出一种缓存组相联度的自适应扩展方法,能根据程序运行时缓存组活跃状态,利用短时非活跃缓存组的存储空间,来扩展当前活跃缓存组的组相联数目,并可实时动态调整组与组之间的扩展互联关系,有效提升缓存空间的整体利用效率。文中在Gem5软件中对所提出的缓存组相联自适应扩展架构进行了仿真,并基于SPEC CPU 2017基准测试集进行了性能测试,结果显示所提方法明显改善了缓存组访问的均匀性,对典型程序缓存组使用频次的均匀性最大提升23.14%左右,降低缓存访问缺失数最大可达54.2%。硬件实现和仿真结果显示,与HY-Way等低功耗可重构缓存架构相比,文中所述缓存架构资源消耗减少了7.66%以上,在嵌入式处理器设计中有较大的应用价值。
基金Supported by the National Natural Science Foundation of China(No.10371028,No.10671177)the Key Project of Chinese Ministry of Education(No.1080607)+1 种基金the Scientific Research Grant of Jiangnan University(No.314000-52210382)the Youth Foundation from School of Science of Jiangnan University(January 2008-December 2009)
文摘Manufacturing network flow （MNF） is a generalized network model that overcomes the limitation of an ordinary network flow in modeling more complicated manufacturing scenarios, in particular the synthesis of different materials into one product and/or the distilling of one type of material into many different products. Though a network simplex method for solving a simplified version of MNF has been outlined in the literature, more research work is still needed to give a complete answer whether some classical duality and optimality results of the classical network flow problem can be extended in MNF. In this paper, we propose an algorithmic method for obtaining an initial basic feasible solution to start the existing network simplex algorithm, and present a network-based approach to checking the dual feasibility conditions. These results are an extension of those of the ordinary network flow problem.
基金National Natural Science Foundation of China(No.61461023)Gansu Provincial Department of Education Project(No.2016B-036)
文摘In order to improve the control performance of three-phase permanent magnet synchronous motor(PMSM)system,an active disturbance rejection finite control set-mode predictive control(FCS-MPC)strategy based on improved extended state observer(ESO)is proposed in this paper.ESO is designed based on the arc-hyperbolic sine function to obtain estimations of rotating speed and back electromotive force(EMF)term of motor speed.Active disturbance rejection control(ADRC)is applied as speed controller.The proposed FCS-MPC strategy aims to reduce the electromagnetic torque ripple and the complexity and calculation of the algorithm.Compared with the FCS-MPC strategy based on PI controller,the constructed control strategy can guarantee the reliable and stable operation of PMSM system,and has good speed tracking,anti-interference ability and robustness.
