A new limited memory symmetric rank one algorithm is proposed. It combines a modified self-scaled symmetric rank one (SSR1) update with the limited memory and nonmonotone line search technique. In this algorithm, th...A new limited memory symmetric rank one algorithm is proposed. It combines a modified self-scaled symmetric rank one (SSR1) update with the limited memory and nonmonotone line search technique. In this algorithm, the descent search direction is generated by inverse limited memory SSR1 update, thus simplifying the computation. Numerical comparison of the algorithm and the famous limited memory BFGS algorithm is given. Comparison results indicate that the new algorithm can process a kind of large-scale unconstrained optimization problems.展开更多
Many real-world networks are found to be scale-free. However, graph partition technology, as a technology capable of parallel computing, performs poorly when scale-free graphs are provided. The reason for this is that...Many real-world networks are found to be scale-free. However, graph partition technology, as a technology capable of parallel computing, performs poorly when scale-free graphs are provided. The reason for this is that traditional partitioning algorithms are designed for random networks and regular networks, rather than for scale-free networks. Multilevel graph-partitioning algorithms are currently considered to be the state of the art and are used extensively. In this paper, we analyse the reasons why traditional multilevel graph-partitioning algorithms perform poorly and present a new multilevel graph-partitioning paradigm, top down partitioning, which derives its name from the comparison with the traditional bottom-up partitioning. A new multilevel partitioning algorithm, named betweenness-based partitioning algorithm, is also presented as an implementation of top-down partitioning paradigm. An experimental evaluation of seven different real-world scale-free networks shows that the betweenness-based partitioning algorithm significantly outperforms the existing state-of-the-art approaches.展开更多
To compensate motion errors of images from the parallel-track bistatic synthetic aperture radar(BiSAR),an improved chirp scaling algorithm(CSA) is proposed.Since velocity vector of the moving aircrafts in the para...To compensate motion errors of images from the parallel-track bistatic synthetic aperture radar(BiSAR),an improved chirp scaling algorithm(CSA) is proposed.Since velocity vector of the moving aircrafts in the parallel-track BiSAR system can not remain invariant in an aperture,an actual aperture is divided into subapertures so that it is reasonable to assume that the aircrafts move with constant acceleration vector in a subaperture.Based on this model,an improved CSA is derived.The new phase factors incorporate three-dimensional acceleration and velocity.The motion compensation procedure is integrated into the CSA without additional operation required.The simulation results show that the presented algorithm can efficiently resolve motion compensation for parallel-track BiSAR.展开更多
该文研究了基于Chirp Scaling原理实现双基聚束SAR成像的极坐标格式算法(Polar Format Algorithm,PFA)。PFA通过两个一维插值来实现数据的极坐标格式转换,插值计算量较大。该文基于发射信号的线性调频特性,在距离向对极坐标格式数据进...该文研究了基于Chirp Scaling原理实现双基聚束SAR成像的极坐标格式算法(Polar Format Algorithm,PFA)。PFA通过两个一维插值来实现数据的极坐标格式转换,插值计算量较大。该文基于发射信号的线性调频特性,在距离向对极坐标格式数据进行变标处理,仅包含信号复乘和FFT,从而避免了插值运算。文中对于接收Chirp信号和Dechirp信号分别进行了讨论,依照不同流程实现了极坐标格式算法。同插值方法相比,二者聚焦结果相当,但是CS(Chirp Scaling)的方法速度有显著提高。点目标仿真实验验证了此方法的有效性。展开更多
基金the National Natural Science Foundation of China(10471062)the Natural Science Foundation of Jiangsu Province(BK2006184)~~
文摘A new limited memory symmetric rank one algorithm is proposed. It combines a modified self-scaled symmetric rank one (SSR1) update with the limited memory and nonmonotone line search technique. In this algorithm, the descent search direction is generated by inverse limited memory SSR1 update, thus simplifying the computation. Numerical comparison of the algorithm and the famous limited memory BFGS algorithm is given. Comparison results indicate that the new algorithm can process a kind of large-scale unconstrained optimization problems.
基金supported by the National Science Foundation for Distinguished Young Scholars of China(Grant Nos.61003082 and 60903059)the National Natural Science Foundation of China(Grant No.60873014)the Foundation for Innovative Research Groups of the National Natural Science Foundation of China(Grant No.60921062)
文摘Many real-world networks are found to be scale-free. However, graph partition technology, as a technology capable of parallel computing, performs poorly when scale-free graphs are provided. The reason for this is that traditional partitioning algorithms are designed for random networks and regular networks, rather than for scale-free networks. Multilevel graph-partitioning algorithms are currently considered to be the state of the art and are used extensively. In this paper, we analyse the reasons why traditional multilevel graph-partitioning algorithms perform poorly and present a new multilevel graph-partitioning paradigm, top down partitioning, which derives its name from the comparison with the traditional bottom-up partitioning. A new multilevel partitioning algorithm, named betweenness-based partitioning algorithm, is also presented as an implementation of top-down partitioning paradigm. An experimental evaluation of seven different real-world scale-free networks shows that the betweenness-based partitioning algorithm significantly outperforms the existing state-of-the-art approaches.
文摘To compensate motion errors of images from the parallel-track bistatic synthetic aperture radar(BiSAR),an improved chirp scaling algorithm(CSA) is proposed.Since velocity vector of the moving aircrafts in the parallel-track BiSAR system can not remain invariant in an aperture,an actual aperture is divided into subapertures so that it is reasonable to assume that the aircrafts move with constant acceleration vector in a subaperture.Based on this model,an improved CSA is derived.The new phase factors incorporate three-dimensional acceleration and velocity.The motion compensation procedure is integrated into the CSA without additional operation required.The simulation results show that the presented algorithm can efficiently resolve motion compensation for parallel-track BiSAR.
文摘该文研究了基于Chirp Scaling原理实现双基聚束SAR成像的极坐标格式算法(Polar Format Algorithm,PFA)。PFA通过两个一维插值来实现数据的极坐标格式转换,插值计算量较大。该文基于发射信号的线性调频特性,在距离向对极坐标格式数据进行变标处理,仅包含信号复乘和FFT,从而避免了插值运算。文中对于接收Chirp信号和Dechirp信号分别进行了讨论,依照不同流程实现了极坐标格式算法。同插值方法相比,二者聚焦结果相当,但是CS(Chirp Scaling)的方法速度有显著提高。点目标仿真实验验证了此方法的有效性。