一个基于两个数学难题的签名方案的分析

分析了文献[4]中提出的基于大数分解和离散对数难题的签名方案,指出文献[4]中提出的方案在离散对数可解时即是不安全的。     

非抽样双树复小波域的BPP-NMF图像融合

提出了一种非抽样双树复小波变换（UDT-CWT）与基于块主元旋转的非负矩阵分解（BPP-NMF）相结合的多聚焦图像融合算法。利用UDT-CWT具有完美的平移不变性及良好的方向选择性,首先对图像进行多尺度、多方向分解并得到低频子带和高频子带系数;然后对低频子带系数采用块主元旋转的非负矩阵分解的融合策略,高频系数则选用高斯加权区域能量与区域标准差一致性选择的融合准则。最后对融合后的系数进行UDT-CWT逆变换得到重构图像。选用多组多聚焦图像进行融合并对融合结果进行主观视觉、客观方面的评价。试验结果表明,该融合算法不仅具有良好的视觉效果,同时在客观评价指标也优于一般的融合策略,验证了该算法的有效性。     

Modified SMC method of blind multiuser detection for DS-CDMA systems over fading channels

This paper presents the application of sequential Monte Carlo (SMC) methodology for blind detection in wireless direct sequence code division multiple access (DS-CDMA) systems over fading channels. It is known that the conventional SMC method requires a high-computational complexity that grows exponentially with the number of active users. This paper proposes a solution to this problem by employing Cholesky factorization to decompose the observed data into separate components for each user and then the parameters of each user are estimated with the SMC inference method under the decision feedback framework. Based on these concepts, an efficient blind decision feedback SMC (DF-SMC) receiver is developed for differentially encoded DS-CDMA systems. Simulation results demonstrate the promising performance of the proposed receiver for both flat fading and frequency-selective fading channels.     

平面单应矩阵对摄像机内参数约束的一些性质

空间x-y坐标平面与图像平面之间的单应矩阵可以提供关于摄像机内参数的2个线性约束.文中研究表明:给定一个一般空间平面与图像平面之间的单应矩阵,如果空间平面在世界坐标系的坐标已知,则该单应矩阵同样可以提供关于摄像机内参数的2个线性约束;如果空间平面在世界坐标系的坐标未知,则该单应矩阵不能构成对摄像机内参数的任何约束.另外,仅仅知道某一个场景中的2幅图像间的单应矩阵不能对摄像机内参数构成任何约束.该结果对从事摄像机标定和三维重建的研究人员有一定的参考作用.     

基于小波变换和NMF的人脸识别方法的研究

为了克服PCA、ICA等传统方法在人脸图像特征抽取时存在速度慢、识别率低的缺点,该文提出了一种将非负矩分解思想应用于人脸特征提取的算法。利用小波变换对人脸图像进行分解,对其中包含主要信息的低频子带运用NMF构造特征子空间,在子空间内实现识别。实验结果表明,该方法实用、有效,减少了计算量,提高了系统的识别率,使识别率达到90％以上,有着广泛的研究价值和应用 前景。     

Computing the positive solutions of the discrete third-order three-point right focal boundary-value problems

The existence of positive solutions to the discrete third-order three-point boundary-value problems (BVPs) was recently established in Ji and Yang [Positive solutions of discrete third-order three-point right focal boundary value problems, J. Differ. Equat. Appl. 15 (2009), pp. 185–195]. In this paper, we propose an algorithm for the computation of such positive solutions. The method is based on the power method for the dominant eigenvalue and the Crout-like factorization algorithm for the sparse system of linear equations. At each iteration of the method, it calls for a linear solver with linear computational complexity. The proposed method is extremely effective for large-scale problems. A numerical example is also included to demonstrate the effectiveness of the algorithm when applied to the third-order three-point BVPs of differential equation.     

求解平面转子本征问题的因式分解方法

讨论了平面转子的可因式分解性,用因式分解的方法求解了平面转子的本征问题,并计算了均匀强电场下平面转子的能级和波函数。     

CLUSTERING VERY LARGE DATA SETS USING A LOW MEMORY MATRIX FACTORED REPRESENTATION

A scalable method to cluster data sets too large to fit in memory is presented. This method does not depend on random subsampling, but does scan every individual data sample in a deterministic way. The original data are represented in factored form by the product of two matrices, one or both of which is very sparse. This factored form avoids the need to multiply together these two matrices by using a variant of the Principal Direction Divisive Partitioning (PDDP) algorithm which does not depend on computing the distances between the individual samples. The resulting clustering algorithm is Piecemeal PDDP (PMPDDP), in which the original data are broken up into sections which will fit into memory and clustered. The cluster centers are used to create approximations to the original data items, and each original data item is represented by a linear combination of these centers. We evaluate the performance of PMPDDP on three real data sets, and observe that the quality of the clusters of PMPDDP is comparable to PDDP for the data sets examined.     

Implicit methods for fluid dynamics

This paper represents the contributions to the development of implicit procedures for solving the equations of fluid dynamics made by Briley and McDonald (1975)[1], Beam and Warming (1976, 1978) [2] and [3] and Lombard et al. (1983) [4]. The contributions of Briley and McDonald and Beam and Warming are well known, but Lombard has not been fully recognized for his innovative contributions to flux vector splitting and use of the DDADI (Diagonally Dominate Alternating Direction Implicit) algorithm. Their contributions are presented herein.Fully implicit algorithms are applied to two complex flow problems of current interest, (1) hypersonic non-equilibrium flow about a blunt nosed body and (2) flow within an MFD (magneto-fluid dynamics) accelerator. These two applications would be exceeding costly without the use of fully implicit methods.