基于张量投票的图像超分辨率算法

张量投票算法在提取图像主观轮廓上具有良好的效果,本文提出了一种基于张量投票的图像超分辨率算法。首先用二维张量矩阵存储低分辨率图像各像素点所处的位置特征信息,并利用稀疏张量投票将特征信息进行加强,再使用稠密张量投票产生高分辨率图像对应的二维张量矩阵,此张量矩阵包含了视觉特性强的边缘信息,最后利用该边缘信息指导高分辨率图像的重构。实验结果表明,该方法得到的高分辨率图像信噪比高、视觉效果好。     

投票理论研究现状及其展望

社会选择理论是研究如何表达和聚合个体选择的一门学问.而社会选择理论与计算机科学的融合产生了称为计算社会选择的交叉学科,该学科成为社会计算的重要研究内容之一,在人工智能、经济和计算性理论领域引起了轰动.其一方面引入了复杂性分析和算法设计等计算机学科中常用的技术来对社会选择机制进行研究;另一方面也通过引入社会选择理论中的概念来推动计算机技术的发展,特别是在多智能体系统研究中有着成功的应用.投票理论是计算社会选择中最重要的研究主题之一.首先介绍常见的投票方法以及投票理论的形式化框架;再对投票理论中所关心的操纵问题做分析;然后介绍在组合域上的投票;最后对其他相关问题作简要介绍,并对该领域未来的发展与应用做出展望.     

The voting analytic hierarchy process method for discriminating among efficient decision making units in data envelopment analysis

Making optimal use of available resources has always been of interest to humankind, and different approaches have been used in an attempt to make maximum use of existing resources. Limitations of capital, manpower, energy, etc., have led managers to seek ways for optimally using such resources. In fact, being informed of the performance of the units under the supervision of a manager is the most important task with regard to making sensible decisions for managing them. Data envelopment analysis (DEA) suggests an appropriate method for evaluating the efficiency of homogeneous units with multiple inputs and multiple outputs. DEA models classify decision making units (DMUs) into efficient and inefficient ones. However, in most cases, managers and researchers are interested in ranking the units and selecting the best DMU. Various scientific models have been proposed by researchers for ranking DMUs. Each of these models has some weakness(es), which makes it difficult to select the appropriate ranking model. This paper presents a method for ranking efficient DMUs by the voting analytic hierarchy process (VAHP). The paper reviews some ranking models in DEA and discusses their strengths and weaknesses. Then, we provide the method for ranking efficient DMUs by VAHP. Finally we give an example to illustrate our approach and then the new method is employed to rank efficient units in a real world problem.     

基于参考点和投票规则的多目标粒子群优化群体决策

针对巨量可选方案的群体决策问题,提出了一个新的基于参考点和投票规则的多目标粒子群优化算法。该算法把个体与参考点的支配关系或者距离作为一个重要因素,在选择引导者的锦标赛方法,局部最优更新规则,以及外部种群档案剪枝规则中都嵌入了基于支配关系或距离因素的投票规则,以找到群体决策解,并且提高搜索效率。仿真结果表明该算法有效。     

贝叶斯网络参数的在线学习算法及应用

以EM算法为基础，在给定贝叶斯网络结构情况下。研究分析了Voting EM算法并利用该算法对防洪决策贝叶斯网络进行在线参数学习，将该算法与EM算法的学习结果进行了比较分析，结果表明Voting EM算法不但能够进行在线参数学习，而且也具有较高的学习精度．     

基于椭圆曲线密码体制的投票协议

本文设计了一种基于椭圆曲线密码体制的投票协议,该协议的特点是能够使投票者在计算机网络上进行无记名投票,并可以有效地抵制各种欺骗行为,从而使安全选举成为可能。     

Algorithms for the coalitional manipulation problem

We investigate the problem of coalitional manipulation in elections, which is known to be hard in a variety of voting rules. We put forward efficient algorithms for the problem in Borda, Maximin and Plurality with Runoff, and analyze their windows of error. Specifically, given an instance on which an algorithm fails, we bound the additional power the manipulators need in order to succeed. We finally discuss the implications of our results with respect to the popular approach of employing computational hardness to preclude manipulation.     

Randomised hough transform with error propagation for line and circle detection

In this paper, we introduce a new Randomised Hough Transform aimed at improving curve detection accuracy and robustness, as well as computational efficiency. Robustness and accuracy improvement is achieved by analytically propagating the errors with image pixels to the estimated curve parameters. The errors with the curve parameters are then used to determine the contribution of pixels to the accumulator array. The computational efficiency is achieved by mapping a set of points near certain selected seed points to the parameter space at a time. Statistically determined, the seed points are points that are most likely located on the curves and that produce the most accurate curve estimation. Further computational advantage is achieved by performing progressive detection. Examples of detection of lines using the proposed technique are given in the paper. The concept can be extended to non-linear curves such as circles and ellipses. ID="A1"Correspondance and offprint requests to: Q. Ji, Department of Electrical, Computer and Systems Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, USA. E-mail: qji@ecse.rpi.edu     

Analysis and optimization of weighted voting systems consisting of voting units with limited availability

The voting system studied consists of n voting units each either providing a binary decision (0 or 1) or abstaining from voting. The system output is 1 if the cumulative weight of all 1-opting units is at least a pre-specified fraction τ of the cumulative weight of all non-abstaining units. Otherwise, the system output is 0.In this paper, we study the effect of limited availability of the voting units on the entire voting system reliability. Two different types of systems are considered. In the system of type 1, the absence of unit output (unit unavailability) is interpreted by the system as abstention from voting. In the system of type 2, the unavailable state of the voting unit and its abstention from voting can be distinguished and the system parameters can be adjusted to optimize its performance for each combination of available units.There are two ways to improve reliability of weighted voting system consisting of units with the given output probability distribution: optimization of system parameters (weights of units and threshold factor value) and units availability enhancement (for example, by choosing proper maintenance policy). This paper shows a method of incorporating information about units' availability into a procedure for determining the optimal system parameters. It also presents a method for determining indices that measure importance of voting units availability for both types of systems. These indices indicate voting units for which efforts of availability enhancement are the most beneficial from the entire system reliability improvement point of view.The approach is based on using a universal generating function technique and optimization procedure presented in [5]. Examples are presented.