Reducing mechanism design to algorithm design via machine learning

We use techniques from sample-complexity in machine learning to reduce problems of incentive-compatible mechanism design to standard algorithmic questions, for a broad class of revenue-maximizing pricing problems. Our reductions imply that for these problems, given an optimal (or β-approximation) algorithm for an algorithmic pricing problem, we can convert it into a (1+?)-approximation (or β(1+?)-approximation) for the incentive-compatible mechanism design problem, so long as the number of bidders is sufficiently large as a function of an appropriate measure of complexity of the class of allowable pricings. We apply these results to the problem of auctioning a digital good, to the attribute auction problem which includes a wide variety of discriminatory pricing problems, and to the problem of item-pricing in unlimited-supply combinatorial auctions. From a machine learning perspective, these settings present several challenges: in particular, the “loss function” is discontinuous, is asymmetric, and has a large range. We address these issues in part by introducing a new form of covering-number bound that is especially well-suited to these problems and may be of independent interest.     

Coverage‐aware connectivity‐constrained unattended sensor deployment in underwater acoustic sensor networks

Careful deployment of nodes in underwater acoustic sensor networks in a distributed manner with the goal of maximized coverage and guaranteed connectivity is a challenging problem because it is very difficult and costly to access the 3D underwater environment. This paper presents a novel algorithm for self‐deployment of nodes in underwater acoustic sensor networks assuming that the nodes are randomly dropped to the water surface and form a densely populated connected network at the water surface. The idea of the algorithm is based on calculating an optimized depth for each node in the network in such a way that the possible sensing coverage overlaps are minimized and the connectivity of final topology is guaranteed. The algorithm has three main phases. In the first phase, nodes are organized in a tree structure that is rooted at the surface station. In the second phase, the depths for all nodes are computed iteratively at surface station. In the final phase, the calculated depths are distributed to nodes so that the nodes start sinking. The performance of the proposed approach is validated through simulation. We observed that the proposed approach performs at least 10% better in terms of network coverage than contemporary schemes in the literature. Copyright © 2016 John Wiley & Sons, Ltd.     

基于EM算法和GOF的宽带分布式 目标检测算法

 针对K分布杂波背景下的宽带分布式目标检测问题,提出了一种基于期望最大化算法和拟合优度检测方法的检测算法.该算法利用期望最大化方法估计杂波参数,提高了估值精度.通过结合拟合优度检测有效利用了目标回波对杂波背景的干扰,并简要分析该算法的恒虚警率性.对仿真数据与实测数据的多个仿真结果表明,与传统的非相干积累方法及基于散射点密度的广义似然相比,该算法检测性能有明显的提高.     

Semi‐supervised classification of facial expression using a mixture of multivariate t distributions

Abstract: This paper addresses the semi‐supervised classification of facial expression images using a mixture of multivariate t distributions. The facial expression features are first extracted into labelled graph vectors using the Gabor wavelet transformation. We then learn a mixture of multivariate t distributions by using the labelled graph vectors, and set correspondence between the component distributions and the basic facial emotions. According to this correspondence, the classification of a given testing image is implemented in a probabilistic way according to its fitted posterior probabilities of component memberships. Specifically, we perform hard classification of the testing image by assigning it into an emotional class that the corresponding mixture component has the highest posterior probability, or softly use the posterior probabilities as the estimates of the semantic ratings of expressions. The experimental results on the Japanese female facial expression database, Ekman's Pictures of Facial Affect database and the AR database demonstrate the effectiveness of the proposed method.     

The fabrication of efficiency-improved W-series interconnect type of module by balancing the performance of single cells

Large dye-sensitized solar cells (DSCs) are usually fabricated as module types instead of single cell types, because the overall efficiency of an area-expanded single DSC is decreased by its large surface resistances and low fill factor (FF). The general DSC module designs are the parallel grid, series interconnect, and series monolithic types. The W-series interconnect type of module has some advantages, such as its easy fabrication and simple structure. Moreover, it also avoids the reduction in the FF. However, it has an efficiency imbalance between the single cells, because of the discrepancy in their luminous intensity. Therefore, the fabrication of the W-series interconnect type of module will be cost-effective only if the problem of its efficiency imbalance is solved. In this study, the thickness of the Pt layer, which has a very high reflection rate, and that of the electrolyte layer are minimized and the transmitted light is reflected by a metallic thin film in order to increase the number of photons absorbed by the dye molecules in the module. As a result, the performance of the efficiency-balanced W-module is improved by approximately 1% as compared to that of the conventional module.     

多用户无线供电通信网络中基于最大加权和速率的优化方案

针对多用户无线供电通信网络系统中的交叉耦合干扰问题,提出了一种基于时间反演技术联合优化上、下行时间分配和功率分配方案,以最大化上行加权和速率.利用时间反演特有的空时聚焦性抑制交叉耦合干扰;然后建立优化模型,将难以求解的加权和速率问题转化为最小均方误差问题;最后通过分级逐次优化变量,分别求出功率和时间的最优解.仿真结果表明,在引入时间反演技术抑制系统的交叉耦合干扰后,系统的平均加权和速率明显提升.     

多天线中继系统中人工噪声辅助的安全波束成形

针对放大转发中继系统中转发信息易被窃听者截获的问题,提出了在中继节点处采用人工噪声辅助的安全波束成形方法。该方法以系统的安全速率最大化（SRM, secrecy rate maximization)为目标,在中继节点的总功率和单个天线功率受限情况下,联合设计最优的中继波束成形矩阵和人工噪声协方差矩阵。由于该SRM问题非凸,设计了双层优化算法,其中采用一维搜索解决外层优化问题,采用半定松弛及内点法解决内层优化问题。理论推导证明,内层优化问题总存在秩为1的最优解,即所采用的松弛技术是紧的。仿真结果表明所提的方法可以显著提高系统的安全性能。     

Projectization-based Enterprise Value Realization Approaches

In the increasingly competitive market,value maximization has become inevitable for enterprises to keep sustainable development.With the benefits of clear definition of scope and objectives,timing,issue tracking,and all that,the managing by projects plays an important role in promoting value realization.This paper first analyzed the components of value maximization objectives,then discussed the relationship between the enterprise value realization process and projectization,including the support of projectization to value maximization objectives and combination of value realization process and projectization,thus proposed approaches to realize enterprise value on the basis of projectization,which are taking all the stakeholders into consideration when setting value objectives,specifying the enterprise value maximization objective,projectizing the implementation of objectives,controlling the projects in a closed loop mode and creating a team culture in enterprises.     

基于γ图像重建放射源三维几何形状的模拟研究

准确评估待检测对象内放射性物质的几何形状,在核设施退役和核安全等方面都具有重要的意义。利用MCNP模拟屏蔽体内不同几何形状的体源,针孔γ相机围绕被探测区域获取投影数据。根据针孔成像的机理,建立系数矩阵,并通过最大似然期望最大(MLEM)算法重建体源的三维位置和形状分布。模拟数据结果表明:该方法可准确地重建出放射性体源的三维位置和形状分布,体源在三维方向上形状的尺寸偏差不大于10%。     

基于信息极大化的ICA算法研究

独立成分分析是在缺乏混合系统和源信号先验知识的条件下,仅通过观测信号来恢复出源信号,已经成为数字信号处理的重要研究方向。文中在研究独立成分分析理论的基础上,介绍了一种基于信息极大化的分离算法,并对混合音频信号进行仿真试验,成功分离出了混合信号中的各个独立成分,仿真结果验证了信息极大化分离算法在语音增强和助听器功能改善方面的优越性,具有一定的理论研究和应用价值。