Application of Rollout Strategy to Test Points Selection for Integer-Coded Fault Wise Table

Test points selection for integer-coded fault wise table is a discrete optimization problem. The global minimum set of test points can only be guaranteed by an exhaustive search which is eompurationally expensive. In this paper, this problem is formulated as a heuristic depth-first graph search problem at first. The graph node expanding method and rules are given. Then, rollout strategies are applied, which can be combined with the heuristic graph search algorithms, in a computationally more efficient manner than the optimal strategies, to obtain solutions superior to those using the greedy heuristic algorithms. The proposed rollout-based test points selection algorithm is illustrated and tested using an analog circuit and a set of simulated integer-coded fault wise tables. Computa- tional results are shown, which suggest that the rollout strategy policies are significantly better than other strategies.     

Novel method to obtain the optimal polygonal approximation of digital planar curves based on Mixed Integer Programming

Polygonal approximations of digital planar curves are very useful for a considerable number of applications in computer vision. A great interest in this area has generated a huge number of methods for obtaining polygonal approximations. A good measure to compare these methods is known as Rosin’s merit. This measure uses the optimal polygonal approximation, but the state-of-the-art methods require a tremendous computation time for obtaining this optimal solution.We focus on the problem of obtaining the optimal polygonal approximation of a digital planar curve. Given N ordered points on a Euclidean plane, an efficient method to obtain M points that defines a polygonal approximation with the minimum distortion is proposed.The new solution relies on Mixed Integer Programming techniques in order to obtain the minimum value of distortion. Results, show that computation time for the new method dramatically decreases in comparison with state-of-the-art methods for obtaining the optimal polygonal approximation.     

一种提升城区网格道路5G覆盖率的新方法

城区网格道路是移动通信用户重要的使用场景。与其他用户静止场景相比,道路上UE移动性导致客户感知相对较差。传统城区网格道路测试优化存在整治不彻底、优化效率低、工单重复派、工作无重点等痛点。提出了一种提升城区网格道路5G覆盖率的新方法,引入测试问题圆域的概念,实现了零星测试问题点的有效聚合,并用“聚合度”“重复度”定量标识测试问题优先级;通过测试问题圆域“理想方位角”和“合适小区”的计算,提出了测试问题最优覆盖小区的计算方法,可有效输出问题圆域的优化方案。所提方法已在现网部署,有效支撑了全网城区网格道路测试优化工作,5G覆盖率由89.95%提升到98.86%,应用效果较好。     

核估计的最佳阈值SAR图像海岸线提取

针对SAR图像海陆分割的最佳阈值难以确定的问题，提出了一种差值核估计的自适应最佳阈值SAR图像海岸线提取方法。首先将图像的频数分布直方图看作一组以灰度值为横坐标和以频数为纵坐标的数据点集，然后以任一点为中心点构建左右两个邻域；定义两邻域内点横坐标到中心点横坐标距离的核函数；以核函数为权重先计算中心点纵坐标与左邻域内所有点纵坐标之差的加权平均值，再计算右邻域内所有点纵坐标与中心点纵坐标之差的加权平均值，并定义后者与前者之差为该数据点在直方图中坡度由陡变缓的跳变幅度，最后将拥有最大跳变幅度的数据点对应的横坐标作为海陆分割的最佳阈值。为去除初始分割结果中海陆交界处的不规则形状像素集，设计基于滤波操作的后处理过程。对真实大尺度SAR图像提取结果的定量评价表明提出方法可以高精度地提取出光滑、连续的海岸线，相较其他阈值分割法有更强的实用性。     

一种基于遗传算法的SVM决策树多分类方法

在当前的机器学习领域,如何利用支持向量机（SVM）对多类目标进行分类,同时提高分类器的分类效率已经成为研究的热点之一,有效地解决此问题对于提高目标的识别概率具有较大意义。本文针对SVM多分类问题提出了一种基于遗传算法的SVM最优决策树生成算法。算法以随机生成的决策树构建的SVM分类器对同一测试样本的分类正确率作为遗传算法的适应度函数,通过遗传算法寻找到最优决策树,再以最优决策树构建SVM分类器,最终实现SVM的多分类。将该算法应用于低空飞行声目标识别问题,实验结果表明,新方法比传统的1-a-1、1-a-r、SVM-DL和GADT-SVM方法有更高的分类精度和更短的分类时间。      

Genetic algorithm‐based content distribution strategy for F‐RAN architectures

Fog radio access network (F‐RAN) architectures provide markedly improved performance compared to conventional approaches. In this paper, an efficient genetic algorithm‐based content distribution scheme is proposed that improves the throughput and reduces the transmission delay of a F‐RAN. First, an F‐RAN system model is presented that includes a certain number of randomly distributed fog access points (F‐APs) that cache popular content from cloud and other sources. Second, the problem of efficient content distribution in F‐RANs is described. Third, the details of the proposed optimal genetic algorithm‐based content distribution scheme are presented. Finally, simulation results are presented that show the performance of the proposed algorithm rapidly approaches the optimal throughput. When compared with the performance of existing random and exhaustive algorithms, that of the proposed method is demonstrably superior.     

基于图论的单线激光雷达数据匹配方法

针对传统的基于单线激光雷达的匹配方法在多障碍物环境下匹配精度低的问题,提出了一种基于图论的匹配方法。该方法从数据点集中提取出具有凹凸性质的特征点,提取对应的线段并构建属性图模型,将点集配准问题转化为属性图匹配问题。与传统的基于线段的匹配算法相比,所提方法基于图模型引入了更多的线段之间的几何关系,使算法可以适用于多障碍物环境以及动态多障碍物环境;与传统的基于点的匹配方法相比,该方法依据特征点组成的线段进行几何意义上的匹配,通过属性图模型快速找到局部观测数据与全局数据的最佳匹配,提升了运算效率,同时也避免了传统方法易陷入局部最优解的缺点。     

Optimal Test Points Selection Based on Multi-Objective Genetic Algorithm

A new approach to select anoptimal set of test points is proposed. The described method uses fault-wise table and multi-objective genetic algorithm to find the optimal set of test points. First, the fault-wise table is constructed whose entries are measurements associated with faults and test points. The selection of optimal test points is transformed to the selection of the columns that isolate the rows of the table. Then, four objectives are described according to practical test requirements. The multi-objective genetic algorithm is explained. Finally, the presented approach is illustrated by a practical example. The results indicate that the proposed method can efficiently and accurately find the optimal set of test points and is practical for large scale systems.     

Energy-efficient power allocation for NOMA heterogeneous networks with imperfect CSI

In this paper, an optimal user power allocation scheme is proposed to maximize the energy efficiency for downlink non-orthogonal multiple access (NOMA) heterogeneous networks (HetNets). Considering channel estimation errors and inter-user interference under imperfect channel state information (CSI), the energy efficiency optimization problem is formulated, which is non-deterministic polynomial (NP)-hard and non-convex. To cope with this intractable problem, the optimization problem is converted into a convex problem and address it by the Lagrangian dual method. However, it is difficult to obtain closed-form solutions since the variables are coupled with each other. Therefore, a Lagrangian and sub-gradient based algorithm is proposed. In the inner layer loop, optimal powers are derived by the sub-gradient method. In the outer layer loop, optimal Lagrangian dual variables are obtained. Simulation results show that the proposed algorithm can significantly improve energy efficiency compared with traditional power allocation algorithms.     

全空域多目标测控天线零点约束方向图综合方法

针对全空域多目标测控天线相互干扰的问题,提出了一种基于零点约束的全空域多目标测控天线方向图综合方法.该方法对多个干扰目标方向进行零点约束,求取逼近给定方向图的最优权矢量的闭合解,生成具有干扰抑制能力的优化波束方向图.仿真结果表明,所提方向图综合方法在维持原有给定方向图特性的前提下,可在多个方向形成有效零点.在等效2m口径全空域多目标测控实物天线对该方法开展试验验证,结果表明在干扰方向抑制能力大于60 dB,证明了方法的正确性.     

Partition sampling strategy for robot motion planning under uncertainty

In order to solve the sensing and motion uncertainty problem of motion planning in narrow passage environment, a partition sampling strategy based on partially observable Markov decision process (POMDP) was proposed. The method combines partition sampling strategy and can improve the success rate of the robot motion planning in the narrow passage. Firstly, the environment is divided into open area and narrow area by using a partition sampling strategy, and generates the initial trajectory of the robot with fewer sampling points. Secondly, the method can calculate a local optimal solution of the initial nominal trajectory by solving POMDP problem, and iterates an overall optimal trajectory of robot motion. The proposed method follows the general POMDP solution framework, in which the belief dynamics is approximated by an extended Kalman filter (EKF), and the value function is represented by an effective quadratic function in the belief space near the nominal trajectory. Using a belief space variant of iterative linear quadratic Gaussian (iLQG) to perform the value iteration, which results in a linear control policy over the belief space that is locally optimal around the nominal trajectory. A new nominal trajectory is generated by executing the control strategy iteration, and the process is repeated until it converges to a locally optimal solution. Finally, the robot gets the optimal trajectory to safely pass through a narrow passage. The experimental results show that the proposed method can efficiently improves the performance of motion planning under uncertainty.     

An efficient rate-distortion optimal shape coding approach utilizing a skeleton-based decomposition

In this paper, we present a new shape-coding approach, which decouples the shape information into two independent signal data sets; the skeleton and the boundary distance from the skeleton. The major benefit of this approach is that it allows for a more flexible tradeoff between approximation error and bit budget. Curves of arbitrary order can be utilized for approximating both the skeleton and distance signals. For a given bit budget for a video frame, we solve the problem of choosing the number and location of the control points for all skeleton and distance signals of all boundaries within a frame, so that the overall distortion is minimized. An operational rate-distortion (ORD) optimal approach using Lagrangian relaxation and a four-dimensional direct acyclic graph (DAG) shortest path algorithm is developed for solving the problem. To reduce the computational complexity from O(N/sup 5/) to O(N/sup 3/), where N is the number of admissible control points for a skeleton, a suboptimal greedy-trellis search algorithm is proposed and compared with the optimal algorithm. In addition, an even more efficient algorithm with computational complexity O(N/sup 2/) that finds an ORD optimal solution using a relaxed distortion criterion is also proposed and compared with the optimal solution. Experimental results demonstrate that our proposed approaches outperform existing ORD optimal approaches, which do not follow the same decomposition of the source data.     

平台侧位置指纹定位系统中接收端问题的优化

当前室内位置指纹定位系统主要用于对移动端的定位.借鉴其定位机理,研究了对无线电发射端的定位,属于平台侧位置指纹定位系统.从部署接收端的位置以减小定位误差的角度出发,提出了增大参考点之间欧式距离确定接收端位置的方案.同时,提出利用覆盖率的概念确定定位区间的接收端个数以满足区间定位的需求.建立了接收端位置及个数优化问题的数学模型,并用遗传算法和全覆盖原则对优化问题进行求解,给出了优化问题的实现流程.针对不同空间,对优化问题进行了仿真,比较了经验布置接收端和优化布置接收端的定位结果误差及接收端是否满足全覆盖的定位结果误差,验证了所提方法的合理性,对定位前部署接收端的个数和位置有一定的指导意义.     

基于列生成的毫米波多连接链路配置调度算法

多连接技术允许用户同时建立和保持与多个小区/接入点的连接,通过网络元素之间的协调在吞吐量和可靠性方面大幅提高网络性能。针对毫米波通信中超高频段的链路中断问题,研究了多连接基于链路配置的调度算法,以提高链路调度效率,降低复杂度。首先,在系统模型中采用链路配置作为优化变量;其次,设计了多连接比例公平的调度准则;最后,提出一种基于列生成算法的链路配置调度优化算法,利用Dantzig-Wolfe分解将原问题分解为限制主问题和定价问题,并结合分支定界方法获得最优解。仿真结果表明,所提算法能够在数值上逼近全局最优,并且比现有的毫米波蜂窝网络链路调度方案增益平均提高40%以上。     

均值反馈下息与能量传输系统的预编码设计

该文研究了多天线信息与能量联合传输系统的最优预编码设计问题，其中发送端只具备信道均值反馈信息。预编码设计目标是最大化系统信息传输速率的期望值，同时满足能量接收机的最低能量要求。将该问题归结为一个半正定规划，进一步转换成对偶问题并且证明了两个问题是等价的；然后采用协方差矩阵分解技术，把对偶问题的约束消除，变为无约束的优化问题，提出了基于梯度下降的搜索算法进行求解。此外，该文还给出了关于信息－能量可达域边界的引理，提供了两个关键边界点。仿真实验验证了提出预编码算法的收敛性，给出了若干系统配置下的系统信息－能量可达域。结果表明，与若干经典发送方案相比，提出算法的信息－能量可达域更加广阔。      

Multiple kernel relevance vector machine for geospatial objects detection in high-resolution remote sensing images

Geospatial objects detection within complex environment is a challenging problem in remote sensing area. In this paper, we derive an extension of the Relevance Vector Machine (RVM) technique to multiple kernel version. The proposed method learns an optimal kernel combination and the associated classifier simultaneously. Two feature types are extracted from images, forming basis kernels. Then these basis kernels are weighted combined and resulted the composite kernel exploits interesting points and appearance information of objects simultaneously. Weights and the detection model are finally learnt by a new algorithm. Experimental results show that the proposed method improve detection accuracy to above 88%, yields good interpretation for the selected subset of features and appears sparser than traditional single-kernel RVMs.     

基于粒子群算法的矩形件优化排样

针对矩形件排样问题,提出了一种应用粒子群算法优化求解的方法.该方法首先将矩形件的排样问题转化为适于优化的排列问题,然后用粒子群优化算法对整个解空间进行高效搜索,在进化计算过程中应用了自适应调整规则,最终可获得全局最优的排样结果.排样实例表明,该优化排样算法行之有效,具有广泛的适应性.     

基于弹丸定位精度分析的传感器布局优化方法

能否快速准确地对超声速弹丸在靶面上的弹着点进行定位,是影响智能报靶系统性能的核心因素。在通过建立弹丸入射模型获取弹丸入射点的过程中,传感器的布局形式对弹丸入射精度的求解至关重要。针对如何选取最佳的传感器布局方法,该文提出使用几何精度因子(GDOP)精度分析与优化算法相结合的弹丸入射精度分析方法,通过计算高精度下弹丸入射精度等号线的面积,在特定范围内寻找最佳的传感器布局形式。基于弹丸入射精度分析法进行多组理论可行性仿真实验,实际情况下进行有限入射范围仿真实验及拓展实验等,最后得出基于高精度弹丸入射定位中传感器布局的基本规律。通过多组实验验证可得,该文提出的弹丸定位精度分析法可有效地选取高精度的传感器布局方式,且最优的传感器布局均符合高精度传感器布局的基本规律。     

图像拼接中运动目标干扰的自适应消除

运动目标在图像拼接时,易产生重影现象.在对SURF算法进行改善的基础上,提出了自适应去除重影的拼接算法.利用增强的单通道图像对其特征点进行提取、匹配,再利用帧差法确定出运动目标在图像重叠区域的位置;取运动目标区域的中心点作为参考点,采用改进的加权融合算法求取加权系数,以增大权值差异.实验表明所提方法能较好地解决运动目标对图像拼接的干扰问题,与最优拼接缝多频率融合算法相比,融合质量、清晰度以及拼接的实时性得到了提高.