Geometric and colorimetric error compensation for multi-view images

In general, excessive colorimetric and geometric errors in multi-view images induce visual fatigue to users. Various works have been proposed to reduce these errors, but conventional works have only been available for stereoscopic images while requiring cumbersome additional tasks, and often showing unstable results. In this paper, we propose an effective multi-view image refinement algorithm. The proposed algorithm analyzes such errors in multi-view images from sparse correspondences and compensates them automatically. While the conventional works transform every view to compensate geometric errors, the proposed method transforms only the source views with consideration of a reference view. Therefore this approach can be extended regardless of the number of views. In addition, we also employ uniform view intervals to provide consistent depth perception among views. We correct color inconsistency among views from the correspondences by considering importance and channel properties. Various experimental results show that the proposed algorithm outperforms conventional approaches and generates more visually comfortable multi-view images.     

时域流信号的多任务稀疏贝叶斯动态重构方法研究

为了解决多任务观测条件下时域流信号动态重构面临的块效应问题,该文基于重叠正交变换(LOT)和稀疏贝叶斯学习的贪婪重构框架先后提出了一种流信号多任务稀疏贝叶斯学习算法及其鲁棒增强型的改进算法,前者将LOT时域滑窗推广到多任务条件下,通过贝叶斯概率建模将未知的噪声精度的估计任务从信号重构中解耦并省略,后者进一步引入了重构不确定性的度量,提高了算法的鲁棒性和抑制误差积累的能力。基于浮标实测数据的实验结果表明,相比多任务重构领域代表性较强的时间多稀疏贝叶斯学习(TMSBL)和多任务压缩感知(MT-CS)算法,本文算法在不同信噪比、观测数目和任务数目条件下具有显著更高的重构精度、成功率和效率。     

大规模MIMO时分双工系统的基站天线互易校准算法

对于采用大规模MIMO技术的时分双工系统,基站天线的互易误差会破坏上下行基带信道互易特性,大幅降低系统下行传输性能。考虑到大规模MIMO技术所带来的基站天线间的耦合效应,该文设计了基于总体最小二乘估计的基站天线互易校准算法,以实现对基站的天线互易误差的补偿。该算法以增加计算复杂度为代价,以及通过增加信道测量样本,克服了上下行信道估计误差对现有天线互易误差校准算法的影响。同时,该文通过瑞利商迭代求解降低了该算法的复杂度。若忽略用户天线互易误差,计算机仿真结果表明,该算法相对于现有的基站天线互易误差校正算法,具有1.8 dB左右的性能增益。若考虑用户天线互易误差,该算法相对于已有的算法,具有随信道估计误差方差减小而增大的增益。     

Garbage Collection Scheduling of Aperiodic Tasks

In the previous work of garbage collection （GC） models, scheduling analysis was given based on an assumption that there were no aperiodic mutator tasks. However, it is not true in practical real-time systems. The GC algorithm which can schedule aperiodic tasks is proposed, and the variance of live memory is analyzed. In this algorithm, active tasks are deferred to be processed by GC until the states of tasks become inactive, and the saved sporadic server time can be used to schedule aperiodic tasks. Scheduling the sample task sets demonstrates that this algorithm in this paper can schedule aperiodic tasks and decrease GC work. Thus, the GC algorithm proposed is more flexible and portable.     

考虑载机位置误差的CLS多机无源定位算法

多机无源定位中存在载机位置误差却不予考虑时必然会降低目标的定位跟踪精度。为了解决存在载机位置误差情况下的定位问题,提出了一种考虑载机位置误差的约束最小二乘（CLS）多机无源定位算法。该算法对伪线性观测方程中由于测量误差和载机位置误差而导致的增广系数矩阵的误差协方差阵进行约束,并对伪线性观测方程的误差进行约束最小二乘处理,最终转化为对一组矩阵束的广义特征分解问题。仿真结果表明,相对于最小二乘（LS）算法和扩展卡尔曼滤波（EKF）算法,该算法具有更快的收敛速度和较高的定位精度,并且受载机位置误差影响小,在观测噪声比较大时仍能保持良好的定位性能。      

A multiprocessor-oriented power-conscious scheduling algorithm for periodic tasks

With the rapid development of advanced technology in VLSI circuit designs, many processors could provide dynamic voltage scaling (DVS) to save power consumption when the supply voltage is allowed to be lower. In this paper, we propose a multiprocessor-oriented power-conscious scheduling algorithm for the real-time periodic tasks with task migration constrained scheme. We classify periodic tasks into fixed tasks and migration tasks, and limit the number of migration tasks and the number of destination processors which execute migration tasks. The proposed algorithm is made up of two steps. Firstly, choosing a processor to sort all of the periodic tasks in a non-increasing order according to task utilization, afterwards, allocating them to other processors. Secondly, scheduling the migration tasks with a virtual execution windows policy, and then scheduling the fixed tasks with EDF algorithm. The experiment results show that compared with arbitrary task migration policy and no task migration allowed policy, the power consumption in multiprocessor real-time periodic tasks scheduling is lowered significantly with the proposed algorithm.     

Energy-efficient scheduling for multiprocessors

An energy-efficient scheduling algorithm is proposed for parallel tasks in a multiprocessor system. The proposed algorithm utilises the dynamic voltage scaling (DVS) method for low energy consumption and executes tasks in parallel to compensate for the execution delay induced by the DVS method     

基于时空混合图卷积网络的机器人定位误差预测及补偿方法

工业机器人作为智能制造的重要载体,在大范围复杂任务中具有巨大潜力。但是,定位精度低且难以控制的问题阻碍了机器人在高精度任务的进一步推广。为了提升机器人作业精度,该文提出一种基于时空混合图卷积网络的机器人定位误差预测及补偿方法。首先通过设计图关系编码模块、时空混合特征解码模块,构建基于图卷积网络的机器人位姿误差预测模型;然后,针对传统迭代补偿方法中机器人逆解次数多导致效率低的问题,该文将定位误差补偿问题转化为优化问题,并利用遗传算法同时对位置和姿态进行误差补偿;最后,通过拉丁超立方抽样方法获得训练集,实现机器人定位误差预测模型的训练,并通过实验验证了定位误差预测的准确性以及补偿的效果。     

Task Scheduling Algorithm for the Communication,Ocean, and Meteorological Satellite

In this paper, we propose an efficient single‐resource task scheduling algorithm for the Communication, Ocean, and Meteorological Satellite. Among general satellite planning functions such as constraint check, priority check, and task scheduling, this paper focuses on the task scheduling algorithm, which resolves conflict among tasks which have an exclusion relation and the same priority. The goal of the proposed task scheduling algorithm is to maximize the number of tasks that can be scheduled. The rationale of the algorithm is that a discarded task can be scheduled instead of a previously selected one depending on the expected benefit acquired by doing so. The evaluation results show that the proposed algorithm enhances the number of tasks that can be scheduled considerably.     

一种新的嵌入式Linux实时调度算法

针对现有实时调度算法在实时性能上的不足,提出了一种新的实时任务分类调度算法,根据实时任务的到达情况进行分类,划分为周期任务和非周期任务,并对不同类型的实时任务使用不同的改进的实时调度算法.通过实验,证明此算法与现有实时调度算法相比,综合实时性能有了很大程度的提高.     

一种稳健的稀疏Capon波束形成算法

常规Capon波束形成算法具有相对较高的旁瓣增益,且在期望信号导向矢量存在失配时,阵列输出性能下降甚至失效。为解决这一问题,引入了稀疏约束Capon波束形成算法,该算法降低了旁瓣,对期望信号来向不确定具有一定稳健性,但在幅相误差、期望信号指向偏差等多种误差同时存在的情况下其性能下降。本文在稀疏约束Capon波束形成算法基础上,给出了一种稳健的稀疏Capon波束形成算法。该算法主要是在最差性能最优化的情况下,在稀疏Capon上增加了一个导向矢量存在偏差的约束条件。通过计算机仿真,验证了新算法在多种误差环境下的有效性与优越性。     

费用-时间优化的网格有向无环图调度算法

网格环境下,基于时间限制和费用最小的有向无环图(DAG)调度算法运用经济规律把网格用户中的任务映射到网格资源中运行,弥补了Buyya R提出的算法中未考虑任务运行的优先关系.该算法有两个关键技术:DAG中有效路径的提取能够定位任务何时在资源上运行;DAG中在作业运行时间尽可能允许的情况下,把任务映射到价格便宜的资源上运行.通过仿真实例,论证了该算法的优越性.     

两阶段平移、旋转图像高精度配准算法

图像配准在图像处理中是十分重要的,通常是许多现代图像处理和计算机视觉任务一个关键的预处理步骤,许多算法和技术已经被提出用来解决配准问题.本文提出一种稳健的两阶段层次配准算法,在频域组合相位相关和谱对消技术对平移和旋转图像获得亚像素精度的配准.算法第一阶段首先利用一维FFT技术实现图像的旋转以确定旋转角度,并利用这个旋转角度将两幅图像之间的运动简化为平移运动,然后利用相位相关法确定整数像素平移参数.算法第二阶段运用谱对消技术确定亚像素平移参数.提出的算法甚至在图像因为下采样而包含混淆误差情况下仍然能够获得亚像素精度配准.     

Heuristic Sarsa algorithm based on value function transfer

With the problem of slow convergence for traditional Sarsa algorithm,an improved heuristic Sarsa algorithm based on value function transfer was proposed.The algorithm combined traditional Sarsa algorithm and value function transfer method,and the algorithm introduced bisimulation metric and used it to measure the similarity between new tasks and historical tasks in which those two tasks had the same state space and action space and speed up the algorithm convergence.In addition,combined with heuristic exploration method,the algorithm introduced Bayesian inference and used variational inference to measure information gain.Finally,using the obtained information gain to build intrinsic reward function model as exploring factors,to speed up the convergence of the algorithm.Applying the proposed algorithm to the traditional Grid World problem,and compared with the traditional Sarsa algorithm,the Q-Learning algorithm,and the VFT-Sarsa algorithm,the IGP-Sarsa algorithm with better convergence performance,the experiment results show that the proposed algorithm has faster convergence speed and better convergence stability.     

Joint Angle and Array Gain-Phase Errors Estimation Using PM-like Algorithm for Bistatic MIMO Radar

This paper discusses the problem of the direction of departure (DOD) and the direction of arrival (DOA) estimation for multi-input multi-output (MIMO) radar with array gain-phase errors. In this paper, we propose a propagator method (PM)-like algorithm for joint angle and array gain-phase errors estimation in MIMO radar. The proposed method not only yields automatically paired estimates of the angles and gain-phase errors but also has much better gain-phase errors estimation performance than the estimation of signal parameters via rotational invariance techniques (ESPRIT)-like algorithm; this has higher computational cost than the proposed algorithm. Furthermore, the proposed algorithm has angle estimation performance very close to ESPRIT-like algorithm. We also derive the Cramér–Rao bound (CRB) for MIMO radar with array gain-phase errors. Simulation results present the usefulness of our approach.     

Robust antenna array calibration and accurate angle estimation based on least trimmed squares

A robust antenna array calibration and single target angle estimation algorithm is proposed. The proposed algorithm is based on the least trimmed squares algorithm and operates in two steps. First, the conventional least squares algorithm is used to estimate the intermediate phases (or angle) and the residual values at each element are calculated. In the second step, it excludes large residual elements and uses only the smallest of them, which prevents large errors during the angle estimation. The least trimmed-based phase difference approximation algorithm is simple to implement and is a practical way of mitigating errors at the antenna elements that are due to hardware and imperfect calibration. The results demonstrate that our proposed algorithm is robust and outperforms other algorithms in three scenarios.     

基于UKF地面雷达网的时空配准方法

为消除地面雷达的系统误差和时间误差,提出了基于Unscented卡尔曼滤波(UKF)的三维空间地面雷达网的时空配准方法。该方法将系统误差、时间误差与目标运动模型组合在一个动态模型中,并用UKF方法进行估计。Monte-Carlo仿真表明:该方法能同时有效地估计雷达的系统误差、时间误差,同时得到目标航迹。     

大规模MIMO时分双工系统的鲁棒预编码设计

对于采用大规模MIMO技术的时分双工系统,天线互易误差会破坏上下行信道互易特性,大幅降低预编码算法下行传输性能。由于实际系统难以完全消除天线互易误差,该文以最大化各用户平均信泄噪比为目标,根据天线互易误差的统计特性,设计了对该误差具有鲁棒性的线性预编码算法。同时为了进一步降低用户接收端的等效噪声功率,该文还将该线性鲁棒预编码算法扩展为基于矢量扰动的非线性鲁棒预编码算法,并通过减格辅助技术降低其扰动矢量求解复杂度,使其更适用于大规模MIMO系统应用。计算机仿真结果表明在存在基站天线互易误差条件下,该文所提出的线性与非线性鲁棒性预编码算法的性能均优于传统预编码算法的性能。     

基于改进遗传算法的网格资源调度算法

网格计算关注大规模的资源和任务调度，要求采用的调度算法能够具有高效性。提出一种基于改进遗传算法的资源调度算法，该算法综合考虑了资源任务分配量以及任务完成时间，从而设计出良好的交叉和选择算子，既能够保留完成时间比较小的个体又能够保留具有一部分优秀资源分配方式的个体．算法具有较好的效率和收敛性。     

基于价值优化的相控阵雷达任务调度算法

针对相控阵雷达时间资源分配问题,该文提出一种基于价值优化的任务调度算法。首先建立任务调度属性参数,对跟踪任务队列进行可行性分析和筛选操作,确定跟踪任务调度属性。其次,根据任务最大价值及其变化斜率,建立关于实际执行时刻的动态任务价值函数,并基于此构建任务调度的价值优化模型,对跟踪任务执行时刻进行分配,以更好满足及时性原则。最后,利用执行跟踪任务间的空闲时间片对搜索任务进行调度。仿真结果表明,该文算法有效减小了时间偏移量,提升了实现价值率。