一种基于高阶统计信息的信噪比估计改进算法

针对多进制正交幅度调制(Multiple quadrature amplitude modulation,MQAM)信号在低信噪比条件下估计精度不高的问题,提出了一种基于综合利用高阶统计信息的信噪比估计改进算法。根据所选高阶统计量最高阶数的不同,建立了3种信噪比与多种高阶统计量运算式之间的线性关系,利用全回归线性分析方法将3种线性关系转化为3种全回归模型,并求解模型系数。该算法充分利用了多种高阶统计量的有用信息,提高了信噪比估计精度。MQAM的仿真结果表明:在低信噪比条件下,该算法减小了信噪比估计误差,其估计性能明显优于传统的其他算法,且3种模型估计性能依次增加,可依据不同的信噪比要求对3种模型进行选取。     

Google Map数字栅格地图算法及应用

Google地图是Google向全球提供的电子地图服务,包括丰富的地图和黄页资源,特别是局部详细的卫星地图。通过具体分析Google Map不同坐标系下的坐标转换、Web墨卡托投影方式、地图瓦片URL组织结构,系统地研究了Google地图的算法及实现,并在VS2008环境下用C#语言实现了任意缩放系数下指定地图类型URL的合成和对应图片的下载。文中列出了部分程序代码以帮助大家进行后续开发设计,更有效地将Google地图集成到应用系统中。实验证实,该方法能够快速准确地下载指定范围的地图。     

一种基于光照变化补偿的颜色识别方法

针对RoboCup中型组足球机器人比赛中光照变化会使颜色发生色彩漂移,影响颜色识别的准确性问题,提出一种基于光照变化补偿的颜色识别方法。该方法首先利用球的历史信息预测球的位置,然后在较小的区域内用基于色调直方图反向投影的方法找到球后,通过球的亮度直方图的变化计算出光照变化率,用于动态补偿颜色查找表。实验表明该方法能提高颜色识别的光照自适应性。     

光学遥感舰船目标识别方法

提出一种基于粗糙集理论和分层判别回归技术的光学遥感舰船目标识别方法。该方法首先提出新的光学遥感舰船识别特征———面积比编码,并与四类特征组合作为备选特征;然后基于粗糙集理论按同可区分度来计算各备选特征的重要性权值,自动选择出对正确识别贡献较大的特征组合;最后根据分层判别回归原理生成分类判决树来识别光学遥感舰船目标。实验结果表明,本文方法在识别精度和速度方面优于最近邻和支持向量机方法,且通用可行。     

基于线性回归的无线传感器网络链路质量估计方法研究

针对无线传感器网络链路质量估计模型中回归算法复杂度高、缺少统一分类标准和公开数据集等问题,提出了一种基于EWMA和线性回归的链路质量估计方法ELR-LQE。以物理层获取的RSSI、LQI和SNR,以及包接收率PRR作为度量参数,分别在多种实验环境中采用不同的发射功率、竞争条件和部署方式采集数据,建立了链路质量估计数据集。通过最小值填充和EWMA对数据进行预处理,明显提高了回归模型的输入特征与链路质量的相关性。与现有方法相比,提出方法易于和网络层协议适配,并且复杂度较低,适合在资源有限的无线传感器网络节点中实现。实验结果显示,ELR-LQE具有较高的精度,在多种实验条件下平均的ME为4.6×10-2,R2为0.99。     

3D human pose estimation in motion based on multi-stage regression

3D human pose estimation in motion is a hot research direction in the field of computer vision. However, the performance of the algorithm is affected by the complexity of 3D spatial information, self-occlusion of human body, mapping uncertainty and other problems. In this paper, we propose a 3D human joint localization method based on multi-stage regression depth network and 2D to 3D point mapping algorithm. First of all, we use a single RGB image as the input, through the introduction of heatmap and multi-stage regression to constantly optimize the coordinates of human joint points. Then we input the 2D joint points into the mapping network for calculation, and get the coordinates of 3D human body joint points, and then to complete the 3D human body pose estimation task. The MPJPE of the algorithm in Human3.6 M dataset is 40.7. The evaluation of dataset shows that our method has obvious advantages.     

Improving human robot collaboration through Force/Torque based learning for object manipulation

Human–Robot Collaboration (HRC) is a term used to describe tasks in which robots and humans work together to achieve a goal. Unlike traditional industrial robots, collaborative robots need to be adaptive; able to alter their approach to better suit the situation and the needs of the human partner. As traditional programming techniques can struggle with the complexity required, an emerging approach is to learn a skill by observing human demonstration and imitating the motions; commonly known as Learning from Demonstration (LfD). In this work, we present a LfD methodology that combines an ensemble machine learning algorithm (i.e. Random Forest (RF)) with stochastic regression, using haptic information captured from human demonstration. The capabilities of the proposed method are evaluated using two collaborative tasks; co-manipulation of an object (where the human provides the guidance but the robot handles the objects weight) and collaborative assembly of simple interlocking parts. The proposed method is shown to be capable of imitation learning; interpreting human actions and producing equivalent robot motion across a diverse range of initial and final conditions. After verifying that ensemble machine learning can be utilised for real robotics problems, we propose a further extension utilising Weighted Random Forest (WRF) that attaches weights to each tree based on its performance. It is then shown that the WRF approach outperforms RF in HRC tasks.     

避雷器接地电阻的测量与预测方法

介绍了避雷器三极法测量接地电阻的接线、测量原理及测量电压的选取,根据测得的历史数据建立了基于回归分析的接地电阻变化趋势预测模型,并通过标准离差检验证明了该预测模型可用于实际接地电阻的预测。实践表明,该测量与预测方法切实可行,能在一定程度上避免因接地电阻超标而引发的雷击事故。     

基于软测量的化工精馏过程推断控制策略

针对化工精馏过程产品成分无法在线检测及其用温度间接控制产品成分的常规控制策略存在着控制精度低的问题,提出基于软测量的精馏过程成分非线性串级推断控制策略。该控制策略首先提出核岭回归的实时软测量方法,即利用满足Mercer条件的核函数改进线性岭回归算法,实现精馏过程产品成分的在线检测;然后在此基础上,提出一种新的非线性串级推断控制策略,即副环采用常规的温度间接控制,主环采用基于核岭回归软测量的推断控制策略。通过Mejedell等建立的精馏塔动态模型分别对单端和双端成分非线性串级推断控制策略性能进行分析,仿真结果表明,与传统控制方案比较,新控制策略的控制质量有了较大提高,控制结构简单,易于实施。     

Numerical investigation of zoomable holographic projection without a zoom lens

Holographic projection is for laser displays and has the merits of being aberration free, producing high‐contrast images, having the ability of color reconstruction with one spatial light modulator, and so on. In this paper, we propose a zoomable holographic projection without using a zoom lens and verify the proposed method by using numerical simulation. Although such a system can be readily realized to use the features of holography, which is capable of recording a large image exceeding the hologram size, the required calculation is very time consuming. For acceleration, we used shifted Fresnel diffraction for setting different sampling rates on a hologram and projected image. The proposed method can project any zoom‐in and zoom‐out image between zeroth‐order and first‐order lights, and the processing time and required memory for the zoom are constant.