Source Inversion by Forward Integration in Inertial Flows

Inertial particles are finite‐sized objects traveling with a certain velocity that differs from the underlying carrying flow, i.e., they are mass‐dependent and subject to inertia. Their backward integration is in practice infeasible, since a slight change in the initial velocity causes extreme changes in the recovered position. Thus, if an inertial particle is observed, it is difficult to recover where it came from. This is known as the source inversion problem, which has many practical applications in recovering the source of airborne or waterborne pollutions. Inertial trajectories live in a higher dimensional spatio‐velocity space. In this paper, we show that this space is only sparsely populated. Assuming that inertial particles are released with a given initial velocity (e.g., from rest), particles may reach a certain location only with a limited set of possible velocities. In fact, with increasing integration duration and dependent on the particle response time, inertial particles converge to a terminal velocity. We show that the set of initial positions that lead to the same location form a curve. We extract these curves by devising a derived vector field in which they appear as tangent curves. Most importantly, the derived vector field only involves forward integrated flow map gradients, which are much more stable to compute than backward trajectories. After extraction, we interactively visualize the curves in the domain and display the reached velocities using glyphs. In addition, we encode the rate of change of the terminal velocity along the curves, which gives a notion for the convergence to the terminal velocity. With this, we present the first solution to the source inversion problem that considers actual inertial trajectories. We apply the method to steady and unsteady flows in both 2D and 3D domains.     

基于散射计波浪参数反演模型的改进算法实验

一种新的利用散射计(ERS1/2)数据反演有效波高和平均周期的模式被提出。通过俄罗斯学者利用浮标数据建立完全成长风浪条件下有效波高与风速之间的关系,与匹配浮标观测的有效波高数据对比,区分完全成长风浪、成长风浪和涌浪3种海况下的匹配数据;利用BP神经网络建立模式反演3种海况下的有效波高,均方根误差分别为0.53、0.57和0.86m,反演平均周期均方根误差分别为0.69、1.04和1.36s。这种反演方法在完全成长风浪海况下最好,依次是成长风浪和涌浪海况。该研究为散射计数据反演波浪参数提供了依据,使大面积反演波浪参数成为可能。     

一种反演问题求解的免疫克隆粒子群优化算法

为了克服标准粒子群优化(PSO)算法易陷入局部最优以及进化后期收敛速度慢等缺陷,分析了标准PSO算法早熟收敛的原因,提出了基于混合变异机制的免疫克隆粒子群优化(ICPSO)算法并将其应用到波阻抗反演问题中.克隆选择算子能够在局部极值点接近全局最优点时有效增强最优粒子跳出局部解的能力;引入混沌映射Tent序列加速最优粒子的变异学习,在局部极值点与全局最优点距离较远时扩大遍历范围,避免陷入局部极值.通过理论模型试算表明,ICPSO算法在进行波阻抗反演时不仅收敛速度快,而且具有较高的反演精度和抗噪性能.     

Full Wave Modelling of Light Propagation and Reflection

The propagation and reflection of electromagnetic waves in a three‐dimensional environment is simulated, and realistic images are produced using the resulting light distributions and reflectance functions. A finite difference time domain method is employed to advance the electric and magnetic fields in a scene. Surfaces containing wavelength scaled structures are created, the interaction of the electromagnetic waves with these nano‐structured materials is calculated, and the sub‐surface interference and diffraction effects are modelled. The result is a reflectance function with wavelength composition and spatial distribution properties that could not have been predicted using classic computer graphic ray tracing approaches. The techniques are employed to reproduce demonstrations of simple interference and diffraction effects, and to create computer‐generated pictures of a Morpho butterfly.     

Binaural Source Localization by Joint Estimation of ILD and ITD

In this paper, we propose a binaural source localization method based on interaural time differences (ITDs) and interaural level differences (ILDs). The two cues, computed from a two-channel time-frequency representation, are combined in order to estimate the azimuth of sources in binaural recording. We introduce an individual parametric model for the ITD and ILD, and an average parametric model that sets us free from measurements of the subjects' HRIRs for sound localization. We conduct several experiments to validate the proposed approach and show that it compares favorably with available techniques.     

Selective Branch Inversion: Confidence Estimation for Branch Predictors

This paper describes a family of branch predictors that use confidence estimation to improve the performance of an underlying branch predictor. This method, referred to as Selective Branch Inversion (SBI), uses a confidence estimator to determine when the branch direction prediction is likely to be incorrect; branch decisions for these low-confidence branches are inverted. SBI with an underlying Gshare branch predictor outperforms other equal sized predictors such as the best history length Gshare predictor, as well as equally complex McFarling and Bi-Mode predictors. Our analysis shows that SBI achieves its performance through conflict detection and correction, rather than through conflict avoidance as some of the previously proposed predictors such as Bi-Mode and Agree. We also show that SBI is applicable to other underlying predictors, such as the McFarling Combined predictor. Finally we show that Dynamic Inversion Monitoring (DIM) can be used as a safeguard to turn off SBI in cases where it degrades the overall performance.     

基于路由生命期的动态源路由协议

无线Ad hoc网络拓扑结构的频繁变化以及无线信道的不稳定,使得如何提高路由可靠性成为无线Ad hoc网络路由协议研究的主要目标之一.在动态源路由协议(Dynamic Source Routing,以下简称DSR)基础上提出一个新的基于路由生命期估计的Ad hoc网络路由协议,REBDSR(Route-lifetime Estimation Based Dynamic Source Routing).该协议通过对链路状态预测估计路由生命期;路由发现算法同时使用路由生命期、路由跳数作为路径选择参数;当路由上的链路进入危险期后,启动主动式路由维护机制,发送路由失效警告以保证快速路由切换.REBDSR还以路由生命期为超时值进行路由缓存管理,解决了DSR路由缓存中存在较多过时路由的问题.大量仿真实验表明:在网络中载和重载情况下,REBDSR协议的整体性能要优于DSR协议,特别是在节点运动频繁的网络中,REBDSR协议的性能优势更为明显.     

利用噪声谱进行风浪声场特征反演

通过建立修正的风浪噪声模型,研究风浪声场特征的反演.在实测数据中提取100段进行频谱分析,建立不同频段噪声谱均值曲线.利用均值曲线风浪模型进行优化,建立修正的风浪声场特征反演模型.对APL和库普曼-费尔拉风浪噪声模型进行修正获得高频段反演模型;对克努森频谱浅海区模型进行修正获得低频段反演模型.对建立的全频段模型进行数据反演,生成一定范围内幅值服从高斯分布、相位服从均匀分布的噪声信号,即风浪信号时域输出.仿真结果表明,利用合理的反演模型,可以通过数据反演获得准确的海洋风浪噪声声场特征信号.为评价反演的准确性,对反演结果进行验证分析.     

相关性算法在超声波形分析中的应用

相关的概念是为研究随机信号的统计特性而引入的,相关性可以用来描述为两组信号的相似程度,超声在介质中传播会产生多次反射波,通过计算各次波的相关系数,可以获得超声在介质中的传输时间,从而得到介质的厚度.     

传感器网络中利用反演集合估计的机器人定位方法

针对大型协作环境中移动机器人的全局定位问题,提出根据机器人车载传感器、环境传感器以及其他机器人的实时数据估计移动机器人的位置。首先,提出的方法整合大量不同类型传感器,从最简单传感器到最复杂传感器;然后,考虑了测量值数量可变、通用测角测量、受容错约束的测量统计知识等约束条件,将非线性边界误差估计问题看作一种反演集合。最后处理特定类型的异常值和不精确环境下的模型误差。完成了误差和异常值的处理,就基本上获得了定位图,解决了移动机器人的定位问题。提出的方法利用实物实验进行验证。测试区域装备有多个传感器、固定在墙顶部的摄像机以及位于机器人上的可见标记。实验结果表明提出的方法在协作环境中具有明显优势,处理异常值更加可靠。     

声源定位中的时延估计技术

时延估计(TDE)是阵列信号处理中的一项关键技术,其目的是要估计出同源信号到达不同传感器时,由于传输距离不同而引起的时间差。现有的TDE算法主要包括经典的广义互相关(GCC)方法、自适应最小均方(LMS)方法、基于子空间的特征值分解(EVD)方法和基于传递函数比(ATF-s ratio)的方法等。这些算法因其抗噪和抗混响性能不同,有着各自的应用场合。本文首先对现有的各种TDE算法进行分类论述,进而通过综合比较揭示了它们各自的优缺点,最后给出了进一步的研究方向。     

基于CUDA的并行全搜索运动估计算法

为了提高H.264视频编码效率,基于计算统一设备架构(CUDA)的并行全搜索运动估计算法,并利用GPU强大的计算能力和CUDA优化的存储层次结构,以加速H.264编码中的运动估计.与传统的以牺牲视频质量来提升运动估计性能的方法不同,该算法在保证视频质量的同时,结合运动估计计算密集、计算量大等特点,充分利用CUDA架构的并行性加快运动估计的速度,从而达到提高实时编码速度的目的.在GTX280实验平台上的实验结果显示,采用文中算法比优化的CPU实现可获得高达70倍的加速比.     

一种易于并行实现的全局运动估计算法

提出一种新的全局运动匹配算法,该算法可高效地将匹配任务分配在多个处理器上,通过协处理器并行工作,最终实现高质量的编码视频。     

ATM网络中全动态视频源的二次建模

通过对ATM网络视频业务传输性能及其建模分析,针对高运动性（即全动态）视频源的建模,给出基于块的MPEG运动估计算法,提出一种非线性模型。基于自回归在GOP层对MPEG视频流进行二次建模。仿真表明,该文提出的NAR模型能准确预测具有适度运动性的实际MPEG流,对具有高运动性的流在不同的负荷和缓冲器的条件下提供可接受的预测。     

基于改进LS-SVM的来波方位估计

提取已知方位信号的协方差矩阵的上三角部分作为样本特征,构建方位估计模型。针对最小二乘支持向量机最优参数难以选定的问题,采用实值编码的启发式遗传算法,以模型的来波方位估计性能为目标,实现基于高斯核函数的SVM参数优化,提高了来波方位估计精度。实验结果表明,该方法估计精度较高、实时性好,在无线电测向领域具有广阔应用前景。     

全功能点在SOA系统规模估算中的应用

规模估算是项目估算的基础,然而针对面向服务体系结构(SOA)系统的规模估算没有一个有效的解决方案。为此,探讨全功能点方法在估算SOA系统规模中的应用,在研究全功能点方法及业务流程建模标记的基础上,定义全功能点主要元素和业务流程建模标记主要元素的映射规则,给出估算步骤,同时以一个实例说明估算过程。     

极化分布源模型及角度估计

通过对“分布源是在一定空间分布的多个点源信号的叠加”的分析，提出了极化分布源模型和一阶近似的极化分布源模型。对极化分布源模型，为减少噪声子空间拟合算法(NSF)的搜索空问雏数，文中提出只搜索角度空间求解到达角，对极化参数通过求解线性方程组获得；对一阶近似的极化分布源模型，利用旋转予空间不变(ESPRIT)类算法求解到达角，极化参数同样通过求解线性方程组获得。仿真结果表明：极化的引入对NSF的性能有很大提高，以及一阶近似模型对角度分布的盲性。     

一种新型全搜索运动估计IP核设计

为了降低全搜索运动估计算法带来的巨大计算量,提高运动估计计算速度,提出了一种新型的用于全搜索运动估计硬件结构。该硬件结构能实时地通过全搜索运动估计来搜索每个像素块最佳的匹配运动向量,并通过改进搜索窗缓存,获得了较高的运算速度增益并有效地降低了电路功耗。