基于网格自适应加密技术的 GPU 高效运行实现研究

针对传统解算器未能实现 GPU 上运行网格自适应加密过程，造成 GPU 与 CPU 之间繁琐的数据交换的问题，本文发展优化了一种 GPU 加速的基于非结构自适应加密网格的解算器 VA2DG。利用加密网格表的方式实现网格自适应加密过程在 GPU 上高速运行，并通过原子操作并行生成网格加密表，对废弃的网格及时回收，节约存储空间，加快运行速度。     

基于多主体建模的社会化养老形成分析

在国家大力推进社会化养老服务体系不断发展的背景下,研究了社会化养老的形成.根据效用最大化原则,利用多主体建模方法,构建了一个包含政府、养老机构、家庭三大类主体的社会化养老仿真模型,模拟了社会化养老行为这一宏观社会经济现象的形成.仿真结果表明:就业率和工资水平对社会化养老的形成有显著影响;政府补贴对社会化养老有效需求的产生影响不显著,而对服务供给产生较大影响;而老年人的财富水平、对父母的关爱水平、对下一代资金投入和对下一代关爱水平对社会化养老的形成影响不显著.     

天宫一号基于控制力矩陀螺的智能多模自适应姿态控制系统设计与验证

天宫一号是目前我国在轨运行的体积最大、重量最重的载人航天器.它具有变构型、变参数的特性,采用控制力矩陀螺系统和喷气推进系统实现高精度、高稳定度姿态控制.本文通过对天宫一号控制对象参数缓变和跳变相结合特点的分析,规划了高可靠灵活的控制策略,设计了智能多模自适应姿态控制系统.利用智能控制中规则集设定多模自适应控制的指标切换函数分配,利用多模自适应控制算法建立多模型控制器实现不同控制对象,不同控制任务的姿态控制.天宫一号通过地面测试和物理仿真试验,最后发射在轨运行,与神舟八号、神舟九号、神舟十号载人飞船圆满完成交会对接任务,充分验证了姿态控制系统设计的正确性和有效性.该设计方法在解决大型航天器变构型、变参数组合体姿态控制方面有突出优点,在未来的载人航天领域空间站建设具有应用前景.     

Long Memory of Financial Time Series and Hidden Markov Models with Time‐Varying Parameters

Hidden Markov models are often used to model daily returns and to infer the hidden state of financial markets. Previous studies have found that the estimated models change over time, but the implications of the time‐varying behavior have not been thoroughly examined. This paper presents an adaptive estimation approach that allows for the parameters of the estimated models to be time varying. It is shown that a two‐state Gaussian hidden Markov model with time‐varying parameters is able to reproduce the long memory of squared daily returns that was previously believed to be the most difficult fact to reproduce with a hidden Markov model. Capturing the time‐varying behavior of the parameters also leads to improved one‐step density forecasts. Finally, it is shown that the forecasting performance of the estimated models can be further improved using local smoothing to forecast the parameter variations. Copyright © 2016 John Wiley & Sons, Ltd.     

建筑间行人高度处的风环境设计

为使用简单的方法对居住区的风环境进行评价,采用CFD软件模拟,运用正交试验的方法选取模拟的工况.根据模拟的结果,推导出建筑尺寸、建筑间距与建筑通道间行人高度处最大风速比的函数关系式,并且进行实例验证.验证表明:该方法简单可行,对建筑师进行风环境设计具有较好的辅助作用.     

Method of adaptive PLL bandwidth adjustment without phase slipping

In a system based on the phase lock loop（PLL）, a trade-off must be made between the tracking precision and the dynamic performance if constant parameters are adopted. To overcome this drawback, a new method called no phase slipping adaptive bandwidth（NPS-AB） is proposed, which can adjust the loop bandwidth adaptively for different working conditions. As a result, both the tracking precision and the dynamic performance can be achieved concurrently. NPS-AB has two features to keep the loop stable： one is the capability of quick response to dynamics; the other is a series of additional constraints when the bandwidth is switched. Compared with other methods, there is no phase slipping during the adjustment process for NPS-AB. The phase integer ambiguity can be avoided and the phase value is kept valid. It is meaningful for carrier ranging systems. Simulation results show that NPS-AB can deal with sudden dynamics and keep the pseudo-range value stable in the entire dynamic process.     

高速铁路路堤传递地基差异沉降特性及控制限值研究

为研究高速铁路地基差异沉降在路堤中的传递扩散特性,运用有限元方法,分析了路基在小变形条件下地基差异沉降与路基面不均匀变形的映射关系,并在得到土工离心模型试验校正的基础上,讨论了地基差异沉降模式、路堤高度等因素对路基面不均匀变形的影响规律.研究表明:地基差异沉降在路堤中的扩散程度随地基差异沉降渐变段长度与路堤高度比值的增大而减小,比值大于3~5以后,地基差异沉降与路基面不均匀变形具有良好的一致性;路基面不均匀变形与地基差异沉降呈正相关性,并随路堤高度、地基差异沉降渐变段长度的增加而减小;基于路基面不均匀变形限值提出了地基差异沉降控制标准,丰富了高速铁路路基沉降变形控制技术指标体系.     

Underdetermined DOA estimation and blind separation of non-disjoint sources in time-frequency domain based on sparse representation method

This paper deals with the blind separation of nonstation-ary sources and direction-of-arrival （DOA） estimation in the under-determined case, when there are more sources than sensors. We assume the sources to be time-frequency （TF） disjoint to a certain extent. In particular, the number of sources presented at any TF neighborhood is strictly less than that of sensors. We can identify the real number of active sources and achieve separation in any TF neighborhood by the sparse representation method. Compared with the subspace-based algorithm under the same sparseness assumption, which suffers from the extra noise effect since it can-not estimate the true number of active sources, the proposed algorithm can estimate the number of active sources and their cor-responding TF values in any TF neighborhood simultaneously. An-other contribution of this paper is a new estimation procedure for the DOA of sources in the underdetermined case, which combines the TF sparseness of sources and the clustering technique. Sim-ulation results demonstrate the validity and high performance of the proposed algorithm in both blind source separation （BSS） and DOA estimation.     

基于自适应遗传算法的超平面分类及遥感应用

智能分类算法是遥感影像分类研究的热点,遗传算法作为一种智能全局优化技术在遥感影像分类中具有良好应用前景.针对现有多光谱遥感影像分类方法的不足,提出了基于自适应遗传算法的超平面分类方法(hyper plane-adaptive genetic algorithm,HP-AGA)并应用于遥感影像分类,该方法利用神经网络中的神经元激活函数Sigmoid函数,对遗传算法中交叉率、变异率进行非线性自适应性调整,不再需要反复训练遗传参数,同时利用快速全局寻优特点,确定分类超平面的各个位置参数,从而获取最佳分类超平面集进行分类.多光谱遥感影像分类方法的应用实验表明,基于自适应遗传算法的超平面遥感分类方法能更快、更稳定地收敛到全局最优解,具有更好的效率及鲁棒性,并能取得优于简单遗传超平面分类算法及传统分类方法的分类精度.