能量有效的NOMA多用户-多信道匹配算法

针对非理想信道状态信息(channel state information, CSI)下面向海量用户的无线资源高效分配难题,通过引入非正交多址(non-orthogonal multiple access, NOMA)技术提出了一种能量有效的多用户-多信道匹配方案。首先,考虑用户中断概率约束,建立以最大化系统能量效率为目标的非理想CSI蜂窝下行NOMA系统信道和功率联合分配优化问题;然后,将建立的含概率约束的优化问题转化为非概率约束优化问题,并从中解耦出用户-信道匹配优化问题;最后,将面向能量效率的NOMA用户-信道匹配优化问题映射为婚姻匹配问题,进而提出一种高效低复杂度的双边匹配算法实现了多用户-多信道的动态匹配。仿真结果表明,提出的匹配算法性能优于传统匹配算法,能够提供更高的系统能效、实现更低的用户中断概率且收敛速度更快。     

Compressive sensing based multiuser detector for massive MBM MIMO uplink

Media based modulation(MBM)is expected to be a prominent modulation scheme,which has access to the high data rate by using radio frequency(RF)mirrors and fewer transmit antennas.Associated with multiuser multiple input multiple output(MIMO),the MBM scheme achieves better performance than other conventional multiuser MIMO schemes.In this paper,the massive MIMO uplink is considered and a conjunctive MBM transmission scheme for each user is employed.This conjunctive MBM transmission scheme gathers aggregate MBM signals in multiple continuous time slots,which exploits the structured sparsity of these aggregate MBM signals.Under this kind of scenario,a multiuser detector with low complexity based on the compressive sensing(CS)theory to gain better detection performance is proposed.This detector is developed from the greedy sparse recovery technique compressive sampling matching pursuit(CoSaMP)and exploits not only the inherently distributed sparsity of MBM signals but also the structured sparsity of multiple aggregate MBM signals.By exploiting these sparsity,the proposed CoSaMP based multiuser detector achieves reliable detection with low complexity.Simulation results demonstrate that the proposed CoSaMP based multiuser detector achieves better detection performance compared with the conventional methods.     

基于模型预测控制的轮式移动机器人轨迹规划

针对轮式移动机器人(Wheeled Mobile Robot-WMR)自身欠驱动的特点,并考虑到实际工作时的各种约束和限制,提出了一种基于模型预测控制(Model Predictive Control -MPC)的多约束轨迹规划方法。可以对车体自身的运动学约束、物理约束以及避障等约束进行集中有效的处理,可以生成符合车体自身模型特点并满足各种约束的可行轨迹,充分保证了轮式移动机器人自主行驶的可行性,安全性,高效性。仿真结果充分验证了该方法的有效性。     

多精英采样与个体差分学习的分布估计算法

提出了基于多精英采样和差分搜索的分布估计算法EDA-M/D (Estimation distribution algorithm based on multiple elites sampling and individuals differential search)。EDA-M/D利用多精英个体独立采样生成子代来提升算法全局搜索能力,利用精英群体分布的σ²约束采样半径,实现种群从全局搜索逐步过度到局部搜索。当精英群体停滞时,劣势个体借助精英群体的μ和种群历史最优解进行差分搜索,帮助种群跳出局部最优解。通过多精英采样与差分搜索的自适应协同实现种群宏观信息与个体微观信息的有机融合。实验结果表明EDA-M/D在稳定性和搜索能力方面均表现出明显的优势。     

考虑多维修台异步单重休假的温贮备冗余系统可靠性模型

本文针对多维修台保障多个系统时维修力量调度规律对系统稳态可靠性的影响,引入多维修台异步单重休假策略,以包含c个维修台的温贮备冗余系统为研究对象,根据维修台所处的维修、休假、空闲3种状态将系统整体工作情况进行状态划分,建立系统状态转移矩阵。引入Phase type分布描述系统工作部件、贮备部件寿命以及维修台维修时间、休假时间、空闲时间等随机变量,构建考虑多维修台异步单重休假的温贮备冗余系统可靠性模型,得出系统稳态可用度和稳态忙期维修台数量等指标的解析表达式。最后利用算例对模型的适用性以及准确性进行分析,并探讨了维修台工作速率和系统可靠性之间的关系。     

基于聚类方法和神经网络的非线性系统多模型自适应控制

针对具有参数跳变的非线性系统,联合聚类算法和神经网络提出新的多模型自适应控制方法。首先对系统的输入输出数据进行模糊聚类,然后基于递推最小二乘法建立多个固定模型。为提高系统的暂态性能,同时建立两个自适应模型,并在此基础上设计鲁棒自适应控制器。此外,为了补偿系统的非线性部分,建立非线性预测模型,并设计非线性神经网络自适应控制器。所提方法可使控制切换系统具有稳定性保证。最后,通过性能指标对控制器进行平滑切换。仿真结果表明,所提方法能够保证系统具有良好的控制性能。     

The US Dollar/Euro Exchange Rate: Structural Modeling and Forecasting During the Recent Financial Crises

The paper investigates the determinants of the US dollar/euro within the framework of the asset pricing theory of exchange rate determination, which posits that current exchange rate fluctuations are determined by the entire path of current and future revisions in expectations about fundamentals. In this perspective, we innovate by conditioning on Fama–French and Carhart risk factors, which directly measures changing market expectations about the economic outlook, on new financial condition indexes and macroeconomic variables. The macro‐finance augmented econometric model has a remarkable in‐sample and out‐of‐sample predictive ability, largely outperforming a standard autoregressive specification. We also document a stable relationship between the US dollar/euro Carhart momentum conditional correlation (CCW) and the euro area business cycle. CCW signals a progressive weakening in economic conditions since June 2014, consistent with the scattered recovery from the sovereign debt crisis and the new Greek solvency crisis exploded in late spring/early summer 2015. Copyright © 2016 John Wiley & Sons, Ltd.     

An efficient identity-based key agreement protocol in a multiple PKG environment

Identity-based key agreement protocol affords a natural way to combine the participant’s identity with its public key.However,most of them just consider the key agreement in a single private key generator(PKG)environment.In addition,the existing key agreement protocols have a great computing overhead for mobile computing which is more and more popular today.This paper proposes a new identity based key agreement protocol.With the help of mathematical tools,we make our protocol applied in multiple PKG environment.It also satisfies all the security properties which is set for key agreement protocol.Moreover,some of its time-consuming operations can be delivered to untrusted public computation resources,so its computing complexity can be greatly reduced.     

基于结构纹理分解和多重网格的光流估计算法

分别针对光流计算对光照变化敏感以及运算复杂度高、迭代收敛缓慢的问题,使用一种基于ROF(Rudin-Osher-Fatemi)模型的结构纹理分解(STD)技术得到对光照变化不敏感的纹理图估计光流场,消除了光照变化产生的负面影响,并提出一种基于多重网格方法的分层处理策略.将光流计算的迭代过程分散在一系列粗细不同的网格上,在细网格上消除高频误差,在粗网格上消除低频误差,以达到加速收敛、提高光流计算速度的目的.实验结果表明,STD过程抑制了光照变化导致的负面影响,提高了光流估计精度.多重网格算法在保持优化精度的前提下,显著提高了光流计算的实时性.     

基于顾客偏好的瓶装水外观感性质量评价

从感性质量评价的角度提取13个感性质量评价词对,用于全面且针对性地评价顾客对瓶装水的偏好.以"想购买"为综合感性提取瓶装水的感性质量评价要素,结合聚类分析等方法确定7种代表性样本.基于语义差异法构建瓶装水感性质量评价量表,运用多元回归模型分析建立顾客偏好与感性评价词对之间的关系模型.关系模型解决了如何识别顾客偏好和感性质量需求,以及如何将这些偏好和需求整合到产品设计过程中的问题.