Mean Square Heun’s Method Convergent for Solving Random Differential Initial Value Problems of First Order

This paper deals with the construction of Heun’s method of random initial value problems. Sufficient conditions for their mean square convergence are established. Main statistical properties of the approximations processes are computed in several illustrative examples.

Fast impurity solver for dynamical mean field theory based on second order perturbation around the atomic limit

This paper proposes an impurity solver for the dynamical mean field theory （DMFT） study of the Mott insulators, which is based on the second order perturbation of the hybridization function. After careful benchmarking with quantum Monte Carlo results on the anti-ferromagnetic phase of the Hubbard model, it concludes that this impurity solver can capture the main physical features in the strong coupling regime and can be a very useful tool for the LDA （local density approximation） ＋ DMFT studies of the Mort insulators with long range order.

On the Mean Value of the Infinite Order Legendre Series

In this paper, we studies the relations between the mean value and the maximun norm of the infinite order entire functions which defined by legendre series. We obtained that if f(z) is an infinite order entire function with a positive exponenatial lower order. then loaM (α) ～logMδ(α) ～ logMδ(α) (α→+∞).

ORDER OF MEAN APPROXIMATION BY MIXED QUASI HERMITE-FEJER INTERPOLATION

In this paper we introduce a new kind of the mixed Hermite--Fejér interpolation with boundary condi- tions and obtain the mean approximation order.Our results include a new theorem of Varma and Prasad.Be- sides,we also get some other results about the mean approximation.

Efficient Mean Estimation in Log-normal Linear Models with First-order Correlated Errors

In this paper, we propose a log-normal linear model whose errors are first-order correlated, and suggest a two-stage method for the efficient estimation of the conditional mean of the response variable at the original scale. We obtain two estimators which minimize the asymptotic mean squared error （MM） and the asymptotic bias （MB）, respectively. Both the estimators are very easy to implement, and simulation studies show that they are perform better.

基于k-means聚类的无导词义消歧

无导词义消歧避免了人工词义标注的巨大工作量,可以适应大规模的多义词消歧工作,具有广阔的应用前景。这篇文章提出了一种无导词义消歧的方法,该方法采用二阶context构造上下文向量,使用k-means算法进行聚类,最后通过计算相似度来进行词义的排歧.实验是在抽取术语的基础上进行的,在多个汉语高频多义词的两组测试中取得了平均准确率82·67%和80·87%的较好的效果。

基于Canopy和k-means算法的订单分批优化

文章针对物流企业的订单分批问题,提出了改进的Canopy-k-means算法。该算法是采用Canopy算法依据最大最小原则生成初始聚类中心,并使用k-means聚类算法对其进行优化获取分批结果的。此外,文章针对不同规模的订单数据集,比较了该算法和先来先服务(first come first served,FCFS)、k-means以及Canopy-k-means算法的实际效果,实验结果表明:该算法可以避免k-means算法中k值选取的盲目性,同时可以有效地提高分拣效率以及降低分拣批次。

基于分子晶体序参数与K-means聚类的TNT晶型转化有限温度弦研究

为揭示炸药转晶稀有事件的分子机制,分别构建了基于键距离(即分子间距离)与键取向和分子取向的两类序参数,借助基于Euclidean距离和密度权重的K-means聚类算法进行了序参数的增强采样。结果表明,基于分子晶体序参数与K-means聚类的增强采样改进了稀有事件常规有限温度弦方法,使自由能快速收敛。将该方法用于TNT晶型转化的研究,避免了分子晶体序参数“维数爆炸”,获得了平均力势面,验证了基于分子晶体序参数与K-means聚类有限温度弦方法在炸药晶型转化研究中的有效性,探明了TNT(O)与TNT(M)之间界面诱导、局部引发、多核非同步生长的晶型转变过程。

Adaptive digital self-interference cancellation based on fractional order LMS in LFMCW radar

Adaptive digital self-interference cancellation(ADSIC)is a significant method to suppress self-interference and improve the performance of the linear frequency modulated continuous wave(LFMCW)radar.Due to efficient implementation structure,the conventional method based on least mean square(LMS)is widely used,but its performance is not sufficient for LFMCW radar.To achieve a better self-interference cancellation(SIC)result and more optimal radar performance,we present an ADSIC method based on fractional order LMS(FOLMS),which utilizes the multi-path cancellation structure and adaptively updates the weight coefficients of the cancellation system.First,we derive the iterative expression of the weight coefficients by using the fractional order derivative and short-term memory principle.Then,to solve the problem that it is difficult to select the parameters of the proposed method due to the non-stationary characteristics of radar transmitted signals,we construct the performance evaluation model of LFMCW radar,and analyze the relationship between the mean square deviation and the parameters of FOLMS.Finally,the theoretical analysis and simulation results show that the proposed method has a better SIC performance than the conventional methods.

Mean Square Convergent Finite Difference Scheme for Stochastic Parabolic PDEs

Stochastic partial differential equations (SPDEs) describe the dynamics of stochastic processes depending on space-time continuum. These equations have been widely used to model many applications in engineering and mathematical sciences. In this paper we use three finite difference schemes in order to approximate the solution of stochastic parabolic partial differential equations. The conditions of the mean square convergence of the numerical solution are studied. Some case studies are discussed.

一种用于解调失真QAM信号的改进K-means聚类算法

在短距离无线通信中,无线节点或移动终端通常有低成本、小体积、低功耗的要求,因此无法使用复杂的预失真或补偿电路克服功放的非线性影响,这是无线节点或移动终端在上行链路中难以使用高阶QAM调制的重要原因之一。基于QAM矩形星座的特点,提出了一种K-means聚类的改进算法作为中央基站节点的高阶QAM解调算法。在发送信号受到较严重的功放非线性失真时,所提改进算法解调性能更优,算法复杂度更低。

Representations for reliability functions of conditional coherent systems with INID components and ordered properties

This paper presents several useful mixture representations for the reliability function of the residual live of a coherent system with independent but non-identically distributed components. These presentations are based on order statistics, signatures and mean reliability functions. We then discuss some stochastic comparisons of residual lives between two systems based on the stochastic ordering of coefficient vectors （or components） of the two systems. These results form nice extensions of some known results for the case of independent and identically distributed components.

Random Crank-Nicolson Scheme for Random Heat Equation in Mean Square Sense

The goal of computational science is to develop models that predict phenomena observed in nature. However, these models are often based on parameters that are uncertain. In recent decades, main numerical methods for solving SPDEs have been used such as, finite difference and finite element schemes [1]-[5]. Also, some practical techniques like the method of lines for boundary value problems have been applied to the linear stochastic partial differential equations, and the outcomes of these approaches have been experimented numerically [7]. In [8]-[10], the author discussed mean square convergent finite difference method for solving some random partial differential equations. Random numerical techniques for both ordinary and partial random differential equations are treated in [4] [10]. As regards applications using explicit analytic solutions or numerical methods, a few results may be found in [5] [6] [11]. This article focuses on solving random heat equation by using Crank-Nicol- son technique under mean square sense and it is organized as follows. In Section 2, the mean square calculus preliminaries that will be required throughout the paper are presented. In Section 3, the Crank-Nicolson scheme for solving the random heat equation is presented. In Section 4, some case studies are showed. Short conclusions are cleared in the end section.

基于改进K-Means聚类电商物流仓储拣选优化策略

拣选作业是电商物流仓储作业中最核心的部分。由于电子商务环境下的订单具有多品种、少批量,且需求时间随机的特点,单纯按照先到先服务的拣选策略不仅难以保障订单履行的时效性,还会造成拣选效率低下,拣选成本居高不下等问题。文中基于节约算法的思想对K-Means聚类算法进行改进,以减少移动货架搬运次数为目标函数,计算两两拣选波次的耦合度,根据耦合度的大小对波次单进行分类,然后运用K-Means聚类算法建立模型并求解,得出波次单的拣选顺序。最后通过系统仿真验证,证实此方法能够有效优化拣选顺序,并提升拣选效率。

一种适用于复杂电网下的高精度锁相环

针对现有并网逆变器在电网电压谐波复杂的情况下难以精确锁定电压频率和相位的问题,结合传统锁相环结构与自适应算法的理论提出一种高精度的锁相方法。依据对传统锁相环在复杂电网下的弊端分析,确定了锁相环采用传统低通滤波器、带通滤波器时的滤波效果与延时的矛盾关系。根据最小均方算法的高自适应特性与快速跟踪特点,结合锁相环中坐标变换公式,确定算法的输入输出以及权重矩阵,构建基于派克变换的最小均方算法矩阵模型。通过将所需的电压正序分量设置为不断更新的权重矩阵来进行高精度的滤波,同时通过引入均方瞬时误差和自相关估计均值来进行变步长控制,提高滤波更新速度,以适用于复杂程度不确定的电网电压进行自适应滤波锁相。对仿真和样机实验的结果表明:采用基于派克变换的最小均方算法的改进型双二阶广义积分锁相方法,可以在不降低动态响应速度的前提下,提高锁相环的滤波效果,进而提高并网逆变器在电网畸变严重场景下锁定电压频率和相位的跟踪精度。

“养民”:构建天下秩序的路径指向——以丘濬《大学衍义补》为中心的考察

明代丘濬以“治国平天下”为中心,探讨如何构建天下秩序,写成了《大学衍义补》。在该书中,丘濬以“三代圣王”为典范,坚守以“养民”为本的仁政思想,极力要求后世君主效法尧舜,以“诚”待民,尽职“养民”,力行“仁义之政”,再现“尧舜之治”。丘濬一再强调,“养民”是君主施行“仁政”的真正体现,只有将“仁政”聚焦到“养民”上,才能真正构建天下秩序,成为像尧舜一样的“圣君”。在丘濬看来,“养民”是构建天下秩序的具体路径,也是唯一路径,君主只有施行“养民”之政且“兼爱华夷之民”,才能真正实现“华夷一家”的大同理想。

自适应分数阶偏微分方程修正模型的能量泛函及Euler-Lagrange方程研究

首先对分数阶微分方程进行构建,结合全变分项,提出了修正的自适应分数阶偏微分方程模型。研究首先确定出分数阶偏分去噪模型的最优分数阶数,当分数阶次为1.8时,峰值信噪比和结构相似度达到33.12和0.874,均方根误差降低至5.62。然后将研究提出的模型与全变分模型、分数阶偏分去噪模型等在图像上进行对比实验,研究提出的模型在峰值信噪比、结构相似度上达到最高,分别为29.045与0.839,均方根误差为9.427,表明模型能够抑制阶梯效应,具有优越的去噪性能。

联合优化无人机位置和功率的用户吞吐量最大化方法

因移动便捷、高视距通信概率等优势,无人机(Unmanned Aerial Vehicle,UAV)在应急通信中发挥重要作用。为此,提出联合优化UAVs位置和传输功率的吞吐量最大化(Joint optimization of UAV 3-D Position and Transmit powers for throughput Maximization,JPTM)方法,进而提高地面用户的吞吐量。先构建一个联合UAVs三维位置和传输功率的优化问题。考虑到该问题的非凸优化性,将其分解为两个子问题。用Mean-Shift算法求解第一个问题,获取最优的UAVs水平位置。采用分而治之策略,将第二个子问题再分解,并利用一阶泰勒级数展开对两个子问题进行近似处理,形成标准凸化问题,然后利用CVX工具求解。性能分析表明,相比于基于圆形堆积理论部署UAVs策略(Circle Packing Theorem-based Deployment,CPTD)和基于多变量仿真的能效UAVs部署策略(Energy-Efficient Variable simultaneous Deployment,EEVD)算法,JPTM算法提高了地面用户的吞吐量。

基于EOE_LMD和阶次跟踪分析的变转速轴承故障诊断

振动信号分析是轴承故障诊断中的重要技术手段之一。变转速工况下的滚动轴承振动信号是典型的非平稳信号,并且在转频变化较小的工况中还存在噪声干扰的问题,使传统的时频分析技术难以应用。为解决该问题,提出了一种基于经验最优包络(empirical optimal envelope,EOE)的局部均值分解(local mean decomposition,LMD)和采用分段线性插值的计算阶次跟踪(computing order tracking,COT)算法相结合的故障诊断方法。首先,确定低通滤波器的截止频率和滤波阶数,对滚动轴承振动信号进行滤波,并对滤波后的包络信号进行COT,以获得角域平稳信号。然后,利用EOE_LMD对重采样后的平稳信号进行处理,得到若干乘积函数(product function,PF)分量。最后,通过计算各分量的信息熵和相关系数,选取合适的分量进行阶次分析,以判断变转速滚动轴承的故障类型。结果表明,该方法可以消除转速波动对故障特征提取的影响,在不同转速变化条件下对滚动轴承具有良好的故障诊断能力。

基于二阶混联灵敏度矩阵的ECT图像重建

电容层析成像技术求解图像重建问题属于非线性问题。在灵敏度矩阵的推导过程中,通常只保留灵敏度系数的线性部分,但是被忽略的非线性部分同样包含重要的成像信息。为了提高图像重建精度,基于二阶灵敏度系数的数学定义,结合模糊C-均值聚类算法和电场中心线理论,建立了二阶混联灵敏度矩阵,并将矩阵引入到Landweber算法中,提出了二阶Landweber算法;最后,进行仿真和静态实验,并与传统的Tikhonov算法和一阶Landweber算法进行对比,结果表明,二阶混联灵敏度矩阵可以提高图像重建精度。