An Efficient One-Arrow-Two-Hawks Strategy Achieves High Efficiency and Stable Batch Variance for Benzodifuran-based Polymer Solar Cells

With the development of organic solar cells (OSCs), the high-performance and stable batch variance are becoming a new challenge for designing polymer donors. To obtain high photovoltaic performance, adopting polymers with high molecular weight as donors is an ordinary strategy. However, the high molecular weight need to subtly control the reaction time and state, inevitably caused batch-to-batch variations. Herein, a strategy of steric effect is applied to benzodifuran (BDF)-based polymer by introducing different positions of Cl atom, producing two polymers PBDFCl-1 and PBDFCl-2. The more twisted side chains conformation not only achieve the control of moderate molecular weight for PBDFCl-2, but also easily form molecular stacking through adopting BDF unit and maintain sufficient polymeric crystallinity. Due to the optimized stacking mode and good blend miscibility, PBDFCl-2-based device exhibitsa more elegant power conversion efficiency (PCE) of 17.00% compared to PBDFCl-1-based device. This is the highest efficiency record for BDF-based binary OSCs. Meanwhile, the PCE device variation of the different molecular weights for PBDFCl-2 is little, indicating the reduction of the batch variation. Therefore, smartly using steric effect of Cl atom in strong crystalline BDF unit can form efficient molecular stacking regulations and realize the coordination of high-performance and stable batch variance.     

空域反转阵导向最小方差波束形成

文章研究了基于空域反转阵（Spatial Reversion Array,SRVA）的导向最小方差（Steered Minimum Variance,STMV）波束形成方法。根据空域反转阵的原理将均匀线阵列的快拍进行空间反转,再与原阵列快拍卷积,得到孔径扩大近一倍的空域反转阵,提高阵列性能。将同样的方法用于构造空域反转阵的导向向量,实现其导向最小方差（SRVA-STMV）波束形成。仿真和海试试验结果表明,相较于常规的STMV波束形成,空域反转阵STMV波束形成能够获得更窄的主瓣、更低的旁瓣、更高的输出信干噪比以及更好的多目标分辨能力。     

非线性广义最小方差控制律综述

如何设计简单的控制策略对复杂非线性系统进行控制是控制界还未解决的难题．非线性广义最小方差控制律的提出使得非线性控制器的设计可以基于更为一般的非线性模型，并且控制器易于实现．整个系统包含时滞环节，稳定的非线性输入子系统和一个可以用多项式或者状态空间描述的子系统．通过最小化由误差加权项、状态加权项和输入加权项组成的信号的方差得到优化控制器．在系统为开环稳定的情况下，可用史密斯预估器进行控制．本文首先介绍了非线性广义最小方差控制的发展进程，然后综述了基于状态空间和多项式描述的系统的非线性广义最小方差控制器的设计以及其现状和今后的发展方向．     

炮控系统的最小方差控制

基于自适应控制原理,将最小方差控制算法应用于炮控系统数字化控制,对行进间火炮在路面谱干扰作用下的响应进行预报．提出了对某坦克炮控系统结构的改进方案．仿真结果表明,这种基于预测的控制算法简单易行,运算速度快,可提高系统控制的有效性     

On minimum class locality preserving variance support vector machine

In this paper, a so-called minimum class locality preserving variance support machine (MCLPV_SVM) algorithm is presented by introducing the basic idea of the locality preserving projections (LPP), which can be seen as a modified class of support machine (SVM) and/or minimum class variance support machine (MCVSVM). MCLPV_SVM, in contrast to SVM and MCVSVM, takes the intrinsic manifold structure of the data space into full consideration and inherits the characteristics of SVM and MCVSVM. We discuss in the paper the linear case, the small sample size case and the nonlinear case of the MCLPV_SVM. Similar to MCVSVM, the MCLPV_SVM optimization problem in the small sample size case is solved by using dimensionality reduction through principal component analysis (PCA) and one in the nonlinear case is transformed into an equivalent linear MCLPV_SVM problem under kernel PCA (KPCA). Experimental results on real datasets indicate the effectiveness of the MCLPV_SVM by comparing it with SVM and MCVSVM.     

Minimum‐variance control of astronomical adaptive optic systems with actuator dynamics under synchronous and asynchronous sampling

Adaptive optic (AO) systems are now routinely used in ground‐based telescopes to counter the effects of atmospheric turbulence. A deformable mirror (DM) generates a correction wavefront, which is subtracted from the turbulent wavefront using measurements of the residual phase provided by a wavefront sensor (WFS). Minimizing the variance of the residual phase defines a sampled data control problem combining a continuous time minimum‐variance (MV) performance criterion with a discrete‐time controller. For a fairly general class of linear time‐invariant DM and turbulence WFS models, this control problem can be transformed into an equivalent discrete‐time LQ optimization problem involving a set of (discrete‐time) control‐sufficient statistics of the incoming continuous‐time turbulence. This paper shows how to constructively solve this MV problem in the presence of DM's dynamics, starting from continuous‐time models of DM and turbulence. This result is extended to the case of asynchronous DM/WFS sampling. An illustrative application to optimal control of tip‐tilt turbulent modes for the European extremely large telescope in the presence of first‐order DM's dynamics is presented. Copyright © 2010 John Wiley & Sons, Ltd.     

磁能驱动微型泵的性能研究

在电磁驱动原理的基础上,设计并研制了一种磁能驱动的微型泵。微型泵的整体尺寸约为Φ11mm×4mm,腔室半径为5mm,深2mm。利用方差分析方法对实验数据进行了检验,验证了前期微型泵研究中获得的性能参数的正确性。为了进一步缩小微型泵体积、简化控制方式和外围电路,针对微型泵的能源部分,开展了单双电源的对比实验研究,并获得了较好的实验结果。     

基于鲁棒相关向量机的转炉炼钢终点预报模型

针对传统相关向量机在训练过程中易受异常点影响的问题,提出了一种鲁棒相关向量机模型,并将其应用于转炉炼钢终点碳含量和温度的预报.通过为每一个训练样本设定独立的噪声方差系数,并使其在训练过程中随模型预测误差的增大而逐渐减小来降低异常点的影响,同时依据贝叶斯证据框架给出了模型超参数的迭代计算公式,进行参数的优化.使用标准测试数据和转炉炼钢实际生产数据进行仿真,结果表明本文模型具有较好的预报精度和鲁棒性.     

小波去噪在智能引线键合机图像处理中的应用

针对小波去噪中硬阈值法和软阈值法存在的缺陷,提出了一种新的多尺度自适应阈值选择算法,该方法根据小波变换的特点和噪声信号的3σ,准则,对于不同的小波系数乘以一个与自身小波系数相关的降噪因子.在现有的图像去噪评估算法的基础上,提出了基于图像平滑度和匹配度的去噪效果评估算法.实验结果表明:多尺度自适应阈值选择算法能有效去除图...     

A two-asset stochastic model for long-term portfolio selection

In mean–variance (M–V) analysis, an investor with a holding period [0,T] operates in a two-dimensional space—one is the mean and the other is the variance. At time 0, he/she evaluates alternative portfolios based on their means and variances, and holds a combination of the market portfolio (e.g., an index fund) and the risk-free asset to maximize his/her expected utility at time T. In our continuous-time model, we operate in a three-dimensional space—the first is the spot rate, the second is the expected return on the risky asset (e.g., an index fund), and the third is time. At various times over [0,T], we determine, for each combination of the spot rate and expected return, the optimum fractions invested in the risky and risk-free assets to maximize our expected utility at time T. Hence, unlike those static M–V models, our dynamic model allows investors to trade at any time in response to changes in the market conditions and the length of their holding period. Our results show that (1) the optimum fraction y*(t) in the risky asset increases as the expected return increases but decreases as the spot rate increases; (2) y*(t) decreases as the holding period shortens; and (3) y*(t) decreases as the risk aversion parameter-γ is larger.