Three-class classification models of logS and logP derived by using GA–CG–SVM approach

In this investigation, three-class classification models of aqueous solubility (logS) and lipophilicity (logP) have been developed by using a support vector machine (SVM) method combined with a genetic algorithm (GA) for feature selection and a conjugate gradient method (CG) for parameter optimization. A 5-fold cross-validation and an independent test set method were used to evaluate the SVM classification models. For logS, the overall prediction accuracy is 87.1% for training set and 90.0% for test set. For logP, the overall prediction accuracy is 81.0% for training set and 82.0% for test set. In general, for both logS and logP, the prediction accuracies of three-class models are slightly lower by several percent than those of two-class models. A comparison between the performance of GA–CG–SVM models and that of GA–SVM models shows that the SVM parameter optimization has a significant impact on the quality of SVM classification model. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users. Hui Zhang and Ming-Li Xiang are contributed equally.     

Localization for a Matrix-valued Anderson Model

We study localization properties for a class of one-dimensional, matrix-valued, continuous, random Schrödinger operators, acting on $L^2(\mathbb R)\otimes \mathbb C^NWe study localization properties for a class of one-dimensional, matrix-valued, continuous, random Schr?dinger operators, acting on , for arbitrary N ≥ 1. We prove that, under suitable assumptions on the Fürstenberg group of these operators, valid on an interval , they exhibit localization properties on I, both in the spectral and dynamical sense. After looking at the regularity properties of the Lyapunov exponents and of the integrated density of states, we prove a Wegner estimate and apply a multiscale analysis scheme to prove localization for these operators. We also study an example in this class of operators, for which we can prove the required assumptions on the Fürstenberg group. This group being the one generated by the transfer matrices, we can use, to prove these assumptions, an algebraic result on generating dense Lie subgroups in semisimple real connected Lie groups, due to Breuillard and Gelander. The algebraic methods used here allow us to handle with singular distributions of the random parameters.      

Photoproduction of the $\Theta^+$ and its vector and axial-vector structure

We present recent investigations on the vector and axial-vector transitions of the baryon antidecuplet within the framework of the self-consistent SU（3） chiral quark-soliton model, taking into account the 1/No rotational and linear mscorrections. The main contribution to the electric-like transition form factor comes from the wave-function corrections. This is a consequence of the generalized Ademollo-Gatto theorem. It is also found that in general the leading-order contributions are almost canceled by the rotational 1/No corrections. The results are summarized as follows： the vector and tensor K＇NO coupling constants, gK＊N= 0.74--0.87 and fk＊N =0.53--1.16, respectively, and F→KN = 0.71 MeV, based on the result of the KN coupling constant gKne =0.83. We also show the differential cross sections and beam asymmetries, based on the present results. We also discuss the connection of present results with the original work by Diakonov, Petrov, and Polyakov.     

PV型HgCdTe光电探测器中的混沌及其诊断

 对激光辐照半导体光电探测器的实验研究，发现当一束不太强的稳定连续波激光照射在PV型HgCdTe光电探测器上时，可以引起探测器出现混沌行为。利用光电探测器的光电压信号随时间变化的实验数据，通过求功率谱、计算Lyapunov指数对混沌进行了诊断。     

用单一驱动变量同步混沌与超混沌的一种方法

为减少混沌或超混沌同步过程中所需同步信号的个数以及提高同步的效率，提出了用线性可逆变换的方法重组系统，从而使原来不能同步的系统实现了只用单一信号就可同步的目的-另外，也大大提高系统的同步速率- 关键词： 线性可逆变换 混沌和超混沌同步 最大条件Lyapunov指数     

航天光学遥感器像移速度矢计算数学模型

随着地面影像分辨力愈来愈高的要求,航天光学遥感器实时精确补偿摄影时地物产生的像移,已成为必需解决的关键技术之一。论述了航天光学遥感器在对星下点摄影时,通过建立从地面景物到像面的七个坐标系,进行14次线性变换,获得了具有15个参量的像面位置方程、像面速度方程,推导出像面上像移速度矢的计算公式,对影响像移速度矢的11个参量进行误差分配,以及应用蒙特卡罗法(统计试验法)进行误差综合。该理论方法已得到了实际应用,从获得的遥感图像达到的分辨力、奈奎斯特(Nyquist)频率处的传递函数、信噪比和平均灰度层次均充分证明了该研究结果的正确性。     

Modelling of chaotic systems based on modified weighted recurrent least squares support vector machines

Positive Lyapunov exponents cause the errors in modelling of the chaotic time series to grow exponentially. In this paper, we propose the modified version of the support vector machines (SVM) to deal with this problem. Based on recurrent least squares support vector machines (RLS-SVM), we introduce a weighted term to the cost function tocompensate the prediction errors resulting from the positive global Lyapunov exponents. To demonstrate the effectiveness of our algorithm, we use the power spectrum and dynamic invariants involving the Lyapunov exponents and the correlation dimension as criterions, and then apply our method to the Santa Fe competition time series. The simulation results shows that the proposed method can capture the dynamics of the chaotic time series effectively.     

General demonstration of principal states of polarization and real-time monitoring of polarization mode dispersion in optical fibres

We investigated the general properties of polarization effects in optical fibres and demonstrated the existence of socalled principal states of polarization (PSP), which mean the fixed points in mathematics, in different polarization effects,such as birefringence and polarization mode dispersion, by using fixed point theory. Furthermore, a time evolution vector is defined to describe the time evolution of polarization state in optical fibres, which is used to investigate the time evolution of polarization mode dispersion vector (PDV), including differential group delay and PSP. The experimental results of real-time monitoring of PDV by using this method are reported. To our knowledge, this is the first report on monitoring PSP evolution in optical fibres.     

基于Karhunen-Loève变换和小波谱特征矢量量化的三维谱像数据压缩

提出了基于Karhunen Lo埁ｖｅ变换的小波谱特征矢量量化三维谱像数据压缩方法耍幔颍瑁酰睿澹?Lo埁ｖｅ变换 /小波变换 /小波谱特征矢量量化方法应用了Karhunen Lo埁ｖｅ变换的消除谱相关性优良性能 ,应用二维小波变换消除空间相关性 ,在小波变换域内应用二维集分割嵌入块编码和一维谱特征矢量量化对三维谱像数据压缩 ,获得较高的压缩性能。实验结果表明 :Karhunen Lo埁ｖｅ变换 /小波变换 /小波谱特征矢量量化编码比Karhunen Lo埁ｖｅ变换 /小波变换 /改进对块零树编码和Karhunen Lo埁ｖｅ变换 /小波变换 /快速矢量量化编码方法在同样压缩比条件下 ,峰值信噪比提高 2dB和 1dB以上 ,而速度提高了 1.5和 8倍 ,整体压缩性能有较大的提高     

用于高数值孔径物镜的可调光瞳滤波器

根据矢量衍射理论，提出了一种用于提高高数值孔径显微物镜纵向分辨率的可调二元环形光瞳滤波器，通过改变滤波器的环半径获得不同的纵向分辨率，并利用共焦显微术点扩散函数的乘积性大大地降低了旁瓣相对主瓣的比值。模拟结果表明，这种新型滤波器不仅可以提高高数值孔径物镜的纵向分辨率，同时基本上不影响横向分辨率。