射流式单重态氧发生器研究

单重态氧O2 (a1Δg)是迄今唯一能用纯化学反应高效产生的具有长寿命的亚稳激发态分子 .为了考察提出的用两个O2 (1Δ)能量汇集反应生成氧第二单重激发态O2 (b1Σ+ g)以实现近可见短波长化学激光方案的现实性 ,设计和实验了一个氯流量为 3～ 10mmol/s的射流式单重态氧发生器 (JSOG) .考察了三种具有不同孔径和孔数目的喷头、氯气流量和脱水冷阱温度等对JSOG出口的O2 (1Δ)浓度、O2 (1Δ)分压、氯利用率及水蒸气含量的影响 .发现用聚氯乙烯管作冷阱时 ,最佳冷阱介质温度为 - 140～ - 15 0℃ ,对此提出了O2 (1Δ)表面脱活与脱水互相竞争的解释 .在最佳条件下 ,可将O2 (1Δ)气中水分压降低至 4Pa ,这一结果是首次报导     

Disparity field and depth map coding for multiview 3D image generation

In the present paper techniques are examined for the coding of the depth map and disparity fields for stereo or multiview image communication applications. It is assumed that both the left and right channels of the multiview image sequence are coded using block- or object-based methods. A dynamic programming algorithm is used to estimate a disparity field between each stereo image pair. Depth is then estimated and occlusions are optionally detected, based on the estimated disparity fields. Spatial interpolation techniques are examined based on the disparity/depth information and the detection of occluded regions using either stereoscopic or trinocular camera configurations. It is seen that the presence of a third camera at the transmitter site improves the estimation of disparities, the detection of occlusions and the accuracy of the resulting spatial interpolation at the receiver. Various disparity field and depth map coding techniques are then proposed and evaluated, with emphasis given to the quality of the resulting intermediate images at the receiver site. Block-based and wireframe modeling techniques are examined for the coding of isolated depth or disparity map information. Further, 2D and 3D motion compensation techniques are evaluated for the coding of sequences of depth or disparity maps. The motion fields needed may be available as a byproduct of block-based or object-based coding of the intensity images. Experimental results are given for the evaluation of the performance of the proposed coding and spatial interpolation methods.     

无偏的岭回归迭代算法

本文探讨线性模型的无偏的岭回归迭代算法,这种算法保持最小二乘法的性质,当存在较为严重的共线性时,它能给出较为精确的参数及其协差阵的估计值;当存在严格的共线性时,给出参数及其协差阵的无穷多解中的一个,这个解由初值决定。文章还给出了算法的收敛性及一些其它性质的证明。     

Identification of nonlinear elliptic equations

An optimization theoretic approach and algorithm for the estimation of state-dependent coefficients in nonlinear elliptic equation is presented. It is based on a splitting method combined with convex analysis techniques. Convergence of the algorithm is established and numerical examples are included.The research of K. Kunisch was supported in part by a grant from the Bundesministerium für Wissenschaft und Forschung, Austria.     

具有平行平均曲率向量子流形的曲率估计与稳定性

本文估计空间形式中具有平行平均曲率向量子流形上共形度量的数量曲率上界,并利用其研究了具有常平均曲率超曲面的稳定性．     

On parabolic equations with a small parameter

A singularly perturbed parabolic equation with a nonlinear right-hand side of a special form is examined. A numerical analytical study of such equations is performed.     

Low-Temperature Magnetic Properties of Co Antidot Array

Cobalt antidot arrays with different thicknesses are fabricated by rf magnetron sputtering onto porous alumina substrates. Scanning electron microscopy and grazing incidence x-ray diffraction are employed to characterize the morphology and crystal structure of the antidot array, respectively. The temperature dependence of magnetic properties shows that in the temperature range 5K--300K, coercivity and squareness increase firstly, reach their maximum values, then decrease. The anomalous temperature dependences of coercivity and squareness are discussed by considering the pinning effect of the antidot and the magnetocrystalline anisotropy.     

人工神经网络技术在板料激光弯曲中的应用

基于人工神经网络基本理论,建立在板料激光弯曲中预测材料表面最高温度、弯曲角度的BP网络模型。借助于MATLAB仿真软件中的神经网络工具箱作为开发平台,将试验样本数据和经过试验验证的数值计算结果作为补充的样本数据用于BP网络的训练,利用训练好的BP网络对非线性的样本数据规律进行拟合,实现激光加工工艺参数的优化,为实际生产和加工提供有效的依据。     

Locally Adaptive Wavelet Empirical Bayes Estimation of a Location Parameter

The traditional empirical Bayes (EB) model is considered with the parameter being a location parameter, in the situation when the Bayes estimator has a finite degree of smoothness and, possibly, jump discontinuities at several points. A nonlinear wavelet EB estimator based on wavelets with bounded supports is constructed, and it is shown that a finite number of jump discontinuities in the Bayes estimator do not affect the rate of convergence of the prior risk of the EB estimator to zero. It is also demonstrated that the estimator adjusts to the degree of smoothness of the Bayes estimator, locally, so that outside the neighborhoods of the points of discontinuities, the posterior risk has a high rate of convergence to zero. Hence, the technique suggested in the paper provides estimators which are significantly superior in several respects to those constructed earlier.