Maximum principle for mean-field jump–diffusion stochastic delay differential equations and its application to finance

This paper investigates a stochastic optimal control problem with delay and of mean-field type, where the controlled state process is governed by a mean-field jump–diffusion stochastic delay differential equation. Two sufficient maximum principles and one necessary maximum principle are established for the underlying system. As an application, a bicriteria mean–variance portfolio selection problem with delay is studied to demonstrate the effectiveness and potential of the proposed techniques. Under certain conditions, explicit expressions are provided for the efficient portfolio and the efficient frontier, which are as elegant as those in the classical mean–variance problem without delays.     

凹凸棒粘土用作高水速凝注浆悬浮剂

以凹凸棒粘土作为高水速凝固化充填材料的悬浮稳定剂，考察了不同制浆机械对凹凸棒粘土制浆率的影响。采用高剪切混合乳化机预制的1％凹凸棒粘土浆配制高水速凝固化充填材料甲、已料单浆可获得满意的悬浮稳定效果。其充填体结石抗压强度早期发展迅速，后期持续增长。采用此工艺，注浆料的材料成本仅增加2％。     

溶液缩聚物分子量分布及其控制的研究

本文根据溶液缩聚基本原理及反应过程的基本事实，用随机过程方法，得到缩聚产物分子量分布函数，并对分子量及其分布的控制作了讨论。     

尼龙/聚丙烯合金的性能与制备

介绍国外各种尼龙/聚丙烯合金的性能和制备工艺。聚合物合金的相容性原理,以及PA/PP合金适用的各种相容剂。     

Surface morphology and nodule formation mechanism of cellulose acetate membranes by atomic force microscopy

By the use of atomic force microscopy (AFM), formation mechanism of nodular structure in cellulose acetate membranes was systematically investigated. Elementary factors affecting the nodule formation were delineated on the basis of both kinetic and thermodynamic considerations. It was shown that (1) the exact nature of nodular structure is thermodynamic equilibrium glassy state; nodular structure will vanish in the rubbery state; (2) the thermodynamic factor affecting nodule formation is the membrane formation temperature; with the membrane formation temperature decreasing, more chain segments are able to form nodular structures; (3) nodule formation is dependent on the segment rearrangement; variation of the solvent environment is the major kinetic factor affecting the segment rearrangement and nodule formation. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 88: 1328–1335, 2003     

Poly(3‐chlorothiophene) films prepared by the direct electrochemical oxidation of 3‐chlorothiophene in mixed electrolytes of boron trifluoride diethyl etherate and sulfuric acid

3‐Chlorothiophene (CT) was electrochemically polymerized in mixed electrolytes of a boron trifluoride diethyl etherate solution containing 0–20% (by volume) sulfuric acid. The oxidation potentials of the monomer in these media were measured to be only 1.06–1.31 V (vs Ag/AgCl). These values were much lower than that of CT in acetonitrile and 0.1 mol/L (Bu)₄NBF₄ (1.92 V vs Ag/AgCl). Poly(3‐chlorothiophene) (PCT) films with conductivities of 0.1–2 S cm^?1 were obtained. The structure, morphology, and electrochemical behavior of the PCT films also were investigated. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 87: 502–509, 2003     

A novel self-adaptive extreme learning machine based on affinity propagation for radial basis function neural network

In this paper, a novel self-adaptive extreme learning machine (ELM) based on affinity propagation (AP) is proposed to optimize the radial basis function neural network (RBFNN). As is well known, the parameters of original ELM which developed by G.-B. Huang are randomly determined. However, that cannot objectively obtain a set of optimal parameters of RBFNN trained by ELM algorithm for different realistic datasets. The AP algorithm can automatically produce a set of clustering centers for the different datasets. According to the results of AP, we can, respectively, get the cluster number and the radius value of each cluster. In that case, the above cluster number and radius value can be used to initialize the number and widths of hidden layer neurons in RBFNN and that is also the parameters of coefficient matrix H of ELM. This may successfully avoid the subjectivity prior knowledge and randomness of training RBFNN. Experimental results show that the method proposed in this thesis has a more powerful generalization capability than conventional ELM for an RBFNN.     

Wavelet twin support vector machine

Twin support vector machine (TWSVM) is a research hot spot in the field of machine learning in recent years. Although its performance is better than traditional support vector machine (SVM), the kernel selection problem still affects the performance of TWSVM directly. Wavelet analysis has the characteristics of multivariate interpolation and sparse change, and it is suitable for the analysis of local signals and the detection of transient signals. The wavelet kernel function based on wavelet analysis can approximate any nonlinear functions. Based on the wavelet kernel features and the kernel function selection problem, wavelet twin support vector machine (WTWSVM) is proposed by this paper. It introduces the wavelet kernel function into TWSVM to make the combination of wavelet analysis techniques and TWSVM come true. The experimental results indicate that WTWSVM is feasible, and it improves the classification accuracy and generalization ability of TWSVM significantly.     

纹理豪斯多夫距离在人脸识别算法中的应用

很多经典的人脸识别方法难以适应姿势变化及人脸错位的情形。为了解决这一问题,提出一种基于纹理豪斯多夫距离(THD)的人脸识别算法。将人脸图像的空间量及纹理特征相结合,使其在深入的头部转动和人脸错位中都有很高的容错度。在FERET及Yale两大人脸数据库的实验表明,与其他经典的方法相比较,所提出的方法取得了更好的识别效果。     

磁盘阵列环境下的取证目标系统重构

封存原始硬盘与业务系统服务的连续性是计算机取证中面临的一对矛盾。在独立硬盘环境中,问题的解决并不困难,但在磁盘阵列(RAID)环境下,目前还缺乏有效的解决办法。为此,为RAID环境下的取证目标系统的重构提出一套解决方案,并设计实现其中关键任务的处理软件。实验表明,该方法可适用于不同RAID等级、不同操作系统下的系统重构,使得用户感受不到重构得到的系统与原系统有任何差异。与数据同步方法相比,该方法可以有效地减少重构的时间开销,且不会破坏原始证据硬盘上的数据。