Dynamic Waveband Switching in WDM Mesh Networks Based on a Generic Auxiliary Graph Model

Waveband switching (WBS) is a promising technique to reduce the switching and transmission costs in the optical domain of a wavelength-division multiplexing (WDM) network. This paper considers the problem of provisioning dynamic traffic using WBS in a WDM mesh network. The network of interest is a homogeneous WBS network, where each node has the functionality of WBS. The problem is called the dynamic WBS problem, which involves searching waveband-routes or wavelength-routes for the dynamically arriving traffic requests. The objective is to minimize the total switching and transmission costs in the optical domain. To solve the dynamic WBS problem, an auxiliary graph model capturing the network state is proposed. Based on the auxiliary graph, two heuristic on-line WBS algorithms with different waveband grouping policies are proposed, namely the wavelength-first WBS algorithm based on the auxiliary graph (WFAUG) and the waveband-first WBS algorithm based on the auxiliary graph (BFAUG). Simulation results indicate that WBS is an attractive technique which reduces the overall switching and transmission costs by up to 30% in the network. The results also show that the WFAUG algorithm outperforms the BFAUG algorithm in terms of port savings and cost savings.     

一个矢量形式的双圆弧插值算法

本文在分析数控插补最常用的双圆弧插值算法特点的基础上，将以局部坐标系中的三角运算为核心的传统双圆弧插值算法，改造成为以整体坐标系中的线性运算为核心的矢量形式的双圆弧插值算法，从而减少了计算的复杂性和程序的复杂性，提高了效率和可靠性。     

逻辑程序的一种并行执行模型

本文基于静态相关性分析和动态调整相结合的方法，提出了一种逻辑程序的执行模型，它不仅开发了“与“并行，同进也开发了一定的“或“并行，从而有效地加速了逻辑程序的执行。     

基于运动矢量的视频图象数字水印算法

数字水印技术是近年发展起来的一种用于数字产品版权保护和真伪性论证的新兴技术。与静止图象相比，视频水印技术要满足盲检的要求。本文根据运动矢量的特征值ρl，提出了一种视频图象水印新算法。实验结果表明，所提出的水印算法简单、快速，能满足视频编码的实时性要求；算法与现有的视频压缩标准有很好的兼容性；水印的提取具有盲检功能，无需原图象；水印的嵌入不影响I帧的图象质量，与嵌入水印前的原压缩图象相比，嵌入水印后的视频图象信噪比损失很小。     

线性时变系统的区间稳定性与鲁棒稳定性

本文应用向量比较定理研究线性时变系统的区间稳定性和具非线性时变摄动的线性时变系统的鲁棒稳定性，所得的新结果包含文献的一些主要结果作为特例，本文的研究方法说明向量比较方法是分析区间稳定性和鲁棒稳定性的一种自然而有力的工具。     

Melt index prediction by weighted least squares support vector machines

Melt index is considered an important quality variable determining product specifications. Reliable prediction of melt index (MI) is crucial in quality control of practical propylene polymerization processes. In this paper a least squares support vector machines (LS‐SVM) soft‐sensor model of propylene polymerization process is developed to infer the MI of polypropylene from other process variables. Considering the use of a SSE cost function without regularization might lead to less robust estimates; the weighted least squares support vector machines (weighted LS‐SVM) approach of propylene polymerization process is further proposed to obtain a robust estimation of melt index. The performance of standard SVM model is taken as a basis of comparison. A detailed comparison research among the standard SVM, LS‐SVM, and weighted LS‐SVM models is carried out. The research results confirm the effectiveness of the presented methods. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 101: 285–289, 2006     

An efficient clustering scheme using support vector methods

Support vector clustering involves three steps—solving an optimization problem, identification of clusters and tuning of hyper-parameters. In this paper, we introduce a pre-processing step that eliminates data points from the training data that are not crucial for clustering. Pre-processing is efficiently implemented using the R*-tree data structure. Experiments on real-world and synthetic datasets show that pre-processing drastically decreases the run-time of the clustering algorithm. Also, in many cases reduction in the number of support vectors is achieved. Further, we suggest an improvement for the step of identification of clusters.     

定量确定纤维织构轴密度分布的矢量法

本文将大幅度减少衍射极图测试数目的织构分析矢量法应用于定量确定纤维织构材料的晶粒取向分布;采用蒙特卡罗方法计算系数矩阵σ_(pn)(hkl)。对立方晶系的研究结果表明,由一张极图甚至一张不完整极图即可准确地构建纤维轴密度分布图。     

基于Gibbs模型的提高图像分辨率方法

在提高图像分辨率过程中,选择合适的成像模型是获得高分辨率图像的一个关键因素。提出一种基于最大后验概率、采用Gibbs成像模型,并利用多帧序列图像重构高分辨率图像的方法,充分利用序列图像之间的累加信息,从而快速地获得较其他方法更优的高分辨率图像。     

支持向量机在交通量预测中的应用

交通量预测对于区域交通规划有重要意义。提出一种基于支持向量机理论的交通量预测方法。该方法以统计学习理论为基础，通过和BP神经网络进行比较的实验，证明其在交通量预测中的有效性。