Segment-based adaptive hyper-Erlang model for long-tailed network traffic approximation

Modeling the long-tailedness property of network traffic with phase-type distributions is a powerful means to facilitate the consequent performance evaluation and queuing based analysis. This paper improves the recently proposed Fixed Hyper-Erlang model (FHE) by introducing an adaptive framework (Adaptive Hyper-Erlang model, AHE) to determine the crucially performance-sensitive model parameters. The adaptive model fits long-tailed traffic data set directly with a mixed Erlang distribution in a new divide-and-conquer manner. Compared with the well-known hyperexponential based models and the Fixed Hyper-Erlang model, the Adaptive Hyper-Erlang model is more flexible and practicable in addition to its accuracy in fitting the tail behavior.

Blind Deconvolution Models Regularized by Fractional Powers of the Laplacian

We present a method for deconvolution of images by means of an inversion of fractional powers of the Gaussian. The main feature of our model is the introduction of a regularizing term which is also a fractional power of the Laplacian. This term allows us to recover higher frequencies. The model is particularly useful to devise an algorithm for blind deconvolution. We will show, analyze and illustrate through examples the performance of this algorithm.

Following non-stationary distributions by controlling the vector quantization accuracy of a growing neural gas network

In this paper, an original method extended from growing neural gas (GNG-T) [B. Fritzke, A growing neural gas network learns topologies, in: G. Tesauro, D.S. Touretzky, T.K. Leen (Eds.), Advances in Neural Information Processing Systems 7, MIT Press, Cambridge, MA, 1995, pp. 625–632] is presented. The method performs continuously vector quantization over a distribution that changes over time. It deals with both sudden changes and continuous ones, and is thus suited for the video tracking framework, where continuous tracking is required as well as fast adaptation to incoming and outgoing people. The central mechanism relies on the management of the quantization resolution, that copes with stopping condition problems of usual GNG inspired methods. Application to video tracking is presented.     

Multi-rate model predictive control of particle size distribution in a semibatch emulsion copolymerization reactor

A multi-rate model predictive controller algorithm is presented for the in-batch closed-loop control of the full particle size distribution (PSD) in a semibatch emulsion copolymerization system. The lack of frequent measurements of the PSD and the measurement delay of these measurements are addressed through the use of frequent density measurements from which the current conditions of the system are estimated. The high dimensionality of the discretized full PSD is reduced by the use of model order reduction based on principal component analysis. This method effectively reduces the size of the problem while preserving the main characteristics of the population balance system. Disturbances that perturb the surfactant and monomer amounts inside the semibatch vinyl acetate–butyl acrylate reactor are considered to demonstrate the performance of the proposed control algorithm.     

改进的模糊交叉算子及其在CGA中的应用

基于标准化适应值信息,提出改进的模糊交叉算子,并应用到细胞状遗传算法(CGA)中。在具有局部搜索倾向的交叉操作中,该算子能使后代更偏向于适应值高的父体。在具有全局搜索倾向的交叉操作中,能使较差个体在更大范围内进行搜索,有效地引导CGA算法向全局最优解的方向收敛。仿真实验结果表明,基于改进模糊交叉算子的CGA算法性能更好。     

基于线性变换的计算与数据动态分解方法

在并行优化编译器的并行识别过程中,许多串行代码无法找到全局一致的分解结果,数据重分布无可避免,有必要寻找一种有效的方法求解计算和数据的动态分解。该文研究了单个嵌套循环计算与数据分解算法以及分解结果表示方法,提出一种在多个嵌套循环间求解数据线性一致分布的动态分解算法,结合程序的结构分析和程序的控制流信息,用于通用串行代码的并行分解过程,可以同时给出串行代码的计算划分和数据分布结果。     

一种新的基于遗传操作的改进型遗传算法

交叉与变异是遗传算法的重要操作,提出了一种新的基于遗传操作的改进型遗传算法.采用最优保留和改进的轮盘赌选择方法,通过基因交叉概率控制交叉,根据高斯分布改进了交叉算子和变异算子,保证了算法的全局搜索能力、局部搜索能力及收敛速度.通过标准函数的数值实验,验证了新算法的有效性.     

管理信息网抗毁构建研究

在机动通信组网时,网络管理信息网是网络管理系统对各节点设备进行参数下发和状态监控的交互通道,在基于ATM虚连接和IP路由器构建的网管信息网中,通过研究网络互连策略和IP动态路由技术,构建了不受限于节点连接接口的抗毁管理信息组网,提高了网络的顽存能力,拓宽了机动通信的适应性,该方法可在工程中推广应用。     

基于复杂局域网的综合布线系统的接地设计

结构化综合布线系统是近年来新兴的高技术产业,是信息化社会发展的必然趋势。综合布线是整个网络组建过程中至关重要的一部分,特别是在规模较大、结构复杂的局域网中。该文对综合布线系统中的接地类型分别予以了介绍,并对综合布线系统中的接地设计进行了阐述。     

基于知识点的试题库组卷算法

该文介绍了一种基于知识点的,采用离散型随机变量的二项分布函数构造选题算法的方法。该算法把题型平均难度系数、题型个数作为主要控制目标,以包含题目题型作为主要条件筛选知识点,以此选择试题,而后对题目按知识点的各难度等级分类,从而按知识点选题组卷,并运用适当的组卷策略优化组卷结果。