基于层叠模型的网络流量异常检测方法*

进行网络流量异常检测,需要对正常流量行为建立准确的模型,根据异常流量与正常模型间的偏离程度作出判断。针对现有网络流量模型中自相似模型与多分形模型无法全面刻画流量特征的不足,提出了一种基于流量层叠模型分析的异常检测算法,采用层叠模型对整个时间尺度上的流量特征进行更准确的描述,并运用小波变换对流量的层叠模型进行估计,分析异常流量对模型估计的影响,提出统计累计偏离量进行异常流量检测的方法。仿真结果表明,该方法能够有效检测出基于自相似Hurst系数方法不能检测的弱异常以及未明显影响Hurst系数变化的异常流。     

一种改进的基音周期提取算法研究

现有的基音周期提取方法在准确度和稳健性上存在一定的局限性,很难准确地提取出信噪比较低的语音信号的周期.针对这一问题,提出一种基于小波变换的基音周期提取改进算法,将TEO(Teager Energy Operator)算子与二进小波变换结合起来,首先进行清浊判定,然后只对浊音帧采取多尺度小波分析提取周期,提出用幅度信息和出现概率信息校正二进小波模极大值间距,从而得到准确的周期.计算机仿真结果表明,与传统方法相比,不仅提高了处理效率,而且具有更高的精确度和稳定性.     

基于二维小波变换的车牌边缘检测的研究

在Matlab环境下运用基于二维小波变换边缘检测方法提取车牌信息的边缘。实验证明这种方法对车牌边缘信息提取的效果比传统的边缘提取算子提取车牌信息边缘的效果要好,特别是对伪边缘和图片噪声的过滤作用比较明显。     

Fabricating Strong and Stiff Bioplastics from Whole Spirulina Cells

Since the 1950s, 8.3 billion tonnes (Bt) of virgin plastics have been produced, of which around 5 Bt have accumulated as waste in oceans and other natural environments, posing severe threats to entire ecosystems. The need for sustainable bio-based alternatives to traditional petroleum-derived plastics is evident. Bioplastics produced from unprocessed biological materials have thus far suffered from heterogeneous and non-cohesive morphologies, which lead to weak mechanical properties and lack of processability, hindering their industrial integration. Here, a fast, simple, and scalable process is presented to transform raw microalgae into a self-bonded, recyclable, and backyard-compostable bioplastic with attractive mechanical properties surpassing those of other biobased plastics such as thermoplastic starch. Upon hot-pressing, the abundant and photosynthetic algae spirulina forms cohesive bioplastics with flexural modulus and strength in the range 3–5 GPa and 25.5–57 MPa, respectively, depending on pre-processing conditions and the addition of nanofillers. The machinability of these bioplastics, along with self-extinguishing properties, make them promising candidates for consumer plastics. Mechanical recycling and fast biodegradation in soil are demonstrated as end-of-life options. Finally, the environmental impacts are discussed in terms of global warming potential, highlighting the benefits of using a carbon-negative feedstock such as spirulina to fabricate plastics.     

小波法的网络流量奇异谱估计

网络流量整形、调度、异常检测、管理与控制及保障QoS需求等都需要了解业务流的局部变化特性.本文给出离散小波及其模极大值的网络流量奇异谱估计算法及影响因素,并通过真实的网络业务数据对算法进行了评估和比较.实验结果表明,两种方法的奇异谱估计能有效刻画网络业务流的局部变化特征,并且能通过奇异谱特征参数之间的差别描述不同业务流之间的差异性,也表明了在一定条件下,离散小波模极大法更加优越.     

一种最大向量平均个数的估计方法

提出一种估计n个d维向量中最大向量平均个数的方法。该方法通过分析单个向量与其他向量子集的支配关系,求出最大向量平均个数的解析式。证明解析式满足已知的递归关系,得到最大向量平均个数的近似估计。与已有方法相比,该方法可应用到估计k个其他向量支配的平均个数问题。     

基于PT在线注入信号及神经网络跟踪小波变换模极大值变化的配电网故障定位方法

提出了一种配网单相接地在线故障定位的新方法。故障发生后从变电站母线在线向系统注入高频脉冲信号并获取线路上与注入信号相对应的反射行波,在电网结构已知的情况下,通过对反射波的分析进行故障定位。该方法不仅能检测故障点的电气距离,而且能确定故障所在的分支线路,还能通过调节注入信号的大小多次定位故障,提高定位的准确性。应用该方法进行故障定位不受接地电阻的限制。通过M atlab/S imu-link进行了建模与仿真分析,仿真结果验证了该方法的正确性。     

基于小波理论的噪声信号分析

小波分析是使信号具有时－频局部特性的信号处理方法。利用小波变换在各尺度的模极大值，能够确定波形的奇异点和在奇异点处的ｌｉｐｓｃｈｉｔｚ指数α。     

输电线路暂态电压行波的故障特征及其小波分析

分析了电压行波的基本故障特征 ,给出了电压行波故障特征的新的数学描述———小波表示。建立起了电压行波的故障特征和小波变换模极大值之间的联系 :通过有限个具有明确物理意义的小波变换模极大值 ,完整、清晰地刻划了暂态电压行波的故障特征。为构造性能优良、可靠的行波测距和行波保护奠定了重要的数学基础。     

Circle Chart for the Monitoring of Maxima in Periodic Processes

An important process characteristic is process maxima as it is often an important quality or performance parameter. Such measurements often play a vital role in process analysis and have to be monitored carefully. In this paper, we consider the problem of monitoring process maxima when the process exhibits a kind of periodicity. A circle chart for periodical process maxima with or without seasonal patterns monitoring is developed and studied, by modeling the process maxima using the extreme value distribution. Mean normalization is applied for periodic process monitoring with seasonal patterns to facilitate comparison between different sections and periods. The average cycle run length is proposed to measure charting efficiency. Copyright © 2014 John Wiley & Sons, Ltd.