Extending metric multidimensional scaling with Bregman divergences

Sum of weighted square distance errors has been a popular way of defining stress function for metric multidimensional scaling (MMDS) like the Sammon mapping. In this paper we generalise this popular MMDS with Bregman divergences, as an example we show that the Sammon mapping can be thought of as a truncated Bregman MMDS (BMMDS) and we show that the full BMMDS improves upon the Sammon mapping on some standard data sets and investigate the reasons underlying this improvement. We then extend a well known family of MMDS, that deploy a strategy of focusing on small distances, with BMMDS and investigate limitations of the strategy empirically. Then an opposite strategy is introduced to create another family of BMMDS that gives increasing mapping quality. A data preprocessing method and a distance matrix preprocessing are introduced.     

Dynamic demultiplexing in network calculus—Theory and application

During the last two decades, starting with the seminal work by Cruz, network calculus has evolved as a new theory for the performance analysis of networked systems. In contrast to classical queueing theory, it deals with performance bounds instead of average values and thus has been the theoretical basis of quality of service proposals such as the IETF’s Integrated and Differentiated Services architectures. Besides these it has, however, recently seen many other application scenarios as, for example, wireless sensor networks, switched Ethernets, avionic networks, Systems-on-Chip, or even to speed-up simulations, to name a few.In this article, we extend network calculus by adding a new versatile modeling element: a demultiplexer. Conventionally, demultiplexing has been either neglected or assumed to be static, i.e., fixed at the setup time of a network. This is restrictive for many potential applications of network calculus. For example, a load balancing based on current link loads in a network could not be modeled with conventional network calculus means. Our demultiplexing element is based on stochastic scaling. Stochastic scaling allows one to put probabilistic bounds on how a flow is split inside the network. Fundamental results on network calculus with stochastic scaling are therefore derived in this work. We illustrate the benefits of the demultiplexer in a sample application of uncertain load balancing.     

一种机载图像缩放引擎的设计与实现

针对机载前景与背景显示画面的不同特征,提出一种实用的航空电子图像缩放引擎的设计方法,通过配置不同的算法以及改变设计架构,解决了传统设计中画面叠加后处理算法难以统一优化的问题.首先利用软件仿真不基于和基于边缘的两种缩放算法,然后利用FPGA(现场可编程门阵列)的可重构特性,将两种核心算法实现在不同的图像处理通道上,最后进行了完整的基于FPGA的硬件实现.实验结果表明本文的设计在显示效果上要优于单一的双三次插值算法,兼具处理速度快和运算复杂度低的特点.     

基于新的超混沌系统的图像加密方案

提出了一个新的超混沌系统,分析了新系统的混沌吸引子相图、平衡点及其性质、工yapunov指数等非线性动力学特性,并用该超混沌系统对图像进行加密研究。给出了一种新的基于四维超混沌系统的图像加密算法。实验结果及安全性分析表明,该算法具有较强的抵御穷举攻击、统计攻击、已知明文攻击能力,因而具有较高的安全性。     

Fuzzy ARTMAP classification of invariant features derived using angle of rotation from a neural network

Conventional regular moment functions have been proposed as pattern sensitive features in image classification and recognition applications. But conventional regular moments are only invariant to translation, rotation and equal scaling. It is shown that the conventional regular moment invariants remain no longer invariant when the image is scaled unequally in the x- and y-axis directions. We address this problem by presenting a technique to make the regular moment functions invariant to unequal scaling. However, the technique produces a set of features that are only invariant to translation, unequal/equal scaling and reflection. They are not invariant to rotation. To make them invariant to rotation, moments are calculated with respect to the principal axis of the image. To perform this, the exact angle of rotation must be known. But the method of using the second-order moments to determine this angle will also be inclusive of an undesired tilt angle. Therefore, in order to correctly determine the amount of rotation, the tilt angle which differs for different scaling factors in the x- and y-axis directions for the particular image must be obtained. In order to solve this problem, a neural network using the back-propagation learning algorithm is trained to estimate the tilt angle of the image and from this the amount of rotation for the image can be determined. Next, the new moments are derived and a Fuzzy ARTMAP network is used to classify these images into their respective classes. Sets of experiments involving images rotated and scaled unequally in the x- and y-axis directions are carried out to demonstrate the validity of the proposed technique.     

Dynamic voltage scaling under EDF revisited

Basic algorithms have been proposed in the field of low-power (Yao, F., et al. in Proceedings of lEEE annual foundations of computer science, pp. 374–382, 1995) which compute the minimum energy-schedule for a set of non-recurrent tasks (or jobs) scheduled under EDF on a dynamically variable voltage processor. In this study, we propose improvements upon existing algorithms with lower average and worst-case complexities. They are based on a new EDF feasibility test that helps to identify the “critical intervals”. The complexity of this feasibility test depends on structural characteristics of the set of jobs. More precisely, it depends on how tasks are included one in the other. The first step of the algorithm is to construct the Hasse diagram of the set of tasks where the partial order is defined by the inclusion relation on the tasks. Then, the algorithm constructs the shortest path in a geometrical representation at each level of the Hasse diagram. The optimal processor speed is chosen according to the maximal slope of each path.

基于二重循环的数字水印算法

针对现有数字水印算法中存在的抵抗联合攻击能力差、水印提取准确率不高等问题,提出了一种基于分块快速傅里叶变换(FFT)的二重循环数字水印算法.先进行图像大小归一化,对其进行分块FFT变换,在每个图像块的FFT系数中通过大小关系调制嵌入若干比特水印,水印按照二重循环嵌入.提取时从任何一个包括所有水印的图像部分中,直接通过判断FFT系数的大小关系来提取水印.实验结果表明,该算法能抵抗滤波加噪等常规信号处理攻击,JPEG压缩等压缩攻击,旋转、缩放、平移等全局几何攻击和裁剪、拼贴等特殊攻击以及它们的联合攻击,并且误码率低,接近0.     

彩色图像增强的改进算法

为提高彩色图像的整体感官效果,在研究CES（Color image Enhancement by Scaling）算法出现块效应的原因基础上,提出了一种改进算法,即各向异性扩散滤波器的ICES（Improved Color image Enhancement byScaling）。与CES相比,ICES算法在不增加计算复杂性的前提下,不仅得到了不逊于CES算法的增强效果,还能极大地抑制块效应。     

一类含两个圈的特殊本原双色有向图的指数

一个双色有向图D是本原的,如果存在非负整数h和k,h+k>0,使得D的每对顶点(i,j)都存在从i到j的(h,k)-途径,称h+k的最小值为本原双色有向图D的指数.给出了一类含两个圈的特殊本原双色有向图指数的紧的上下界,并对一类特殊情况进行了极图刻划.