机载电缆作战损毁后智能化诊断系统

从技战术实际需要出发,给出了某型飞机作战损毁后机载电缆的智能化诊断系统的硬件结构框图。根据硬件系统模拟开关组件的原理,定义了电缆的连接矩阵、测量矩阵以及断口的映像矩阵运算,给出了断头查找的算法。计算表明,系统可在20 min内完成一个循环的断头查找并给出故障定位。     

A weighted H1 seminorm regularization method for Fredholm integral equations of the first kind

Many problems in mathematics and engineering lead to Fredholm integral equations of the first kind, e.g. signal and image processing. These kinds of equations are difficult to solve numerically since they are ill-posed. Therefore, regularization is required to obtain a reasonable approximate solution. This paper presents a new regularization method based on a weighted H¹ seminorm. Details of numerical implementation are given. Numerical examples, including one-dimensional and two-dimensional integral equations, are presented to illustrate the efficiency of the proposed approach. Numerical results show that the proposed regularization method can restore edges as well as details.     

Lossless asymmetric single instruction multiple data codec

This report introduces a new lossless asymmetric single instruction multiple data codec designed for extremely efficient decompression of large satellite images. A throughput in excess of 3GB/s allows decompression to proceed in parallel with asynchronous transfers from fast block devices such as disk arrays. This is made possible by a simple and fast single instruction multiple data entropy coder that removes leading null bits. Our main contribution is a new approach for vectorized prediction and encoding. Unlike previous approaches that treat the entropy coder as a black box, we account for its properties in the design of the predictor. The resulting compressed stream is 1.2 to 1.5 times as large as JPEG‐2000, but can be decompressed 100 times as quickly – even faster than copying uncompressed data in memory. Applications include streaming decompression for out of core visualization. To the best of our knowledge, this is the first entirely vectorized algorithm for lossless compression. Copyright © 2011 John Wiley & Sons, Ltd.     

金属表面脏污区域的分割和量化算法研究

针对目前金属表面缺陷检测技术的研究现状,主要研究金属表面脏污检测与量化算法。结合金属表面的特点,通过对几种分割方法的比较,研究了阈值分割法中的迭代法对图像进行分割,该算法能够最大限度地保留细节信息。另外,研究了一种改进的自适应滤波算法结合像素计数法对金属表面的脏污区域进行量化处理。实验结果证明了所提出方法的有效性。     

Structure quantitative map in application for AB2X4 system

Structure maps are constructed for AB₂X₄ (A = metal, B = three-valency element and X = O, S, Se, Te) system (>490 compounds). A way to improve the resolution of the maps is proposed. Crystal structure characteristic (symmetry) is represented on a quantitative scale (coordinate axe Z). The 3D structure diagram with approximating integral plane is constructed and a field of high symmetry compounds is specified with ion radii ratio R(A)/R(X) ≈ 0.60–0.85 and R(B)/R(X) ≈ 0.55–0.70.     

基于XC164CS微处理器的正弦脉宽调制信号的实现

把电压空间矢量的概念引入到正弦脉宽调制波形产生中,介绍了16位微处理器在正弦脉宽调制中的应用,并基于具体硬件结构利用双极性调制方法实现了正弦脉宽调制波形的生成。试验证明:本方案具有计算速度快、效率高的优点,在工程实践中切实可行。     

基于多种特征的红外目标识别技术研究

红外图像独特的热辐射特性,通常是由其各个子部件的红外热辐射特性所形成的。文中在传统红外热图像特征量的基础上,通过分析红外热图像自身特性以及它的形成与其自身姿态的关系,提出了对目标物体红外热图像基于目标姿态的子分类,并对目标红外热图像进行了子区域分割,通过多目标分类器进行识别,形成了新的红外图像特征量。     

基于Kohonen神经网络聚类方法在遥感分类中的比较

设计完成和比较了基于Kohonen自组织网络的Kohonen聚类网络（Kohonen Clustering Network, KCN）、模糊Kohonen聚类网络（Fluzzy KCN, FKCN）和基于进化规划的Kohonen聚类网络（Evalutionary Programming based KCN, EPKCN）三种聚类算法在遥感土地利用/覆盖分类中的应用。结果表明三种非监督学习方法在进行遥感土地利用/覆盖分类过程中，在分类性能上有显著差异。EPKCN分类目视效果最好，单次迭代的速度最快；FKCN总的收敛速度最快；而按遥感土地利用/覆盖分类要求而言，EPKCN方法在三种分类方法中效果最好，因此可采用该算法进行遥感土地利用/覆盖的非参数分类。