抵御已知/选择明文攻击的混沌图像加密算法

论文在对现有一类典型图像混沌加密算法的分析基础上,提出了一种改进的图像混沌加密算法。该算法引入小波变换,可以有效地克服一些混沌加密算法不能抵御已知/选择明文攻击的缺陷。     

连续小波变换在函数空间中的应用

某些微分方程和相应的积分方程之间的关系被讨论；这些微分方程通过边境小波变换可被转换成相应的积分方程，它们不仅在弱收敛意义下而且在范围数收敛意义下是等价的；关于这些微分方程的讨论就与相应的积分方程的讨论联系起来。     

时频域自动识别与压制高频噪声

本文在分析张宇等及钱忠平等提出的高频噪声判别准则基础上,利用夏洪瑞等根据在窄档等频距小波分频之后识别、压制高频噪声的思路,提出在时频域将代表地震道主要能量的几个频带的平均振幅绝对值作为正常子波的平均振幅绝对值,以此来识别和压制高频噪声的异常振幅。实际处理结果表明,此法不仅可以压制高频谐振及高频突发噪声,而且可以保护弱地震反射信号不受损害。     

应用时频分析方法辨识时变系统的模态参数

应用Gabor展开及Hilbert变换进行时变线性系统模态参数的辨识。利用非平稳信号的Gabor变换将结构响应信号表示在时频面上，并通过Gabor展开重构分离模态分量，建立每一阶模态的时变线性模型。对单模态时变线性模型应用Hilbert变换来辨识随时间变化的模态频率和阻尼。通过对刚度和阻尼慢变的两自由度系统模态参数的仿真辨识验证辨识方法的有效性。仿真结果表明：本文方法为时变线性系统的模态参数辨识提供了一条新的途径。     

小波变换在光谱特征提取方面的应用

人们在处理高光谱图像时一般要对一些典型地物进行光谱分析、特征波段的提取,以便提取出最大量的有效信息,剔除无用或冗余的信息,然后再进行分类识别.采用小波变换的分析方法,选用合适的小波进行分解,根据分解后的高频分量中包含的重要信息,利用局部相邻的正负极值点找出对应于原始光谱曲线上每个吸收带的左右边界;利用局部过零点,即可比较精确的提取出各个吸收带的中心波长.该方法比传统的光谱特征提取方法更简洁、有效,实验证明为一种比较理想的光谱特征提取方法.     

H.264变换编码与量化原理及优化研究

本文分析了H.264视频编码标准中的整数变换和量化过程。H.264采用从DCT变换演化而来的4×4整数变换,使变换算法复杂度减小,同时消除了浮点运算导致的失配现象。将尺度调整融合在量化过程中,减少乘法次数,使H.264标准相对于以前的编码标准更加有效。同时通过采用SSE2指令,实现H.264变换与量化的优化算法,实验结果表明此算法有效地提高了编码速度。     

The Two-Dimensional Clifford-Fourier Transform

Recently several generalizations to higher dimension of the Fourier transform using Clifford algebra have been introduced, including the Clifford-Fourier transform by the authors, defined as an operator exponential with a Clifford algebra-valued kernel. In this paper an overview is given of all these generalizations and an in depth study of the two-dimensional Clifford-Fourier transform of the authors is presented. In this special two-dimensional case a closed form for the integral kernel may be obtained, leading to further properties, both in the L ₁ and in the L ₂ context. Furthermore, based on this Clifford-Fourier transform Clifford-Gabor filters are introduced. AMS subject classification numbers: 42B10, 30G35 Fred Brackx received a diploma degree in mathematics from Ghent University, Belgium, in 1970 and a Ph.D. degree in mathematics from the same university in 1973. Since 1984 he is professor for mathematical analysis at Ghent University and currently he is leading the Clifford Research Group. His main interests are function theory and functional analysis for functions with values in quaternion and Clifford algebras. The research covers Clifford distributions, generalized Fourier, Radon and Hilbert transforms, orthogonal polynomials and multi-dimensional wavelets. Nele De Schepper received a diploma degree in mathematics from Ghent University, Belgium, in 2001. Since then she holds an assistantship at the Department of Mathematical Analysis of Ghent University and is a member of the Clifford Research Group. Her main interests are function theory and functional analysis for functions with values in Clifford algebras. The research covers generalized Fourier transforms, orthogonal polynomials and multi-dimensional wavelets. Frank Sommen received a diploma degree in mathematics from Ghent University, Belgium, in 1978, a Ph.D. degree in mathematics from the same university in 1980, and a habilitation degree in mathematical analysis in 1984. From 1978 until 1999 he was at the National Fund for Scientific Research (Flanders). Since 2000 he holds a Research professorship at Ghent University. His main interests are function theory and functional analysis for functions with values in quaternion and Clifford algebras. The research covers Clifford distributions, generalized Fourier, Radon and Hilbert transforms, orthogonal polynomials and multi-dimensional wavelets, algebraic analysis, hyperfunctions and radial algebra.     

信号的小波尺度-频率表示及其在机械故障诊断中的应用

基于对信号的连续小波变换特点的分析，提出信号特征的小波尺度一频率表示方法。该方法对污染的脉冲信号和正弦信号的应用结果表明该方法能有效提取强噪声背景下的周期成分。以变速器齿轮的故障诊断为例，用该方法对变速箱齿轮振动信号的尺度-频率表示进行分析，结果表明该方法能非常有效地将不同磨损状况的齿轮振动信号的特征表现出来。     

基于子波域空间相关的多分辨图像滤波方法

从静态子波变换入手,提出了一种有效的图像滤波算法。通过计算相邻尺度下细节信号的空间相关性来区分噪声和信号,如果子波系数的空间相关性大,则认为此位置的系数含有特征及边缘信息予以保留。实现这种理论的完整方法包括两部分:空间滤波和子波收缩。仿真结果表明这个算法有很好的降噪性能。     

电力系统谐波检测的现状与发展

准确、实时地对电力系统谐波进行检测有着重要的意义。本文根据电力系统谐波测量的基本方法，对近年来电力系统谐波检测的新方法进行了分析和评述。最后对电力系统的谐波测量进行了总结并提出了看法。