FIR完全重建滤波器组构造双正交小波基

本文论述了由双正交完全重建滤波器组构造高度正则的双正交小波基的充分条件和构造方法，系统地研究了双正交线性相位ＦＩＲ完全重建滤波器组的解的结构和已知Ｈ０（ｚ）构造完全重建滤波器组的方法，并且实现了用单一的传递函数Ａ（ｚ）构造线性相位ＦＩＲ双正交完全重建滤波器组的设计方法。这种方法的突出优点是滤波器组分析、合成部分中的滤波器可以用数值优化的方法使两者同时逼近理想低通滤波器和理想高通滤波器，即具有良好的频率选择性，并且所有滤波器都具有线性相位的特点。该滤波器组具有良好的梯形实现结构。在具体的滤波器设计中提出了基于均方误差最小准则的特征滤波器的设计方法和基于误差最大值最小准则的Ｒｅｍｅｚ交换法。而且上述方法设计的滤波器组可以构造出具有高度正则性的光滑的双正交小波基。     

多小波预滤波器设计中初始滤波器的快速算法

针对多小波矢量预处理滤波器设计中计算初始滤波器Q(0)过程复杂的问题,文章提出了一种基于零空间的快速计算方法,只要给出多小波的尺度和小波滤波器的系数,就可快速准确地计算出Q(0)值.文中计算了对应GHM和CL多小波的Q(0)值,计算结果与传统方法相同,证明了方法的正确性.整个过程耗时不到0.03秒,并且避免了繁琐推导计算过程中可能出现的人为误差.     

双正交小波提升系数的递推算法与实现

根据双正交小波提升格式的特点,为了得到快速提升小波变换的系数,提出求解提升系数的递推算法。该方法基于前向小波变换的预测和更新过程的递推式,与给定双正交小波滤波器比较系数,求得小波提升系数和尺度系数。实例证明,无论是先预测后更新的提升格式,还是先更新后预测的提升格式,均可用此法求解提升系数。在Matlab7.0平台上,用递推算法编程实现db5.3小波转换成提升格式,完成图像的三级分解。     

低剂量X射线CT重建算法仿真分析

对Shepp-Logan头部图像模型提供的原始图像进行低剂量X射线计算机断层成像（CT,Computed Tomography）平移/旋转扫描,利用所得数据对图像的统计重建算法进行仿真。将仿真结果与传统的滤波反投影重建算法的重建结果进行比较,并分别将两种算法的重建图像与原图像进行比较。通过比较得出,滤波反投影重建算法不能有效重建低剂量CT图像,而统计重建算法重建效果优于前者,能够较好地恢复原图像,从而能够适用于低剂量条件下的CT图像重建。     

特征空间分解算法分析与仿真

卫星导航信号为扩频信号,比接收机热噪声低20~30dB,极易受到干扰,因此,研究卫星导航系统接收机的抗干扰能力显得极为重要。特征空间算法是一种有效的自适应抗干扰算法,目前广泛应用于抗干扰接收机中。首先建立了阵列信号基本模型,然后介绍了阵列信号特征分解原理,对其性能进行分析,并由计算机仿真证明了该算法的有效性。     

Adaptive Algorithms for Generalized Eigenvalue Decomposition with a Nonquadratic Criterion

In this papers we propose a nonquadratic criterion to solve the Generalized eigenvalue decomposi- tion （GED） problem. This criterion exhibits a single global maximum that is attained if and only if the weight matrix spans the principal generalized subspace. The other sta- tionary points of this criterion are （unstable） saddle points. Since the criterion is nonquadratics it has a steep landscape ands therefores yields fast gradient-based algorithms. Ap- plying the projection approximation method and Recursive least squares （RLS） technique, we develop an adaptive al- gorithm with low computational complexity to track the principal generalized subspace, as well as an adaptive algo- rithm to parallely estimate the principal generalized eigen- vectors. Numerical results are provided to corroborate the proposed studies.     

An Efficient Architecture for a Lifted 2D Biorthogonal DWT

This paper presents a new algorithm for a 2D non-separable lifted bi-orthogonal wavelet transform. The algorithm is derived by factoring complementary pairs of wavelet transform 2D filters. The results are efficient architectures for real time signal processing, which do not require transpose memory for the 2D processing of data. The proposed architecture exploits in place implementation, inherit from the algorithm, and can take advantage of both vertical and horizontal parallelism in the direct implementation. The processing in our architecture is scheduled by carefully pipelining the lifted steps, which allows for up to four times faster processing than the direct implementation. The proposed architecture operates at high speed, consumes low power and has reduced computational complexity as compared to previously published filter and lifted based bi-orthogonal wavelet architectures.M. Alam (Student) is currently M.Sc. student in the Department of Electrical and Computer Engineering at University of Calgary. His research interest includes VLSI signal processing. He is recipient of iCORE International Graduate Scholarship.Wael Badawy (Ph.D. 00, M.Sc 98, 97; B.Sc. 94) is an associate professor in the Department of Electrical and Computer Engineering. He holds an adjunct professor in the Department of Mechanical Engineering, University of Alberta.Dr. Badawys research interests are in the areas of: Microelectronics, VLSI architectures for video applications with low-bit rate applications, digital video processing, low power design methodologies, and VLSI prototyping. His research involves designing new models, techniques, algorithms, architectures and low power prototype for novel system and consumer products. Dr. Badawy authored and co-authored more than 100 peer reviewed Journal and Conference papers and about 30 technical reports. He is the Guest Editor for the special issue on System on Chip for Real-Time Applications in the Canadian Journal on Electrical and Computer Engineering, the Technical Chair for the 2002 International Workshop on SoC for real-time applications, and a technical reviewer in several IEEE journals and conferences. He is currently a member of the IEEE-CAS Technical Committee on Communication. Dr. Badawy was honored with the 2002 Petro Canada Young Innovator Award, 2001 Micralyne Microsystems Design Award and the 1998 Upsilon Pi Epsilon Honor Society and IEEE Computer Society Award for Academic Excellence in Computer Disciplines. He is currently the Chairman of the Canadian Advisor Committee (CAC) and Head of the Canadian Delegation on ISO/IEC/JTC1/SC6 Telecommunications and Information Exchange Between Systems. Member, The Canadian Advisory Committee for the Standards Council of Canada-Subcommittee 29: Coding of Audio, Picture Multimedia and Hypermedia Information, and Canadian Delegate, The ISO/IEC MPEG standard committee. He is a voting Member on the VSI Alliance. He is also the Chair of the IEEE-Southern Alberta Society-Computer Chapter.Vassil S. Dimitrov was born in Plovdiv, Bulgaria, in 1964. He received his Ph.D. degree in mathematics in 1995 from the Mathematical Institute of the Bulgarian Academy of Sciences. Since then, he has spent two years as a postdocral fellow at the VLSI Research Group, University of Windsor, Canada, one year as a research scientist at the Reliable Software Technology Corporation, Virginia, USA, one year as a chief research scientist at the Signal Processing and Computer Technology Laboratory, Helsinki University of Technology, Finland, and one year as an Associate Professor at the University of Windsor, Canada. Since July 2001 he has held the position of Associate Professor at the Department of Electrical and Computer Engineering, University of Calgary, Canada. His main interests are in the area of number theoretic algorithms, computational complexity, cryptography, optimization theory, fast algorithms for digital signal processing and related topics. Dr. Dimitrov is a member of the New York Academy of Sciences.Graham Jullien (Fellow IEEE) was educated in the United Kingdom, receiving degrees, in Electrical Engineering, from the Universities of Loughborough, Birmingham and Aston (Ph.D., 1969). He was a student engineer and data processing engineer at English Electric Computers, UK, from 1961 to 1966, and a visiting senior research engineer at the Central Research Laboratories of EMI Ltd., UK, from 1975 to 1976. From 1969 until 2000 he was with the Department of Electrical and Computer Engineering at the University of Windsor, Ontario, Canada, where he held the rank of University Professor and was the Director of the VLSI Research Group. Since January 2001, he has been with the Department of Electrical and Computer Engineering at the University of Calgary, where he holds the iCORE Research Chair in Advanced Technology Information Processing Systems. He is a member of the Board of Directors of the Canadian Microelectronics Corporation (CMC) and is a member of the Steering Committee and Board of Directors of the Micronet Network of Centres of Excellence. He has published widely in the fields of Digital Signal Processing, Computer Arithmetic, Neural Networks and VLSI Systems, and teaches courses in related areas. He has served on the technical committees of many international conferences; he currently serves on the Editorial Board of the Journal of VLSI Signal Processing; and is a past Associate Editor of the IEEE Transactions on Computers. He hosted and was program co-chair of the 11th IEEE Symposium on Computer Arithmetic, was program chair for the 8th Great Lakes Symposium on VLSI, and was the technical program chair for the 1999 Asilomar Conference on Signals, Systems and Computers. He is general chair for the 2003 Asilomar Conference and general co-chair of the International Workshop on System-on-Chip for Real-Time Systems, Calgary, Alberta 2003.     

基于小波分解和支持向量机的网络流量组合预测

研究网络流量预测问题,网络流量具有突发性、周期性、非线性特点,传统网络流量预测模型无法建立准确预测模型,导致预测误差大,预测精度低.为了提高网络流量的预测精度,提出一种小波分解和支持向量机的网络流量预测模型.首先采用小波变换对网络流量进行分解,把网络流量不同特性成分分离出来,然后采用支持向量机对各分量进行预测,最后采用小波变换对各分量预测结果进行重构,得到网络流量的最终预测结果.仿真实验结果表明,相对其它预测模型,提高了网络流量的预测精度,为网络流量预测优化提供了可靠依据.     

移动对象全局K最接近邻居查询研究

基于两个对象在一段时间内的范围距离度量,给出了一种新的时空查询形式-全局最接近邻居查询。该查询检索移动对象在一段时间内范围距离最小的运动对象。通过考察查询和连续最接近邻居之间关系,给出了一个基本查询处理算法。根据数据对象集的运动性不同,精化了运动和静止数据集下的全局距离的定义,并对R树结构索引的数据集给出了裁减、更新和访问启发式规则。采用分支界定技术和给出的启发式规则,设计了迭代的深度优先和基于堆的最好优先的查询处理算法。大量的实验表明,最好优先的查询处理算法具有突出的性能。     

Methodology and Algorithms for Planning Cost-Effective High Survivability SDH Networks

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Error Free Butcher Algorithms for Linear Electrical Circuits

In this paper, an error‐free Butcher algorithm is introduced to study the singular system of a linear electrical circuit for time invariant and time varying cases. The discrete solutions obtained using Runge‐Kutta (RK)‐Butcher algorithms are compared with the exact solutions of the electrical circuit problem and are found to be very accurate. Stability regions for the single term Walsh series (STWS) method and the RK‐Butcher algorithm are presented. Error graphs for inductor currents and capacitor voltages are presented in a graphical form to show the efficiency of the RK‐Butcher algorithm. This RK‐Butcher algorithm can be easily implemented in a digital computer for any singular system of electrical circuits.     

基于小波分解和支持向量机的准正面人脸识别方法

基于小波分解提取人脸特征技术和多分类支持向量机模型，提出了一种新的准正面人脸识别算法。小波分解提取人脸特征具有对表情变化不敏感的特点；支持向量机作为分类器被认为具有很高的推广(generalization)性能，无需先验知识。在所提出的算法中，首先对训练图像进行预处理，然后使用小波分解方法对人脸图像进行特征提取，用所提取的人脸特征向量训练多分类支持向量机模型，最后用训练好的支持向量机进行人脸识别。利用ORL人脸图像库对该算法的实验测试结果，以及与其它人脸识别方法的比较结果表明了该算法在识别性能方面的优越性。     

Real-Time Simultaneous Estimation and Decomposition of Random Signals

In this paper, an efficient algorithm is derived for multiresolutional estimation and decomposition of noisy random signals. This algorithm performs in real-time the estimation and decomposition simultaneously, using the discrete wavelet transform implemented by a filter bank. Although the algorithm is developed based on the standard Kalman filtering scheme, the nature of blockwise filtering results in a smoothing-equivalent effect. However, the interpolated filtering produces decomposed estimate output in real-time.     

基于极化分解的舰船和角反射器鉴别方法

使用角反射器是舰船电子对抗中常用的一种无源干扰方式,它在时域、频域和空域上与舰船的雷达回波都没有显著差异,因此传统单极化雷达很难有效鉴别舰船和角反射器。分析了舰船和角反射器在极化回波上的特性差异,并基于Krogager极化分解提取了单频点和多频点情况下的特征矢量,通过支持矢量机对舰船和角反射器进行了鉴别。电磁计算数据表明：该方法可以较好地对二者进行鉴别,且对单角反射器和阵列角反射器都有效,为解决舰船和角反射器的鉴别问题提供了一个可行的思路。     

气动光学畸变波前的本征正交分解和低阶近似

应用哈特曼波前传感器测量了准直平行光通过低速热射流流场后的畸变波前时间序列,对该波前时间序列进行了本征正交分解(POD)和低阶近似研究,对比研究了16#,1008#数据点处的低阶近似波前时间序列和测量波前时间序列。结果表明,畸变波前可用本征正交分解基来展开,应用少量的低阶本征正交分解基即可捕捉到波前的主要信息,并且随着重构模式数的增加,低阶近似波前更加逼近测量波前。由于波面上不同位置处相位脉动量的空间相关性各异,因此选用相同的重构模式数时不同数据点处的重构精度也不一样。     

人工神经网络与遗传算法的结合：进展及展望

近来，人工神经网络（ＡＮＮ）与遗传算法（ＧＡ）结合的研究引起了人们的极大注意。本文综述了这一领域的发展现状，并试图从两者的结合上分为辅助式及合作式两种结合方式，对于辅助式结合，ＧＡ不仅能为ＡＮＮ选择训练数据，也可用来选择网络的学习参数或学习规则，而且可利用ＧＡ解释或分析ＡＮＮ的结果；对于合作式结合，主要论述了ＧＡ作为ＡＮＮ的一种权重训练方法的不足和长处，同时评述了它与ＢＰ训练算法的优缺点，最后着重综述了利用ＧＡ自动优选ＡＮＮ的各种方法。     

基于小波分解和SVM的城市大气污染浓度预测

使用一种结合小波分解和支持向量机的方法建立城市大气污染物浓度预测模型。首先将大气污染物浓度数据序列小波分解和重构为不同频段的分解序列,然后对各分解序列使用不同的模型进行预测,最后将各分解序列的预测结果合成为浓度的最终预测结果。实验结果表明,该模型的预测精度优于RBF神经网络模型及一般支持向量机模型。     

Models and Approximation Algorithms for Channel Assignment in Radio Networks

We consider the frequency assignment (broadcast scheduling) problem for packet radio networks. Such networks are naturally modeled by graphs with a certain geometric structure. The problem of broadcast scheduling can be cast as a variant of the vertex coloring problem (called the distance-2 coloring problem) on the graph that models a given packet radio network. We present efficient approximation algorithms for the distance-2 coloring problem for various geometric graphs including those that naturally model a large class of packet radio networks. The class of graphs considered include (r,s)-civilized graphs, planar graphs, graphs with bounded genus, etc.     

Decomposition and compression for ECG and EEG signals with sequence index coding method based on matching pursuit

An efficient compression method is proposed by encoding the sequence index of atoms based on matching pursuit (MP)algorithm with over-complete Gabor dictionary,which has the merit to adjust the compres...     

无线网络预约退避算法的实现和分析

针对无线局域网IEEE 802.11MAC层二进制退避算法的不足,当前已经提出多种典型退避算法。主要针对预约发送类退避算法进行研究分析,并提出与EBA不同的实现措施,对NS2网络仿真软件的Mac802.11模块进行了修改和扩展,实现了NS2对改进的预约退避算法的实现。结果表明,与标准DCF相比,改进的预约退避算法也能对IEEE802.11无线局域网的吞吐量、时延等方面性能有所改善。为今后基于NS2对预约退避算法的进一步开发研究奠定基础。