关于共轭滤波器

小波分析里，起关键作用的是共轭滤波器。本文证明了Ｄａｕｂｅｃｈｉｅｓ的│ＨＮ（ω）│＾２与Ｍｅｙｅｒ的│ＨＮ（ω）│＾２有相同的极限。并根据其极限给出了一种新的滤波器Ｈ↑￣（ω），证明了Ｎψ（ω）几乎处处收敛于ψ↑￣（ω）。     

Egocentric Object Manipulation in Virtual Environments: Empirical Evaluation of Interaction Techniques

The acceptance of virtual environment (VE) technology requires scrupulous optimization of the most basic interactions in order to maximize user performance and provide efficient and enjoyable virtual interfaces. Motivated by insufficient understanding of the human factors design implications of interaction techniques and tools for virtual interfaces, this paper presents results of a formal study that compared two basic interaction metaphors for egocentric direct manipulation in VEs, virtual hand and virtual pointer, in object selection and positioning experiments. The goals of the study were to explore immersive direct manipulation interfaces, compare performance characteristics of interaction techniques based on the metaphors of interest, understand their relative strengths and weaknesses, and derive design guidelines for practical development of VE applications.     

Supercompact multiwavelets for flow field simulation

A supercompact multiwavelet scheme for computational fluid dynamics is presented. Beam and Warming's supercompact wavelet method is an appropriate wavelet for fluid simulation data in the sense that it can provide compact support. The compactness of the wavelets avoids unnecessary interaction with remotely located data (e.g. across a shock discontinuity or vortex) and significantly reduces computational data processing time. Thresholding for data compression with the supercompact wavelets is applied based on a covariance vector structure of multiwavelets. The extension of this scheme to three dimensions is analyzed. Numerical tests demonstrate that the analytic advantages actually result in large data compression ratios.     

Performance of quasisynchronous scale time code division multiple access for AWGN channel

We analyze bit error rate performance of a recently proposed multiple access system called scale time code division multiple access (STCDMA) for quasisynchronous communication over an AWGN channel. STCDMA depends on code, time and scale orthogonality introduced by spreading sequences and wavelets. Wavelets are employed as an orthogonal set of symbols for signaling, and their orthogonality over scale and time is exploited. The channel is partitioned into different scales, and each scale into different time slots. Each user is assigned a specific scale, time slot, and spreading code. Information symbols of each user are encoded by the Haar wavelet in its scale and time slot, and then they are spread by its spreading code. Complex-valued Hadamard sequences are used as spreading sequences and conventional detector (i.e. matched filter) is used at the receiver. Results show that the performance of STCDMA gets much better than that of CDMA over the quasisynchronous AWGN channel as the number of scales increases.     

时变非线性分布参数控制系统的小波辨识算法

基于正交函数逼近理论,在Haar小波正交规范基的基础上,总结并推导出了其积分运算矩阵、微分运算矩阵、乘积运算矩阵及其运算性质,并应用于一类时变非线性分布参数系统的辨识.借助于正交小波函数逼近方法对分布参数系统进行辨识,经正交小波逼近变换转化为代数矩阵方程,因此该方法可以不考虑初始条件和边界条件,较其他辨识方法要简单得多.该算法简单、计算量小、简化了分布参数系统辨识的求解过程,应用在分布参数系统辨识中不失为一种有效的分析方法.     

Impact identification on a sandwich plate from wave propagation responses

This study investigates the use of an impact detection algorithm to locate a potentially damaging impact on an orthotropic plate by detecting the stress waves generated by such an event. The proposed algorithm was tested experimentally on a sandwich plate by using ultrasonic signals. The arrival times of stress waves at different frequencies at the sensor locations were determined by analyzing the recorded signals using the wavelet transforms. The stress wave propagation phenomenon was characterized by measuring the propagation speeds along different directions. This data along with the sensor co-ordinates were input into the impact detection algorithm, which uses the difference in time of flight to the sensors and trigonometric identities to locate impact source locations. The accuracy of the method was demonstrated by the close agreement observed between the estimated locations for the three impact locations studied with the actual locations of the impact loads applied. In particular, maximum error in the estimation of the co-ordinates of the impact location was less than 9% for all different types of loading considered.     

基于时频等高图的汽轮发电机组振动故障诊断方法研究

状态监测与故障诊断的主要内容包括故障信号的检测、故障诊断、趋势分析和早期故障预测即预测诊断等。传统的振动故障诊断主要是基于频谱分析的方法，小波变换得出的时频等高图是分析故障信号奇异性的有效工具，为汽轮发电机组的故障检测和诊断提供了新思路。在介绍小波变换理论、Morlet小波和时频等高图的基础上，通过对仿真的汽轮发电机组几种典型振动故障，如不对中、油膜涡动和部件松动等信号进行分析，结果表明时频等高图不仅能够直观检测出信号中的微弱奇异成分，而且还可以有效地对故障进行分类诊断、实现早期故障检测和故障变化趋势分析等。最后，采用时频等高图分析了3种实际机组的振动异常信号。     

Image denoising with neighbour dependency and customized wavelet and threshold

Image denoising by means of wavelet transforms has been an active research topic for many years. For a given noisy image, which kind of wavelet and what threshold we use should have significant impact on the quality of the denoised image. In this paper, we use Simulated Annealing to find the customized wavelet filters and the customized threshold corresponding to the given noisy image at the same time. Also, we propose to consider a small neighbourhood around the customized wavelet coefficient to be thresholded for image denoising. Experimental results show that our approach is better than VisuShrink, our NeighShrink with fixed wavelet, and the wiener2 filter that is available in Matlab Image Processing Toolbox. In addition, our NeighShrink with fixed wavelet already outperforms VisuShrink for all the experiments.     

Bayesian wavelet denoising and evolutionary calibration

Wavelet shrinkage estimation has become an attractive and efficient method for signal denoising and compression. Despite the ample variety of methods which have been used in the wavelet denoising context, it has proven elusive to construct threshold estimators with good adaptive properties. Recently, empirical Bayes selection criteria have been proposed to derive adaptive shrinkage estimators. We consider the application of empirical Bayes variable selection criteria to each level of the wavelet transform to obtain adaptive threshold estimates. A set of level-dependent hyperparameters has to be estimated to derive nonlinear data-dependent thresholding rules. We propose the use of an evolutionary algorithm to calibrate the multilevel parameters, in order to automate parameter selection and enhance adaptivity of the threshold estimators. Comparative simulations on a set of standard model functions show good performance. Applications to data drawn from various fields of application are used to explore the practical performance of the proposed approach.     

A wavelet-based image fusion tutorial

The objective of image fusion is to combine information from multiple images of the same scene. The result of image fusion is a new image which is more suitable for human and machine perception or further image-processing tasks such as segmentation, feature extraction and object recognition. Different fusion methods have been proposed in literature, including multiresolution analysis. This paper is an image fusion tutorial based on wavelet decomposition, i.e. a multiresolution image fusion approach. We can fuse images with the same or different resolution level, i.e. range sensing, visual CCD, infrared, thermal or medical. The tutorial performs a synthesis between the multiscale-decomposition-based image approach (Proc. IEEE 87 (8) (1999) 1315), the ARSIS concept (Photogramm. Eng. Remote Sensing 66 (1) (2000) 49) and a multisensor scheme (Graphical Models Image Process. 57 (3) (1995) 235). Some image fusion examples illustrate the proposed fusion approach. A comparative analysis is carried out against classical existing strategies, including those of multiresolution.