双正交多重小波的一种构造方法

多重小波是近年来新兴的小波研究方向,它具有许多一维小波所不具备的优越性质．完全正交的多重小波在构造上有很大的难度,所以在许多应用中人们都可以用双正交多重小波作为分析的工具     

多尺度多重向量值双正交小波的构建算法与性质

研究多尺度多重向量值双正交小波的构建算法与性质.运用向量细分格式、矩阵理论和多重向量值多分辨分析,证明了与一对给定的多尺度多重向量值双正交尺度函数对应的多尺度多重向量值双正交小波函数的存在性.提出了紧支撑多尺度多重向量值双正交小波的构造算法.讨论了多尺度多重向量值小波包的性质,得到了多重向量值小波包的双正交公式与向量值小波包基.     

利用提升格式构造稳定的对偶小波

近年来 ,产生了一种称为“提升格式”的新的小波构造方法 [7,8,9] ,它从一个较简单的多尺度分析 (MRA)出发 ,利用尺度函数相同的多尺度分析之间的相互关系 ,逐步地得到所需性质的多尺度分析 .本文仅考虑双正交滤波的提升格式 .当选定一初始双正交滤波后 ,利用提升格式构造的双正交滤波仍是双正交的 ,而这双正交滤波能否生成双正交小波 Riesz基即稳定的对偶小波 ?更进一步 ,如何从一些较为简单的不能生成双正交小波 Riesz基的双正交滤波出发 ,利用提升格式构造出具有 Riesz基性质的双正交滤波 ?这在目前有关提升格式的文章中没作回答 .本…     

三元双正交小波滤波器的刻画

研究由三元双正交插值尺度函数构造对应的双正交小波滤波器的矩阵扩充问题.当给定的一对三元双正交尺度函数中有一个为插值函数时,利用提升思想与矩阵多相分解方法,给出一类三元双正交小波滤波器的显示构造公式和一个计算实例.讨论了三元双正交小波包的的性质.     

不同尺度下多项式滤波器的优化算法

１　　引　言 在小波分析的应用中,紧支撑正交对称的小波是非常可贵的．尤其是对称性,它在实际应用中具有非常重要的意义．但Daubechies的具有紧支撑正交小波无任何对称性和反对称性（除Haar小波外）．为了克服这一不足,崔锦泰和王建忠［１］提出了样条小波,样条小波用失去正交性换来了小波的对称性．A.Cohen［２］等引入了双正交小波似乎解决了这一问题,但它需要两个对偶的小波．匡正［３］等采用了小波的分式滤波器构造出了既正交又对称的小波,但却没有有限的支撑区间．本文欲采用优化的方法给出了一种构造具有任意正则性的多项式…     

区间[-1，1]上的α尺度双正交多小波的构造

本文研究了一元α尺度紧支撑、双正交多小波的构造．在区间[-1，1]，给出了利用α尺度双正交尺度向量构造α尺度双正交多小波的推导过程得到了一种有效的小波构造算法，并给出了数值算例．     

一类周期小波的局部性质

在文献[1]中,陈翰麟等构造了一类具有很好性质的周期小波．我们在这篇论文中进一步研究了该类周期小波,证明了它们在一个周期内具有局部性质．     

离散超小波变换下双正交小波谱分析

在离散超小波交换下，双正交小波交换矩阵的谱是有界的，我们给出一个确定的界．任何一个双正交小波变换矩阵的谱不可能分布在1附近的某个开区间内，我们给出该区间估计，从而证明了任何一个双正交小波族变换矩阵的谱不可能无限接近于1（正交小波交换矩阵的谱）．     

一类离散型4-带对称双正交小波

本文给出了一类具有对称4-进双正交小波的构造,该小波类可以由它的低通滤波器确定,因此,其自由度可以运用到应用背景,并且研究了变换矩阵的性质,为应用提供了大量选择.     

离散超小波变换下双正交小波谱分析

我们研究发现，在离散超小波变换下双正交小波谱是有界的．并且任何一个双正交小波变换的谱不可能分布在1附近的某个区间内，并给出了该区间的一个估计．     

双正交小波滤波器簇代数结构及构造

研究了一类向量多项式两种特殊分解结构,由此引进了与双正交小波滤波器簇相应的多相向量概念,分析了多相向量分解代数结构,得到了在低通滤波器给定条件下,满足任意阶可和规则的对偶低通滤波器构造方法.分析并证明了双正交滤波器簇对应多相向量至多具有的3种代数分解结构,根据其分解的形式得到了双正交小波基构造的新方法,该方法便于双正交小波构造计算机程序化.     

三进制双正交对称小波的设计

本文给出了一种三进制双正交对称小波的设计方法.在给定插值紧支撑对称尺度函数的情况下,指出了如果对偶尺度函数同为紧支撑插值的,则它们同为1-型对称.并且给出了对偶尺度函数为紧支撑插值和非插值情况下的通解计算公式.还提出了频率优化方法设计对偶尺度函数和小波函数,把双正交条件归结为线性约束的二次规划问题,最后通过线性方程组来求解.对于小波函数本文也给出了一组特解公式.     

Refinable Functions with Exponential Decay: An?Approach via Cascade Algorithms

Refinable functions with exponential decay arise from applications such as the Butterworth filters in signal processing. Refinable functions with exponential decay also play an important role in the study of Riesz bases of wavelets generated from multiresolution analysis. A fundamental problem is whether the standard solution of a refinement equation with an exponentially decaying mask has exponential decay. We investigate this fundamental problem by considering cascade algorithms in weighted L _p spaces (1≤p≤∞). We give some sufficient conditions for the cascade algorithm associated with an exponentially decaying mask to converge in weighted L _p spaces. Consequently, we prove that the refinable functions associated with the Butterworth filters are continuous functions with exponential decay. By analyzing spectral properties of the transition operator associated with an exponentially decaying mask, we find a characterization for the corresponding refinable function to lie in weighted L ₂ spaces. The general theory is applied to an interesting example of bivariate refinable functions with exponential decay, which can be viewed as an extension of the Butterworth filters.     

Tree wavelet approximations with applications

We construct a tree wavelet approximation by using a constructive greedy scheme (CGS). We define a function class which contains the functions whose piecewise polynomial approximations generated by the CGS have a prescribed global convergence rate and establish embedding properties of this class. We provide sufficient conditions on a tree index set and on bi-orthogonal wavelet bases which ensure optimal order of convergence for the wavelet approximations encoded on the tree index set using the bi-orthogonal wavelet bases. We then show that if we use the tree index set associated with the partition generated by the CGS to encode a wavelet approximation, it gives optimal order of convergence.     

Designing Multiresolution Analysis-type Wavelets and Their Fast Algorithms

Often, the Dyadic Wavelet Transform is performed and implemented with the Daubechies wavelets, the Battle-Lemarie wavelets, or the splines wavelets, whereas in continuous-time wavelet decomposition a much larger variety of mother wavelets is used. Maintaining the dyadic time-frequency sampling and the recursive pyramidal computational structure, we present various methods for constructing wavelets ψ_wanted, with some desired shape and properties and which are associated with semi-orthogonal multiresolution analyses. We explain in detail how to design any desired wavelet, starting from any given multiresolution analysis. We also explicitly derive the formulae of the filter bank structure that implements the designed wavelet. We illustrate these wavelet design techniques with examples that we have programmed with Matlab routines.     

Spherical Singular Integrals, Monogenic Kernels and Wavelets on the Three-Dimensional Sphere

The construction of wavelets relies on translations and dilations which are perfectly given in . On the sphere translations can be considered as rotations but it is difficult to say what are dilations. For the 2-dimensional sphere there exist two different approaches to obtain wavelets which are worth to be considered. The first concept goes back to W. Freeden and collaborators who define wavelets by means of kernels of spherical singular integrals. The other concept developed by J.P. Antoine and P. Vandergheynst is a purely group theoretical approach and defines dilations as dilations in the tangent plane. Surprisingly both concepts coincides for zonal functions. We will define singular integrals and kernels of singular integrals on the three dimensional sphere which are also approximate identities. In particular the Cauchy kernel in Clifford analysis is a kernel of a singular integral, the singular Cauchy integral, and an approximate identity. Furthermore, we will define wavelets on the 3-dimensional sphere by means of kernels of singular integrals. This paper is dedicated to the memory of our friend and colleague Jarolim Bureš Received: October, 2007. Accepted: February, 2008.     

Prolate Spheroidal Wavelets: Translation, Convolution, and Differentiation Made Easy

Prolate spheroidal wavelets were previously introduced and shown to have some interesting convergence properties. In this work, several shortcomings of standard wavelets are discussed, and are shown not to be present in these new wavelets. These include invariance under arbitrary translations and differentiation of the associated multiresolution subspaces as well as similar properties of dilations.     

Periodic Prolate Spheroidal Wavelets

Prolate spheroidal wavelets (PS wavelets) were recently introduced by the authors. They were based on the first prolate spheroidal wave function (PSWF) and had many desirable properties lacking in other wavelets. In particular, the subspaces belonging to the associated multiresolution analysis (MRA) were shown to be closed under differentiation and translation. In this paper, we introduce periodic prolate spheroidal wavelets. These periodic wavelets are shown to possess properties inherited from PS wavelets such as differentiation and translation. They have the potential for applications in modeling periodic phenomena as an alternative to the usual periodic wavelets as well as the Fourier basis.     

Periodic Wavelets from Scratch

Periodic wavelets can be constructed from most standard wavelets by periodization. In this work we first derive some of their properties and then construct the periodic wavelets directly from their Fourier series without reference to standard wavelets. Several examples are given some of which are not constructable from the usual wavelets on the real line.     

CONSTRUCTION OF REAL-VALUED MULTIVARIATE WAVELETS

In this paper, we give a method to construct multivariate wavelets for skew-symmetric scaling function. Such wavelets have some desirable properties, e.g., they are real-valued and orthogonal if the scaling function is real-valued and orthonormal respectively.