Wavelets and Wavelet Packets Related to a Class of Dilation Matrices

The construction of wavelets generated from an orthogonal multiresolution analysis can be reduced to the unitary extension of a matrix, which is not easy in most cases. Jia and Micchelli gave a solution to the problem in the case where the dilation matrix is 21 and the dimension does not exceed 3. In this paper, by the method of unitary extension of a matrix, we obtain the construction of wavelets and wavelet oackets related to a class of dilation matrices.     

Orthogonal Matrix-Valued Wavelet Packets

In this paper, we introduce matrix-valued multiresolution analysis and matrix- valued wavelet packets. A procedure for the construction of the orthogonal matrix-valued wavelet packets is presented. The properties of the matrix-valued wavelet packets are investigated. In particular, a new orthonormal basis of L2(R, Cs×s) is obtained from the matrix-valued wavelet packets.     

The spectrum sequences of periodic frame multiresolution analysis

The periodic multiresolution analysis （PMRA） and the periodic frame multiresolution analysis （PFMRA） provide a general recipe for the construction of periodic wavelets and periodic wavelet frames, respectively. This paper addresses PFMRAs by the introduction of the notion of spectrum sequence. In terms of spectrum sequences, the scaling function sequences generating a normalized PFMRA are characterized; a characterization of the spectrum sequences of PFMRAs is obtained, which provides a method to construct PFMRAs since its proof is constructive; a necessary and sufficient condition for a PFMRA to admit a single wavelet frame sequence is obtained; a necessary and sufficient condition for a PFMRA to be contained in a given PMRA is also obtained. What is more, it is proved that an arbitrary PFMRA must be contained in some PMRA. In the meanwhile, some examples are provided to illustrate the general theory.     

N维M进制广义多尺度分析及其应用

In this paper,we extend the generalized multiresolution analysis(GMRA)to higher dimensional spaces.The GMRA is generalized from each ladder spaceexpanded by a different scaling function with positive integer dilation factor m≥2.The n-d GMRA is discussed in orthogonal and bi-orthogonal cases.Then the optimalm-band wavelets are applied in processing the image datasets of the human bodyslices.The efficiency and superiority of the algorithm can be seen from the processingresults.     

COMPACTLY SUPPORTED BOX-SPLINE WAVELETS

A general procedure for constructing multivariate non-tensor-product wavelets that gen-erate an orthogonal decomposition of L~2(R~),s≥ 1,is described and applied to yield explicitformulas for compactly supported spline-wavelets based on the multiresolution analysis ofL~2(R~s),1≤s≤3,generated by any box spline whose direction set constitutes a unimodularmatrix.In particular,when univariate cardinal B-splines are considered,the minimally sup-ported cardinal spline-wavelets of Chui and Wang are recovered.A refined computationalscheme for the orthogonalization of spaces with compactly supported wavelets is given.Arecursive approximation scheme for“truncated”decomposition sequences is developed and asharp error bound is included.A condition on the symmetry or anti-symmetry of the waveletsis applied to yield symmetric box-spline wavelets.     

A Semi-Conjugate Matrix Boundary Value Problem for General Orthogonal Polynomials on an Arbitrary Smooth Jordan Curve

In this article, the author characterizes orthogonal polynomials on an arbitrary smooth Jordan curve by a semi-conjugate matrix boundary value problem, which is different from the Riemann-Hilbert problems that appear in the theory of Riemann -Hilbert approach to asymptotic analysis for orthogonal polynomials on a real interval introduced by Fokas, Its, and Kitaev and on the unit circle introduced by Baik, Deift, and Johansson. The author hopes that their characterization may be applied to asymptotic analysis for general orthogonal polynomials by combining with a new extension of steepest descent method which we are looking for.     

Biorthogonal multiple wavelets generated by vector refinement equation

Biorthogonal multiple wavelets are generated from refinable function vectors by using the multiresolution analysis.In this paper we provide a general method for the construction of compactly supported biorthogonal multiple wavelets by refinable function vectors which are the solutions of vector refinement equations of the form (?)(x)=(?)a(α)(?)(Mx-α),x∈R~s, where the vector of functions(?)=((?)_1,...,(?)_r)~T is in(L_2(R~s))~r,a=:(a(α))_(α∈Z~s)is a finitely supported sequence of r×r matrices called the refinement mask,and M is an s×s integer matrix such that lim_(n→∞)M~(-n)=0.Our characterizations are in the general setting and the main results of this paper are the real extensions of some known results.     

MULTIRESOLUTIONS AND PRIMITIVES

In wavelet theory smootheness is one of the main interests. By the Mallat-Meyer construction (see [He] or [Ne]) the problem of finding smooth wavelets is reduces to finding smooth scaling functions of multiresolu-tims. From a given scaling function g a smoother one can be made by taking convolution with e. g. the characteristic function of [0,1]. In this article a characterisation of the multiresolution generated by that convolution-will be given by means of primitives of functions in the multiresolution generated by g. From this , the spline muhtresolutiom follow as a special case.     

MULTIRESOLUTION ANALYSIS, SELF-SIMILAR TILINGS AND HAAR WAVELETS ON THE HEISENBERG GROUP

In this article, the properties of multiresolution analysis and self-similar tilings on the Heisenberg group are studied. Moreover, we establish a theory to construct an orthonormal Haar wavelet base in L^2（H^d） by using self-similar tilings for the acceptable dilations on the Heisenberg group.     

A Construction of Multiresolution Analysis on Interval

We present a concrete method of constructing multiresolution analysis on interval. The method generalizes the corresponding results of Cohen, Daubechies and Vial [Appl. Comput. Harmonic Anal., 1（1993）, 54-81]. By the use of the subdivision operator, the expressions of the constructed functions are more compact. Furthermore, the method reveals more clearly some properties of multiresolution analysis with certain approximation order.     

矩阵值函数空间中尺度空间的稠密性

多分辨分析的概念在小波基构造中起着非常重要的作用,并经历了从经典多分辨分析到多重多分辨分析,再到矩阵值多分辨分析的研究历程.本文基于矩阵值多分辨分析,研究并给出了矩阵值函数空间中尺度空间稠密性的两个充要条件,并在此基础之上得到了稠密性的两个充分条件.     

向量值正交小波的构造与向量值小波包的特征

The notion of vector-valued multiresolution analysis is introduced and the concept of orthogonal vector-valued wavelets with 3-scale is proposed.A necessary and sufficient condition on the existence of orthogonal vector-valued wavelets is given by means of paraunitary vector filter bank theory.An algorithm for constructing a class of compactly supported orthogonal vector-valued wavelets is presented.Their characteristics is discussed by virtue of operator theory,time-frequency method.Moreover,it is shown how to design various orthonormal bases of space L2(R,Cn) from these wavelet packets.     

多尺度紧支撑向量值正交小波的构造

引入了多尺度向量值多分辨分析．利用矩阵理论,给出多尺度紧支撑向量值正交小波存在的必要条件及其构造方法．     

分数阶尺度函数的分解与重构算法

引入分数阶多分辨分析与分数阶尺度函数的概念.运用时频分析方法与分数阶小波变换,研究了分数阶正交小波的构造方法,得到分数阶正交小波存在的充要条件.给出分数阶尺度函数与小波的分解与重构算法,算法比经典的尺度函数与小波的分解与重构算法更具有一般性.     

Finite orthogonal transforms and multiresolution analyses on intervals

A class of fast orthogonal transformations for finite strings of data are described. These transformations are based on the multiresolution analysis paradigm of Mallat and Meyer and give rise to a method for constructing multiresolution analyses and orthogonal wavelets on an interval. Mathematical details and numerical examples are included.     

Construction and decomposition of biorthogonal vector-valued wavelets with compact support

In this article, we introduce vector-valued multiresolution analysis and the biorthogonal vector-valued wavelets with four-scale. The existence of a class of biorthogonal vector-valued wavelets with compact support associated with a pair of biorthogonal vector-valued scaling functions with compact support is discussed. A method for designing a class of biorthogonal compactly supported vector-valued wavelets with four-scale is proposed by virtue of multiresolution analysis and matrix theory. The biorthogonality properties concerning vector-valued wavelet packets are characterized with the aid of time–frequency analysis method and operator theory. Three biorthogonality formulas regarding them are presented.     

A study on orthogonal two-direction vector-valued wavelets and two-direction wavelet packets

In this paper, the notion of two-direction vector-valued multiresolution analysis and the two-direction orthogonal vector-valued wavelets are introduced. The definition for two-direction orthogonal vector-valued wavelet packets is proposed. An algorithm for constructing a class of two-direction orthogonal vector-valued compactly supported wavelets corresponding to the two-direction orthogonal vector-valued compactly supported scaling functions is proposed by virtue of matrix theory and time-frequency analysis method. The properties of the two-direction vector-valued wavelet packets are investigated. At last, the direct decomposition relation for space L₂(R)^r is presented.     

A study on compactly supported orthogonal vector-valued wavelets and wavelet packets

In this paper, vector-valued multiresolution analysis and orthogonal vector-valued wavelets are introduced. The definition for orthogonal vector-valued wavelet packets is proposed. A necessary and sufficient condition on the existence of orthogonal vector-valued wavelets is derived by means of paraunitary vector filter bank theory. An algorithm for constructing a class of compactly supported orthogonal vector-valued wavelets is presented. The properties of the vector-valued wavelet packets are investigated by using operator theory and algebra theory. In particular, it is shown how to construct various orthonormal bases of L²(R, C^s) from the orthogonal vector-valued wavelet packets.     

The properties of orthogonal matrix-valued wavelet packets in higher dimensions

In the paper matrix-valued multiresolution analysis and matrix-valued wavelet packets of spaceL ²(R ⁿ ,C ^{s x s}) are introduced. A procedure for constructing a class of matrix-valued wavelet packets in higher dimensions is proposed. The properties for the matrix-valued multivariate wavelet packets are investigated by using integral transform, algebra theory and operator theory. Finally, a new orthonormal basis ofL ²(R ⁿ ,C ^{s x s}) is derived from the orthogonal multivariate matrix-valued wavelet packets.