Local sampling set conditions in weighted shift-invariant signal spaces

How to represent a continuous signal in terms of a discrete sequence is a fundamental problem in sampling theory. Most of the known results concern global sampling in shift-invariant signal spaces. But in fact, the local reconstruction from local samples is one of the most desirable properties for many applications in signal processing, e.g. for implementing real-time reconstruction numerically. However, the local reconstruction problem has not been given much attention. In this article, we find conditions on a finite sampling set X such that at least in principle a continuous signal on a finite interval is uniquely and stably determined by their sampling value on the finite sampling set X in shift-invariant signal spaces.     

Invariance of shift-invariant spaces

In this paper, we give a characterization of shift-invariant subspaces which are also invariant under additional non-integer translations. Both principal and finitely generated shift-invariant subspaces are studied. Our results improve some known ones.     

Approximation from locally finite-dimensional shift-invariant spaces

After exploring some topological properties of locally finite-dimensional shift-invariant subspaces of , we show that if provides approximation order , then it provides the corresponding simultaneous approximation order. In the case is generated by a compactly supported function in , it is proved that provides approximation order in the -norm with if and only if the generator is a derivative of a compactly supported function that satisfies the Strang-Fix conditions.

     

主平移不变空间的特征

Shifts-invariant spaces in L1 (R) are investigated. First,based on a study of the system of linearly difference operators, the method of constructing generators with linearly independent shifts is provided. Then the characterizations of the closed shift-invariant subspaces in L1 (R) are given in terms of such generators and the local basis of shift-invariant subspaces.     

Exact iterative reconstruction algorithm for multivariate irregularly sampled functions in spline-like spaces: The -Theory

We prove that the exact reconstruction of a function from its samples on any ``sufficiently dense" sampling set can be obtained, as long as is known to belong to a large class of spline-like spaces in . Moreover, the reconstruction can be implemented using fast algorithms. Since a limiting case is the space of bandlimited functions, our result generalizes the classical Shannon-Whittaker sampling theorem on regular sampling and the Paley-Wiener theorem on non-uniform sampling.

     

Uncertainty principles in finitely generated shift-invariant spaces with additional invariance

We consider finitely generated shift-invariant spaces (SIS) with additional invariance in L²(R^d)$L^2({\mathbb{R}}^d)$. We prove that if the generators and their translates form a frame, then they must satisfy some stringent restrictions on their behavior at infinity. Part of this work (non-trivially) generalizes recent results obtained in the special case of a principal shift-invariant spaces in L²(R)$L^2(\mathbb{R})$ whose generator and its translates form a Riesz basis.     

Frames, modular functions for shift-invariant subspaces and FMRA wavelet frames

We introduce the concept of the modular function for a shift-invariant subspace that can be represented by normalized tight frame generators for the shift-invariant subspace and prove that it is independent of the selections of the frame generators for the subspace. We shall apply it to study the connections between the dimension functions of wavelet frames for any expansive integer matrix and the multiplicity functions for general multiresolution analysis (GMRA). Given a frame mutiresolution analysis (FMRA), we show that the standard construction formula for orthonormal multiresolution analysis wavelets does not yield wavelet frames unless the underlying FMRA is an MRA. A modified explicit construction formula for FMRA wavelet frames is given in terms of the frame scaling functions and the low-pass filters.

     

平移不变空间的非均匀采样

为了从采样值稳定和惟一地重建信号f(x),函数在采样集{xj,j=∈Z}上的采样值{f(xj),j∈Z}要满足A||f||L^p^p≤∑j∈Z|f(xj)|^p≤B||f||L^p^p.本文研究在平移不变空间V^p[φ]中使上式成立的条件,在几种情况下,得到了使上式成立的采样条件,并建立了由采样值重建f(x)的重建算法,该算法比一般的迭代重建算法收敛更快．     

Generalized sampling in shift-invariant spaces with multiple stable generators

The aim of this paper is to derive stable generalized sampling in a shift-invariant space with ? stable generators. This is done in the light of the theory of frames in the product Hilbert space (? times). The generalized samples are expressed as the frame coefficients of an appropriate function in with respect to some particular frame in . Since any multiply stable generated shift-invariant space is the image of by means of a bounded invertible operator, the generalized sampling is obtained from some dual frame expansions in . An example in the setting of the Hermite cubic splines is exhibited.     

Dual frames in connected with generalized sampling in shift-invariant spaces

The aim of this article is to derive stable generalized sampling in a shift-invariant space by using some special dual frames in L²(0,1). These sampling formulas involve samples of filtered versions of the functions in the shift-invariant space. The involved samples are expressed as the frame coefficients of an appropriate function in L²(0,1) with respect to some particular frame in L²(0,1). Since any shift-invariant space with stable generator is the image of L²(0,1) by means of a bounded invertible operator, our generalized sampling is derived from some dual frame expansions in L²(0,1).     

Multivariate generalized sampling in shift-invariant spaces and its approximation properties

Nowadays the topic of sampling in a shift-invariant space is having a significant impact: it avoids most of the problems associated with classical Shannon's theory. Under appropriate hypotheses, any multivariate function in a shift-invariant space can be recovered from its samples at Zd. However, in many common situations the available data are samples of some convolution operators acting on the function itself: this leads to the problem of multivariate generalized sampling in shift-invariant spaces. This extra information on the functions in the shift-invariant space will allow to sample in an appropriate sub-lattice of Zd. In this paper an L²(Rd) theory involving the frame theory is exhibited. Sampling formulas which are frame expansions for the shift-invariant space are obtained. In the case of overcomplete frame formulas, the search of reconstruction functions with prescribed good properties is allowed. Finally, approximation schemes using these generalized sampling formulas are included.     

Bases in Sobolev weight spaces

In the paper, we construct a system of smooth two-dimensional splines and describe a class of measures for which this system is a basis in the Sobolev weight space on the square. Translated fromMatematicheskie Zametki, Vol. 67, No. 3, pp. 343–354, March, 2000.     

Some notes on split Newton iterative algorithm

In this study, a parameterized split Newton method is derived by using the accelerating technique. Convergence and error estimates of the method are obtained. In practical application, the proposed method can give a better result in view of computational CPU time. Numerical examples on several partial differential equations are shown to illustrate our findings. Copyright © 2015 John Wiley & Sons, Ltd.     

Using a natural deconvolution for analysis of perturbed integer sampling in shift-invariant spaces

An important cornerstone of both wavelet and sampling theory is shift-invariant spaces, that is, spaces V spanned by a Riesz basis of integer-translates of a single function. Under some mild differentiability and decay assumptions on the Fourier transform of this function, we show that V also is generated by a function with Fourier transform for some g with . We explain why analysis of this particular generating function can be more likely to provide large jitter bounds ε such that any f∈V can be reconstructed from perturbed integer samples f(k+εk) whenever supk∈Z|εk|?ε. We use this natural deconvolution of to further develop analysis techniques from a previous paper. Then we demonstrate the resulting analysis method on the class of spaces for which g has compact support and bounded variation (including all spaces generated by Meyer wavelet scaling functions), on some particular choices of φ for which we know of no previously published bounds and finally, we use it to improve some previously known bounds for B-spline shift-invariant spaces.     

Adaptive algorithm in irregular sampling of band-limited functions

This article obtains an adaptive algorithm in irregular sampling of band-limited functions, that is to say, important information on how the sampling density affects the performance of the algorithm is discovered. Moreover, the rate of convergence of the algorithm of the discrete model is improved.     

The Implicit General Order Complementarity Problem,models and iterative methods

We present the Implicit General Order Complementarity Problem associated to a finite family of operators on an ordered Banach space which is a vector lattice. Models and some iterative methods are studied.The author would like to express his thanks to Prof. V.H. Nguyen for many valuable discussions.