基于混合l_2/l_1范数极小化方法的块稀疏信号重构条件

研究压缩感知中的块稀疏信号重构问题,主要对混合l_2/l_1极小化方法建立了一类改进的可重构条件.具体地说,本文证明若测量矩阵满足条件δ_k+θ_(k,k)1,则混合l_2/l_1极小化方法可精确重构(无噪声情形)或鲁棒重构(有噪声情形)原始块k-稀疏信号.进而表明本文给出的新条件弱于现有文献所给出的条件.     

随机测量矩阵齐次RIP的证明

在压缩感知理论中,若要保证重构信号的精确性,测量矩阵需要满足限制等距性质,即RIP.当测量矩阵是随机矩阵时,RIP的成立与概率相关.对高斯矩阵RIP进行了修正,其中将原高斯矩阵RIP相关的集中不等式的■范数修正为■范数,梳理了这一类RIP证明过程,并证明得到了齐次RIP.     

多小波采样定理的拓展

采样定理在数字信号通讯中发挥了十分重要的作用,因为信号通常由它的离散采样数据来恢复.Han Bin等人在[J.Comput.Appl.Math.,2009,227:254-270]中构造了广义插值加细函数向量.本文研究与广义插值加细函数向量有关的采样定理的拓展问题.具体而言,对于已知的广义插值d-加细函数向量φ=(φ_1,…,φ_r)~T,即φe(m/r+k)=δ_kδ_(e-1-m),k∈Z,m=0,1,…,r-1,e=1,…,r我们将构造一组函数{φ_(r+1),…,φ_(dr)},使得φ~ロ=(φ~T,φ_(r+1),…,φ_(dr))~T也是d-加细的,而且满足φ_e(m/(dr)+k)=δ_kδ_(θ_(d,r(e)-m))k∈Z,m=0,1,…,dr-1,e=r+1,…,dr,其中θ_(d,r(e))=e-r+R_(e-1-r,d-1),R_(e-1-r,d-1)=「(e-1-r)/(d-1)」.我们建立与φ~■有关的采样定理.显然,φ的多小波子空间采样定理的适用范围得到了拓展.给出φ~■的多小波子空间采样级数的截断误差估计.     

基于lp有界噪声的压缩数据分离

本文考虑l_p有界噪声约束下的压缩数据分离问题,即从压缩测量数据中重建信号的不同稀疏子成分.为了重构不同框架D₁∈R^n×d₁和D₂∈R^n×d₂下(近似)稀疏的不同子成分,我们首先提出了l₁-αl₂分解分析算法,在测量矩阵满足一定的约束等距性条件且字典之间满足某个相互相干性条件时,此算法可以处理不同噪声干扰下的信号分离问题.此外,基于经典Dantzig Selector模型,我们还引入了l₁-αl₂分解分析Dantzig Selector算法,在适当条件下此算法也可以稳定分离压缩数据.数值实验表明,l₁-αl₂最小化算法对于冗余紧框架下的数据分离问题具有鲁棒性和稳定性.     

基于非凸优化模型的块稀疏信号恢复条件

压缩感知(compressed sensing,CS)是一种全新的信息采集与处理理论，它表明稀疏信号能够在远低于Shannon-Nyquist采样率的条件下被精确重构.现从压缩感知理论出发，对块稀疏信号重构算法进行研究，通过混合l₂/l_q(0相似文献   

一个素变量丢番图问题

设k和r是满足k≥3及r≥Ψ(k)+1的正整数,这里当3≤k≤4时,Ψ(k)=2~(k-1);而当k≥5时,Ψ(k)=1/2k(k+1).假定δ和ε是给定的足够小的正数,λ_1,λ_2,…,λ_(r+1)是不全同号且两两之比不全为有理数的非零实数.对于任意实数η与0σ2~(1-2k)/r-1,证明了:存在一个正数序列X→+∞,使得不等式|λ_1p_1~k+λ_2p_2~k+···+λ_rp_r~k+λ_(r+1)p_(r+1)+η|(max(1≤j≤r+1)p_j)~(-σ)有》■X~(■-(2~(1-2k))/(r-1)+ε组素数解(p_1,p_2,…,p_(r+1)),这里(δX)~(1/k)≤p_j≤X~(1/k)(1≤j≤r)及δX≤p_(r+1)≤X.这改进了之前的结果.     

逼近转化论和泛系逼近论(Ⅳ)

Theorem 1 If 1≤p≤∞, f∈W_p~(l)(D), then ω_k(δ,f,W_p~(l)(D))≤c(‖f‖_(l)_p),if f∈C~〔k+l〕(D), then ω_k(δ, f,W_p~(l)(D))≤c(δ~kmax‖(D)~(k)f‖_(()p)), where c is independent of δ≥0 and f. Theorem 2 If f∈W_p~(r)H_M~(a)(〔a,b〕)is of period b-a<∞, then ‖f‖_((s)t)≤cM~d‖f‖_((u)υ)~e, where d=δ/θ, e=(θ-δ)/θ, p≥1, t≥υ≥1, r>s≥u, δ=s-u+     

压缩感知

压缩感知是近来国际上热门的研究方向. 其主要思想为: 利用信号稀疏性的特征, 通过尽量少的观测信息恢复信号. 压缩感知在多个应用领域, 如医学成像、图像处理、地质勘探等中具有很好的应用前景. 此外, 它与逼近论、最优化、随机矩阵及离散几何等领域密切相关, 由此产生了一些漂亮的数学结果. 本文综述压缩感知一些基本结果并介绍最新进展. 主要包括RIP 矩阵编码与l₁ 解码的性能、RIP (restricted isometry property) 矩阵的构造、Gelfand 宽度、个例最优性及OMP (orthogonalmatching pursuit) 解码等.     

固定时间梯度流在?_1-?_2范数中的稀疏重构

压缩感知(compressed sensing,CS)是一种全新的信号采样技术,对于稀疏信号,它能够以远小于传统的Nyquist采样定理的采样点来重构信号.在压缩感知中,采用动态连续系统,对?_1-?_2范数的稀疏信号重构问题进行了研究.提出了一种基于固定时间梯度流的稀疏信号重构算法,证明了该算法在Lyapunov意义上的稳定性并且收敛于问题的最优解.最后通过与现有的投影神经网络算法的对比,体现了该算法的可行性以及在收敛速度上的优势.     

压缩感知和稀疏优化简介

介绍压缩感知和稀疏优化的基本概念、理论基础和算法概要. 压缩感知利用原始信号的稀疏性,从远少于信号元素个数的测量出发,通过求解稀疏优化问题来恢复完整的原始稀疏信号. 通过一个小例子展示这一过程,并以此说明压缩感知和稀疏优化的基本理念. 接着简要介绍用以保证l₁凸优化恢复稀疏信号的零空间性质和RIP条件. 最后介绍求解稀疏优化的几个经典算法.     

RECENT PROGRESS ON SPHERICAL HARMONIC APPROXIMATION MADE BY BNU RESEARCH GROUP ——In memory of Professor Sun Yongsheng

As early as in 1990, Professor Sun Yongsheng, suggested his students at Beijing Normal University to consider research problems on the unit sphere. Under his guidance and encouragement his students started the research on spherical harmonic analysis and approximation. In this paper, we incompletely introduce the main achievements in this area obtained by our group and relative researchers during recent 5 years （2001-2005）. The main topics are： convergence of Cesaro summability, a.e. and strong summability of Fourier-Laplace series; smoothness and K-functionals; Kolmogorov and linear widths.     

Boundedness for commutators of multipliers on Hardy type spaces

In this paper, we study the commutators generalized by multipliers and a BMO function. Under some assumptions, we establish its boundedness properties from certain atomic Hardy space Hb^p（R^n） into the Lebesgue space L^p with p 〈 1.     

A unified approach to certain problems of best local approximation

In this paper we study best local quasi-rational approximation and best local approximation from finite dimensional subspaces of vectorial functions of several variables. Our approach extends and unifies several problems concerning best local multi-point approximation in different norms.     

Towards Excellence in Science Chinese Academy of Sciences

<正>May 26,2014,Beijing Science is a human enterprise in the pursuit of knowledge.The scientific revolution that occurred in the 17th Century initiated the advances of modern science.The scientific knowledge system created by     

THE 8~(th) INTERNATIONAL CONGRESS ON INDUSTRIAL AND APPLIED MATHEMATICS

<正>August 10-14,2015Beijing,ChinaThe International Congress on Industrial and Applied Mathematics(ICIAM)is the premier international congress in the field of applied mathematics held every four years under the auspices of the International Council for Industrial and Applied Mathematics.From August 10 to 14,2015,mathematicians,scientists     

Bounds for the zeros of polynomials

Let P(z)=∑↓j=0↑n ajx^j be a polynomial of degree n. In this paper we prove a more general result which interalia improves upon the bounds of a class of polynomials. We also prove a result which includes some extensions and generalizations of Enestrǒm-Kakeya theorem.     

Boundedness of commutators related to Marcinkiewicz integrals on hardy type spaces

In this paper, the authors study the boundedness of the operator [μΩ, b], the commutator generated by a function b ∈ Lipβ(Rn)(0 ＜β≤ 1) and the Marcinkiewicz integrals μΩ, on the classical Hardy spaces and the Herz-type Hardy spaces in the case Ω∈ Lipα(Sn-1)(0 ＜α≤ 1).     

Generalization of the interaction between Haar approximation and polynomial operators to higher order methods

In applications it is useful to compute the local average empirical statistics on u. A very simple relation exists when of a function f（u） of an input u from the local averages are given by a Haar approximation. The question is to know if it holds for higher order approximation methods. To do so, it is necessary to use approximate product operators defined over linear approximation spaces. These products are characterized by a Strang and Fix like condition. An explicit construction of these product operators is exhibited for piecewise polynomial functions, using Hermite interpolation. The averaging relation which holds for the Haar approximation is then recovered when the product is defined by a two point Hermite interpolation.     

Jacobi polynomials used to invert the laplace transform

Given the Laplace transform F(s) of a function f(t), we develop a new algorithm to find an approximation to f(t) by the use of the classical Jacobi polynomials. The main contribution of our work is the development of a new and very effective method to determine the coefficients in the finite series expansion that approximation f(t) in terms of Jacobi polynomials. Some numerical examples are illustrated.