在离散多尺度分析框架下的数据分解和回复的数值特征

本文在离散多尺度分析框架下讨论了关于给定数据的分解和回复过程的数值特征，它给出了数据分解的回复算法的一般设计原则，它能有效地解释在正交小波基和双正交小波基下的数据分解回复过程。据此设计原则，文中还给出了一种新的数据分解回复方法，它可以在线性分层基背景下得到解释。     

L~2([0,1])的半正交小波基及其对偶小波基

本文从样条函数出发利用折叠法得到了L2（[0,1]）空间的两组相互对偶的半正交小波基，这两组小波基有显式表达式，并导出了他们的小波分解与重建算法．进一步，应用这些小波基给出了刻划高阶Holder空间的一个充分条件．     

正交小波变换的向量空间算法

本文揭示了一个事实，小波不仅可构成Ｌ２空间中的正交基，小波分解与重构滤波还可产生Ｎ维空间中的正交基．在本文提出修改的小波变换算法之下，Ｎ点信号的小波变换等价于Ｎ维空间中的正交变换．用该算法进行信号或图象压缩，无需对信号或图象进行周期延拓，可严格地在Ｎ维空间中进行．     

一族非正交小波基

本文构造了Ｌ＾２（Ｒ）的一族非正交样条小波基，它包含Ｃｈｕｉ和Ｗａｎｇ＾「１」的样条小波基作为基特殊情况，并且我们导出了其分解和重建算法。     

正交小波包的构造

本文给出尺度因子ａ＝４时正交小波包的构造，推广了［２，４］引入的正交小波包，并给出相应的分解与再构造算法．本文引入的正交小波包具有保持信号ｆ∈Ｌ^２的线性相位，也讨论了尺度因子ａ＝ｋ（ｋ∈Ｚ，ｋ≥２）正交小波的构造     

一维参数化正交小波滤波器的解析性质与优化逼近

本文给出了一维参数化正交小波滤波器系数向量的解析表达式和它的递推计算公式,还给出了它的一阶变分及二阶变分公式．利用这些结果和最优化方法,给出了FIR正交小波滤波器的逼近和设计问题的优化模型和数值例子．     

小波基的选取对图像去噪的影响

小波图像去噪方法是现代图像处理中的重要组成部分，小波基的不同选取直接影响到去噪的效果．本文在全局阈值的标准下，通过对噪声水平和图像纹理特征的估计，讨论了小波基的正交性和线性相位性对去噪结果的不同影响，提出了选取小波基的近似标准．     

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．     

r重非正交小波包

该文讨论了由有限个尺度函数｛φ1，φ2，…，φr｝所生成的L2（R）上的多分辨分析．并考虑了L2（R）上直接小波分解和直接小波包分解，对（对偶）非正交小波包以及产生它们的基的稳定性作了较为深人的研究，获得了一些结果．     

矩阵伸缩的高维向量值小波包

本文给出了对应于任意整数矩阵伸缩的高维向量值正交小波包的定义及其构造方法．并讨论了这种向量值正交小波包的性质,得到向量值函数空间L2(Rs,Cr)的新的正交小波基．     

On the Uniqueness of the Solution of the Inverse Sturm–Liouville Problem with Nonseparated Boundary Conditions on a Geometric Graph

For the first time, the inverse Sturm–Liouville problem with nonseparated boundary conditions is studied on a star-shaped geometric graph with three edges. It is shown that the Sturm–Liouville problem with general boundary conditions cannot be uniquely reconstructed from four spectra. Nonseparated boundary conditions are found for which a uniqueness theorem for the solution of the inverse Sturm–Liouville problem is proved. The spectrum of the boundary value problem itself and the spectra of three auxiliary problems are used as reconstruction data. It is also shown that the Sturm–Liouville problem with these nonseparated boundary conditions can be uniquely recovered if three spectra of auxiliary problems are used as reconstruction data and only five of its eigenvalues are used instead of the entire spectrum of the problem.     

Direct and inverse spectral problems for a class of non-self-adjoint periodic tridiagonal matrices

The spectral properties of a class of tridiagonal matrices are investigated. The reconstruction of matrices of this special class from given spectral data is also studied. Necessary and sufficient conditions for that reconstruction are found. The obtained results extend some results on the direct and inverse spectral problems for periodic Jacobi matrices and for some non-self-adjoint tridiagonal matrices.     

Solvability of the Dirichlet Problem for the Poisson Equation on Some Noncompact Riemannian Manifolds

The behavior of solutions of the Poisson equation on noncompact Riemannian manifolds of a special form is studied. Sharp conditions for the unique solvability of the Dirichlet problem on the reconstruction of solutions of the Poisson equation from continuous boundary data at infinity are found.     

Inverse Sturm–Liouville problem with spectral polynomials in nonsplitting boundary conditions

Theorems on the unique reconstruction of a Sturm–Liouville problem with spectral polynomials in nonsplitting boundary conditions are proved. Two spectra and finitely many eigenvalues (one spectrum and finitely many eigenvalues for a symmetric potential) of the problem itself are used as the spectral data. The results generalize the Levinson uniqueness theorem to the case of nonsplitting boundary conditions containing polynomials in the spectral parameter. Algorithms and examples of solving relevant inverse problems are also presented.     

Dynamic reconstruction of disturbances in stochastic differential equations

The reconstruction of the unknown deterministic disturbance in an Ito stochastic differential equation is studied using the Osipov-Kryazhimskii dynamic inversion theory. Inexact discrete observations of the current phase state are used as input data. A finite-step solving algorithm based on the method of auxiliary controllable models is proposed. Its convergence is proved, and the compatibility conditions for the parameters are given.     

基于字典学习方法的CT不完全投影图像重建算法

对于不完全投影角度的重建研究是CT图像重建中一个重要的问题.将压缩感知中字典学习的方法与CT重建算法ART迭代算法相结合.字典学习方法中字典更新采用K-SVD(K-奇异值分解)算法,稀疏编码采用OMP(正交匹配追踪)算法.最后通过对标准Head头部模型进行仿真实验,验证了字典学习方法在CT图像重建中对于提高图像的重建质量和提高信噪比的可行性与有效性.另外还研究了字典学习中图像块大小和滑动距离对重建图像的影响     

Two-view curve reconstruction based on the snake model

Reconstruction of 3D curves from their stereo images is an important issue in computer vision. Based on deformation of the snake model and NURBS representation, we evolve the curve in the view of inverse optimization to finish reconstruction. This manner can reduce the need of matching multi-view space curve projections, meanwhile improve the reconstruction precision. Considering that the 2D data reconstruction exists error inevitably, based on two cameras, a discussion on its influence to stereo reconstruction is given next. Finally, the proposed approach is experimented with artificial and real data, and gains a satisfying reconstruction effect.     

Inverse spectral problem for the operators with non‐local potential

The main object under consideration in the paper is the second derivative operator on a finite interval with zero boundary conditions perturbed by a self‐adjoint integral operator with the degenerate kernel (non‐local potential). The inverse problem, i.e., the reconstruction of the perturbation from the spectral data, is solved by means of the step‐by‐step procedure based on the n‐interlacing property of the spectrum.     

Two-view curve reconstruction based on the snake model

Reconstruction of 3D curves from their stereo images is an important issue in computer vision. Based on deformation of the snake model and NURBS representation, we evolve the curve in the view of inverse optimization to finish reconstruction. This manner can reduce the need of matching multi-view space curve projections, meanwhile improve the reconstruction precision. Considering that the 2D data reconstruction exists error inevitably, based on two cameras, a discussion on its influence to stereo reconstruction is given next. Finally, the proposed approach is experimented with artificial and real data, and gains a satisfying reconstruction effect.     

A variational proximal alternating linearized minimization in a given metric for limited-angle CT image reconstruction

Due to the restriction of computed tomography (CT) scanning environment, the acquired projection data may be incomplete for exact CT reconstruction. Though some convex optimization methods, such as total variation minimization based method, can be used for incomplete data reconstruction, the edge of reconstruction image may be partly distorted for limited-angle CT reconstruction. To promote the quality of reconstruction image for limited-angle CT imaging, in this paper, a nonconvex and nonsmooth optimization model was investigated. To solve the model, a variational proximal alternating linearized minimization (VPALM) method based on proximal mapping in a given metric was proposed. The proposed method can avoid computing the inverse of a huge system matrix thus can be used to deal with the larger-scale inverse problems. What’s more, we show that each bounded sequence generated by VPALM globally converges to a critical point based on the Kurdyka–Lojasiewicz property. Real data experiments are used to demonstrate the viability and effectiveness of VPALM method, and the results show that the proposed method outperforms two classical CT reconstruction methods.