Reconstruction of a Source from Observational Data

A procedure is described for determining the strength, position, and startup time of a surface force source acting on an elastic half-space from recorded data on the vertical displacements (seismograms) of a linear oscillator (seismograph). The algorithm is based on a previously published analytical solution of the Lamb problem. Special attention is given to the role of the Rayleigh wavefront as a generator of displacements much larger than in the approach of P waves and SV waves to the seismograph, revealing the Rayleigh wave as the primary indicator of a source's space–time position.     

Construction of Real Band Anti-Symmetric Matrices from Spectral Data

In this paper,we describe how to construct a real anti-symmetric(2p-1)-band matrix with prescribed eigenvalues in its ρ leading principal submatrices.This is done in two steps.First,an anti-symmetric matrix B is constructed with the specified spectral data but not necessary a band matrix.Then B is transformed by Householder transformations to a (2ρ-1)-band matrix with the prescribed eigenvalues.An algorithm is presented.Numerical results are presented to demonstrate that the proposed method is effective.     

An Algorithm for Cavity Reconstruction in Electrical Impedance Tomography

We consider the inverse problem of finding cavities within some objectfrom electrostatic measurements on the boundary. By a cavity we understand anyobject with a different electrical conductivity from the background material of thebody. We give an algorithm for solving this inverse problem based on the outputnonlinear least-square formulation and the regularized Newton-type iteration. Inparticular, we present a number of numerical results to highlight the potential andthe limitations of this method.     

An Algorithm for Cavity Reconstruction in Electrical Impedance Tomography

We consider the inverse problem of finding cavities within some object from electrostatic measurements on the boundary. By a cavity we understand any object with a different electrical conductivity from the background material of the body. We give an algorithm for solving this inverse problem based on the output nonlinear least-square formulation and the regularized Newton-type iteration. In particular, we present a number of numerical results to highlight the potential and the limitations of this method.     

Efficient Reconstruction of Functions on the Sphere from Scattered Data

Recently, fast and reliable algorithms for the evaluation of spherical harmonic expansions have been developed. The corresponding sampling problem is the computation of Fourier coefficients of a function from sampled values at scattered nodes. We consider a least squares approximation and an interpolation of the given data. Our main result is that the rate of convergence of the two proposed iterative schemes depends only on the mesh norm and the separation distance of the nodes. In conjunction with the nonequispaced FFT on the sphere, the reconstruction of N² Fourier coefficients from M reasonably distributed samples is shown to take O(N² log² N + M) floating point operations. Numerical results support our theoretical findings.     

一种积分数据的函数重构及其误差估计

本文考虑了一种基于函数积分平均值的函数重构方法,在定义了一个插值算子之后建立了误差估计.从理论分析结果可以看出这种方法得到的解是适定的,因此我们不需要选择正则化参数,这样就简化了算法,而且最后一系列的数值结果很好的验证了这种方法的有效性.     

Diffraction of Electromagnetic Waves on an Impedance Interface between Two Media with Different Perturbations in Impedance

The problem on the diffraction of the electromagnetic plane wave on the impedance interface between two media is investigated. The impedance is assumed to be different from a constant on a segment of the interface, where the impedance is described by piecewise-linear, quadratic, or step functions. Bibliography: 4 titles.     

Adaptive Mollifiers for High Resolution Recovery of Piecewise Smooth Data from its Spectral Information

We discuss the reconstruction of piecewise smooth data from its (pseudo-) spectral information. Spectral projections enjoy superior resolution provided the data is globally smooth, while the presence of jump discontinuities is responsible for spurious O (1) Gibbs oscillations in the neighborhood of edges and an overall deterioration of the unacceptable first-order convergence in rate. The purpose is to regain the superior accuracy in the piecewise smooth case, and this is achieved by mollification. Here we utilize a modified version of the two-parameter family of spectral mollifiers introduced by Gottlieb and Tadmor [GoTa85]. The ubiquitous one-parameter, finite-order mollifiers are based on dilation . In contrast, our mollifiers achieve their high resolution by an intricate process of high-order cancellation . To this end, we first implement a localization step using an edge detection procedure [GeTa00a, b]. The accurate recovery of piecewise smooth data is then carried out in the direction of smoothness away from the edges, and adaptivity is responsible for the high resolution. The resulting adaptive mollifier greatly accelerates the convergence rate, recovering piecewise analytic data within exponential accuracy while removing the spurious oscillations that remained in [GoTa85]. Thus, these adaptive mollifiers offer a robust, general-purpose ``black box' procedure for accurate post-processing of piecewise smooth data. March 29, 2001. Final version received: August 31, 2001.     

Global Optimal Image Reconstruction from Blurred Noisy Data by a Bayesian Approach

In this paper, a procedure is presented which allows the optimal reconstruction of images from blurred noisy data. The procedure relies on a general Bayesian approach, which makes proper use of all the available information. Special attention is devoted to the informative content of the edges; thus, a preprocessing phase is included, with the aim of estimating the jump sizes in the gray level. The optimization phase follows; existence and uniqueness of the solution is secured. The procedure is tested against simple simulated data and real data.     

基于字典学习和TV的能谱CT重建算法

能谱CT可以将较宽的能谱数据划分为几个单独的窄谱数据,从而同时获得多个能量通道下的投影.但由于窄谱通道内接收到的光子数较少,投影通常包含较大的噪声.针对这一问题,基于压缩感知理论提出了一种基于字典学习和全变分TV(total-variation)的迭代重建算法用于能谱CT重建,应用交替最小化方法优化相关目标函数,并采用Split-Bregman算法求解.同时,采用有序子集方法加速迭代收敛过程,提高运算速率.为了验证和评估所提出的方法,使用简单模型和实际临床小鼠模型进行了仿真实验,实验结果表明,所提出的算法有较好的去噪及细节保存能力.     

Graph Theoretic and Spectral Analysis of Enron Email Data

Analysis of social networks to identify communities and model their evolution has been an active area of recent research. This paper analyzes the Enron email data set to discover structures within the organization. The analysis is based on constructing an email graph and studying its properties with both graph theoretical and spectral analysis techniques. The graph theoretical analysis includes the computation of several graph metrics such as degree distribution, average distance ratio, clustering coefficient and compactness over the email graph. The spectral analysis shows that the email adjacency matrix has a rank-2 approximation. It is shown that preprocessing of data has significant impact on the results, thus a standard form is needed for establishing a benchmark data. Anurat Chapanond is currently a Ph.D. student in Computer Science, RPI. Anurat graduated B. Eng. degree in Computer Engineering from Chiangmai University (Thailand) in 1997, M. S. in Computer Science from Columbia University in 2002. His research interest is in web data mining analyses and algorithms. M.S. Krishnamoorthy received the B.E. degree (with honors) from Madras University in 1969, the M. Tech degree in Electrical Engineering from the Indian Institute of Technology, Kanpur, in 1971, and the Ph. D. degree in Computer Science, also from the Indian Institute of Technology, in 1976. From 1976 to 1979, he was an Assistant Professor of Computer Science at the Indian Institute of Technology, Kanpur. From 1979 to 1985, he was an Assistant Professor of Computer Science at Rensselaer Polytechnic Institute, Troy, NY, and since, 1985, he has been an Associate Professor of Computer Science at Rensselaer. Dr. Krishnamoorthy's research interests are in the design and analysis of combinatorial and algebraic algorithms, visualization algorithms and programming environments. Bulent Yener is an Associate Professor in the Department of Computer Science and Co-Director of Pervasive Computing and Networking Center at Rensselaer Polytechnic Institute in Troy, New York. He is also a member of Griffiss Institute of Information Assurance. Dr. Yener received MS. and Ph.D. degrees in Computer Science, both from Columbia University, in 1987 and 1994, respectively. Before joining to RPI, he was a Member of Technical Staff at the Bell Laboratories in Murray Hill, New Jersey. His current research interests include bioinformatics, medical informtatics, routing problems in wireless networks, security and information assurance, intelligence and security informatics. He has served on the Technical Program Committee of leading IEEE conferences and workshops. Currently He is an associate editor of ACM/Kluwer Winet journal and the IEEE Network Magazine. Dr. Yener is a Senior Member of the IEEE Computer Society.     

Reconstruction of the Dirac Operator From Nodal Data

Inverse nodal problems consist in constructing operators from the given nodes (zeros) of their eigenfunctions. In this work, we deal with the inverse nodal problem of reconstructing the Dirac operator on a finite interval. We prove that a dense subset of nodal points uniquely determine the parameters of the boundary conditions, the mass of a particle and the potential function of the Dirac system. We also provide a constructive procedure for the solution of the inverse nodal problem.     

On the Reconstruction of the Sturm-Liouville Problems with Spectral Parameter in the Discontinuity Conditions

In this paper, we are concerned with the problem of recovering the Sturm–Liouville problem under the circumstance of the discontinuity conditions involved spectral parameter at finite interior points of a finite interval. We provide procedures for constructing their potentials and boundary conditions either from the Weyl function, or from spectral data, or from two spectra in terms of the method of spectral mappings.     

Spectral Properties of an Energy-Dependent Hamiltonian

We study spectral properties of a quantum Hamiltonian with a complex-valued energy-dependent potential related to a model introduced in physics of nuclear reactions[30]and we prove that the principle of limiting absorption holds at any point of a large subset of the essential spectrum.When an additional dissipative or smallness hypothesis is assumed on the potential,we show that the principle of limiting absorption holds at any point of the essential spectrum.     

Approximation in the Space of Spectral Data of a Perturbed Harmonic Oscillator

We consider the spaces of sequences that arise in the inverse spectral problem for a harmonic oscillator perturbed by potential. We establish embedding theorems which connect such spaces with weight spaces . We also study the approximation of elements by finite sequences.This problem arises if we restore the potential from its spectrum.Bibliography: 5 titles.     

由半直线上Strum-Liouville方程的散射数据重构位势

本文考虑半直线Strum-Liouville方程的逆散射问题,研究如何重建出位势函数.重建位势时,我们利用矩阵薛定谔算子理论及其散射矩阵的性质,证明了半直线上Strum-Liouville方程可通过散射数据重构位势.     

Reconstruction of inclusions in an elastic body

We consider the reconstruction of elastic inclusions embedded inside of a planar region, bounded or unbounded, with isotropic inhomogeneous elastic parameters by measuring displacements and tractions at the boundary. We probe the medium with complex geometrical optics solutions having polynomial-type phase functions. Using these solutions we develop an algorithm to reconstruct the exact shape of a large class of inclusions including star-shaped domains and we implement numerically this algorithm for some examples.     

Diffraction of the Plane Wave by an Impedance Cone

Some questions concerning the justification of the solution in the problem of diffraction of the plane wave by an impedance cone are discussed. The surface waves, as well as the Weyl-van-der-Pol phenomenon, are studied in the zone illuminated by reflected rays. Bibliography: 19 titles.__________Translated from Zapiski Nauchnykh Seminarov POMI, Vol. 297, 2003, pp. 191–215.     

Reconstruction from vertex-switching

Let X be a graph with vertices x₁ ,…, x_n. Let X_i be the graph obtained by removing all edges {x_i, x_j} of X and inserting all nonedges {x_i, x_k}. If n ? 0 (mod 4), then X can be uniquely reconstructed from the unlabeled graphs X₁.…, X_n. If n = 4 the result is false, while for n = 4m≥8 the result remains open. The proof uses linear algebra and does not explicitly describe the reconstructed graph X.