Inverse boundary spectral problems
Kachalov, Alexander; Lassas, Matti
2001-01-01
Inverse boundary problems are a rapidly developing area of applied mathematics with applications throughout physics and the engineering sciences. However, the mathematical theory of inverse problems remains incomplete and needs further development to aid in the solution of many important practical problems.Inverse Boundary Spectral Problems develop a rigorous theory for solving several types of inverse problems exactly. In it, the authors consider the following: ""Can the unknown coefficients of an elliptic partial differential equation be determined from the eigenvalues and the boundary value
Inverse logarithmic potential problem
Cherednichenko, V G
1996-01-01
The Inverse and Ill-Posed Problems Series is a series of monographs publishing postgraduate level information on inverse and ill-posed problems for an international readership of professional scientists and researchers. The series aims to publish works which involve both theory and applications in, e.g., physics, medicine, geophysics, acoustics, electrodynamics, tomography, and ecology.
Directory of Open Access Journals (Sweden)
Calvez V.
2010-12-01
Full Text Available We consider the radiative transfer equation (RTE with reflection in a three-dimensional domain, infinite in two dimensions, and prove an existence result. Then, we study the inverse problem of retrieving the optical parameters from boundary measurements, with help of existing results by Choulli and Stefanov. This theoretical analysis is the framework of an attempt to model the color of the skin. For this purpose, a code has been developed to solve the RTE and to study the sensitivity of the measurements made by biophysicists with respect to the physiological parameters responsible for the optical properties of this complex, multi-layered material. On étudie l’équation du transfert radiatif (ETR dans un domaine tridimensionnel infini dans deux directions, et on prouve un résultat d’existence. On s’intéresse ensuite à la reconstruction des paramètres optiques à partir de mesures faites au bord, en s’appuyant sur des résultats de Choulli et Stefanov. Cette analyse sert de cadre théorique à un travail de modélisation de la couleur de la peau. Dans cette perspective, un code à été développé pour résoudre l’ETR et étudier la sensibilité des mesures effectuées par les biophysiciens par rapport aux paramètres physiologiques tenus pour responsables des propriétés optiques de ce complexe matériau multicouche.
Inverse problem in hydrogeology
Carrera, Jesús; Alcolea, Andrés; Medina, Agustín; Hidalgo, Juan; Slooten, Luit J.
2005-03-01
The state of the groundwater inverse problem is synthesized. Emphasis is placed on aquifer characterization, where modelers have to deal with conceptual model uncertainty (notably spatial and temporal variability), scale dependence, many types of unknown parameters (transmissivity, recharge, boundary conditions, etc.), nonlinearity, and often low sensitivity of state variables (typically heads and concentrations) to aquifer properties. Because of these difficulties, calibration cannot be separated from the modeling process, as it is sometimes done in other fields. Instead, it should be viewed as one step in the process of understanding aquifer behavior. In fact, it is shown that actual parameter estimation methods do not differ from each other in the essence, though they may differ in the computational details. It is argued that there is ample room for improvement in groundwater inversion: development of user-friendly codes, accommodation of variability through geostatistics, incorporation of geological information and different types of data (temperature, occurrence and concentration of isotopes, age, etc.), proper accounting of uncertainty, etc. Despite this, even with existing codes, automatic calibration facilitates enormously the task of modeling. Therefore, it is contended that its use should become standard practice. L'état du problème inverse des eaux souterraines est synthétisé. L'accent est placé sur la caractérisation de l'aquifère, où les modélisateurs doivent jouer avec l'incertitude des modèles conceptuels (notamment la variabilité spatiale et temporelle), les facteurs d'échelle, plusieurs inconnues sur différents paramètres (transmissivité, recharge, conditions aux limites, etc.), la non linéarité, et souvent la sensibilité de plusieurs variables d'état (charges hydrauliques, concentrations) des propriétés de l'aquifère. A cause de ces difficultés, le calibrage ne peut êtreséparé du processus de modélisation, comme c'est le
Inverse problems for Maxwell's equations
Romanov, V G
1994-01-01
The Inverse and Ill-Posed Problems Series is a series of monographs publishing postgraduate level information on inverse and ill-posed problems for an international readership of professional scientists and researchers. The series aims to publish works which involve both theory and applications in, e.g., physics, medicine, geophysics, acoustics, electrodynamics, tomography, and ecology.
Statistical perspectives on inverse problems
DEFF Research Database (Denmark)
Andersen, Kim Emil
of the interior of an object from electrical boundary measurements. One part of this thesis concerns statistical approaches for solving, possibly non-linear, inverse problems. Thus inverse problems are recasted in a form suitable for statistical inference. In particular, a Bayesian approach for regularisation...... is obtained by assuming that the a priori beliefs about the solution before having observed any data can be described by a prior distribution. The solution to the statistical inverse problem is then given by the posterior distribution obtained by Bayes' formula. Hence the solution of an ill-posed inverse...... problem is given in terms of probability distributions. Posterior inference is obtained by Markov chain Monte Carlo methods and new, powerful simulation techniques based on e.g. coupled Markov chains and simulated tempering is developed to improve the computational efficiency of the overall simulation...
Parameter estimation and inverse problems
Aster, Richard C; Thurber, Clifford H
2005-01-01
Parameter Estimation and Inverse Problems primarily serves as a textbook for advanced undergraduate and introductory graduate courses. Class notes have been developed and reside on the World Wide Web for faciliting use and feedback by teaching colleagues. The authors'' treatment promotes an understanding of fundamental and practical issus associated with parameter fitting and inverse problems including basic theory of inverse problems, statistical issues, computational issues, and an understanding of how to analyze the success and limitations of solutions to these probles. The text is also a practical resource for general students and professional researchers, where techniques and concepts can be readily picked up on a chapter-by-chapter basis.Parameter Estimation and Inverse Problems is structured around a course at New Mexico Tech and is designed to be accessible to typical graduate students in the physical sciences who may not have an extensive mathematical background. It is accompanied by a Web site that...
Optimization and geophysical inverse problems
Energy Technology Data Exchange (ETDEWEB)
Barhen, J.; Berryman, J.G.; Borcea, L.; Dennis, J.; de Groot-Hedlin, C.; Gilbert, F.; Gill, P.; Heinkenschloss, M.; Johnson, L.; McEvilly, T.; More, J.; Newman, G.; Oldenburg, D.; Parker, P.; Porto, B.; Sen, M.; Torczon, V.; Vasco, D.; Woodward, N.B.
2000-10-01
A fundamental part of geophysics is to make inferences about the interior of the earth on the basis of data collected at or near the surface of the earth. In almost all cases these measured data are only indirectly related to the properties of the earth that are of interest, so an inverse problem must be solved in order to obtain estimates of the physical properties within the earth. In February of 1999 the U.S. Department of Energy sponsored a workshop that was intended to examine the methods currently being used to solve geophysical inverse problems and to consider what new approaches should be explored in the future. The interdisciplinary area between inverse problems in geophysics and optimization methods in mathematics was specifically targeted as one where an interchange of ideas was likely to be fruitful. Thus about half of the participants were actively involved in solving geophysical inverse problems and about half were actively involved in research on general optimization methods. This report presents some of the topics that were explored at the workshop and the conclusions that were reached. In general, the objective of a geophysical inverse problem is to find an earth model, described by a set of physical parameters, that is consistent with the observational data. It is usually assumed that the forward problem, that of calculating simulated data for an earth model, is well enough understood so that reasonably accurate synthetic data can be generated for an arbitrary model. The inverse problem is then posed as an optimization problem, where the function to be optimized is variously called the objective function, misfit function, or fitness function. The objective function is typically some measure of the difference between observational data and synthetic data calculated for a trial model. However, because of incomplete and inaccurate data, the objective function often incorporates some additional form of regularization, such as a measure of smoothness
Inverse feasibility problems of the inverse maximum flow problems
Indian Academy of Sciences (India)
A strongly polynomial time algorithm to solve the inverse maximum flow problem under l1 norm (denoted ... IMF can not be solved using weakly polynomial algorithms (although sometimes they can be preferred) because ..... in the network ˜G. We shall sort descending the arcs of ˜G by their capacities˜c1. After sorting, the.
Size Estimates in Inverse Problems
Di Cristo, Michele
2014-01-06
Detection of inclusions or obstacles inside a body by boundary measurements is an inverse problems very useful in practical applications. When only finite numbers of measurements are available, we try to detect some information on the embedded object such as its size. In this talk we review some recent results on several inverse problems. The idea is to provide constructive upper and lower estimates of the area/volume of the unknown defect in terms of a quantity related to the work that can be expressed with the available boundary data.
Inverse problem in transformation optics
DEFF Research Database (Denmark)
Novitsky, Andrey
2011-01-01
. We offer the solution of some sort of inverse problem: starting from the fields in the invisibility cloak we directly derive the permittivity and permeability tensors of the cloaking shell. This approach can be useful for finding material parameters for the specified electromagnetic fields...
The continuation inverse problem revisited
Huestis, Stephen P.
1998-06-01
The non-uniqueness of the continuation of a finite collection of harmonic potential field data to a level surface in the source-free region forces its treatment as an inverse problem. A formalism is proposed for the construction of continuation functions which are extremal by various measures. The problem is cast in such a form that the inverse problem solution is the potential function on the lowest horizontal surface above all sources, serving as the boundary function for the Dirichlet problem in the upper half-plane. The desired continuation, at the higher level of interest, must then be in the range of the upward continuation operator acting on this boundary function, rather than being allowed the full freedom of itself being part of a Dirichlet problem boundary function. Extremal solutions minimize non-linear functionals of the continuation function, which are re-expressed as different functionals of the boundary function. A crux of the method is that there is no essential distinction between the upward and downward continuation inverse problems to levels above or below data locations. Casting the optimization as a Lagrange multiplier problem leads to an integral equation for the boundary function, which is readily solved in the Fourier domain for a certain class of functionals. The desired extremal continuation is then given by upward continuation. It is found that for some functionals, application of the Lagrange multiplier theorem requires a further restriction on the set of allowable boundary functions: bandlimitedness is a natural choice for the continuation problem. With this imposition, the theory is developed in detail for semi-norm functionals penalizing departure from a constant potential, in the 2-norm and Sobelev norm senses, and illustrated by application for a small synthetic Deep Tow magnetic field data set.
Iterative optimization in inverse problems
Byrne, Charles L
2014-01-01
Iterative Optimization in Inverse Problems brings together a number of important iterative algorithms for medical imaging, optimization, and statistical estimation. It incorporates recent work that has not appeared in other books and draws on the author's considerable research in the field, including his recently developed class of SUMMA algorithms. Related to sequential unconstrained minimization methods, the SUMMA class includes a wide range of iterative algorithms well known to researchers in various areas, such as statistics and image processing. Organizing the topics from general to more
Optimization based inversion method for the inverse heat conduction problems
Mu, Huaiping; Li, Jingtao; Wang, Xueyao; Liu, Shi
2017-05-01
Precise estimation of the thermal physical properties of materials, boundary conditions, heat flux distributions, heat sources and initial conditions is highly desired for real-world applications. The inverse heat conduction problem (IHCP) analysis method provides an alternative approach for acquiring such parameters. The effectiveness of the inversion algorithm plays an important role in practical applications of the IHCP method. Different from traditional inversion models, in this paper a new inversion model that simultaneously highlights the measurement errors and the inaccurate properties of the forward problem is proposed to improve the inversion accuracy and robustness. A generalized cost function is constructed to convert the original IHCP into an optimization problem. An iterative scheme that splits a complicated optimization problem into several simpler sub-problems and integrates the superiorities of the alternative optimization method and the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm is developed for solving the proposed cost function. Numerical experiment results validate the effectiveness of the proposed inversion method.
Inverse Nonlinear Programming Problem and its Application
Kotkin, G.G.
1990-01-01
Inverse nonlinear programming problems for a new class of optimization problems relevant for game theory, system optimization, multicriteria optimization, etc. are considered by the author. This paper deals with problem definitions, numerical methods and applications of the inverse nonlinear programming problem in multicriteria optimization. Some associated properties of related parametric optimization problems and software implementations are also considered.
Inverse Problems and Uncertainty Quantification
Litvinenko, Alexander
2014-01-06
In a Bayesian setting, inverse problems and uncertainty quantification (UQ) - the propagation of uncertainty through a computational (forward) modelare strongly connected. In the form of conditional expectation the Bayesian update becomes computationally attractive. This is especially the case as together with a functional or spectral approach for the forward UQ there is no need for time- consuming and slowly convergent Monte Carlo sampling. The developed sampling- free non-linear Bayesian update is derived from the variational problem associated with conditional expectation. This formulation in general calls for further discretisa- tion to make the computation possible, and we choose a polynomial approximation. After giving details on the actual computation in the framework of functional or spectral approximations, we demonstrate the workings of the algorithm on a number of examples of increasing complexity. At last, we compare the linear and quadratic Bayesian update on the small but taxing example of the chaotic Lorenz 84 model, where we experiment with the influence of different observation or measurement operators on the update.
Inverse problems and uncertainty quantification
Litvinenko, Alexander
2013-12-18
In a Bayesian setting, inverse problems and uncertainty quantification (UQ)— the propagation of uncertainty through a computational (forward) model—are strongly connected. In the form of conditional expectation the Bayesian update becomes computationally attractive. This is especially the case as together with a functional or spectral approach for the forward UQ there is no need for time- consuming and slowly convergent Monte Carlo sampling. The developed sampling- free non-linear Bayesian update is derived from the variational problem associated with conditional expectation. This formulation in general calls for further discretisa- tion to make the computation possible, and we choose a polynomial approximation. After giving details on the actual computation in the framework of functional or spectral approximations, we demonstrate the workings of the algorithm on a number of examples of increasing complexity. At last, we compare the linear and quadratic Bayesian update on the small but taxing example of the chaotic Lorenz 84 model, where we experiment with the influence of different observation or measurement operators on the update.
The factorization method for inverse problems
Kirsch, Andreas
2008-01-01
The factorization method is a relatively new method for solving certain types of inverse scattering problems and problems in tomography. Aimed at students and researchers in Applied Mathematics, Physics and Engineering, this text introduces the reader to this promising approach for solving important classes of inverse problems. The wide applicability of this method is discussed by choosing typical examples, such as inverse scattering problems for the scalar Helmholtz equation, ascattering problem for Maxwell's equation, and a problem in impedance and optical tomography. The last section of the
Metaheuristic optimization of acoustic inverse problems.
van Leijen, A.V.; Rothkrantz, L.; Groen, F.
2011-01-01
Swift solving of geoacoustic inverse problems strongly depends on the application of a global optimization scheme. Given a particular inverse problem, this work aims to answer the questions how to select an appropriate metaheuristic search strategy, and how to configure it for optimal performance.
Optimization and inverse problems in electromagnetism
Wiak, Sławomir
2003-01-01
From 12 to 14 September 2002, the Academy of Humanities and Economics (AHE) hosted the workshop "Optimization and Inverse Problems in Electromagnetism". After this bi-annual event, a large number of papers were assembled and combined in this book. During the workshop recent developments and applications in optimization and inverse methodologies for electromagnetic fields were discussed. The contributions selected for the present volume cover a wide spectrum of inverse and optimal electromagnetic methodologies, ranging from theoretical to practical applications. A number of new optimal and inverse methodologies were proposed. There are contributions related to dedicated software. Optimization and Inverse Problems in Electromagnetism consists of three thematic chapters, covering: -General papers (survey of specific aspects of optimization and inverse problems in electromagnetism), -Methodologies, -Industrial Applications. The book can be useful to students of electrical and electronics engineering, computer sci...
The inverse scattering problem for transmission lines
Kay, I.
1972-01-01
A number of exact and approximate methods for solving the inverse scattering problem for transmission lines are reviewed. In particular, the application to transmission lines of Marcenko's version of the Gelfand-Levitan exact method for the quantum mechanical problem is compared with a more direct approach based on a different version of the Gelfand-Levitan method. In addition, some aspects of the lack of uniqueness of solutions are discussed, and some open questions related to the inverse scattering problem are suggested.
BOOK REVIEW: Inverse Problems. Activities for Undergraduates
Yamamoto, Masahiro
2003-06-01
This book is a valuable introduction to inverse problems. In particular, from the educational point of view, the author addresses the questions of what constitutes an inverse problem and how and why we should study them. Such an approach has been eagerly awaited for a long time. Professor Groetsch, of the University of Cincinnati, is a world-renowned specialist in inverse problems, in particular the theory of regularization. Moreover, he has made a remarkable contribution to educational activities in the field of inverse problems, which was the subject of his previous book (Groetsch C W 1993 Inverse Problems in the Mathematical Sciences (Braunschweig: Vieweg)). For this reason, he is one of the most qualified to write an introductory book on inverse problems. Without question, inverse problems are important, necessary and appear in various aspects. So it is crucial to introduce students to exercises in inverse problems. However, there are not many introductory books which are directly accessible by students in the first two undergraduate years. As a consequence, students often encounter diverse concrete inverse problems before becoming aware of their general principles. The main purpose of this book is to present activities to allow first-year undergraduates to learn inverse theory. To my knowledge, this book is a rare attempt to do this and, in my opinion, a great success. The author emphasizes that it is very important to teach inverse theory in the early years. He writes; `If students consider only the direct problem, they are not looking at the problem from all sides .... The habit of always looking at problems from the direct point of view is intellectually limiting ...' (page 21). The book is very carefully organized so that teachers will be able to use it as a textbook. After an introduction in chapter 1, sucessive chapters deal with inverse problems in precalculus, calculus, differential equations and linear algebra. In order to let one gain some insight
3rd Annual Workshop on Inverse Problem
2015-01-01
This proceeding volume is based on papers presented on the Third Annual Workshop on Inverse Problems which was organized by the Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, and took place in May 2013 in Stockholm. The purpose of this workshop was to present new analytical developments and numerical techniques for solution of inverse problems for a wide range of applications in acoustics, electromagnetics, optical fibers, medical imaging, geophysics, etc. The contributions in this volume reflect these themes and will be beneficial to researchers who are working in the area of applied inverse problems.
Direct Problems and Inverse Problems in Biometric Systems
Mihailescu Marius Iulian
2013-01-01
The article purpose is to describe the two sides of biometrics technologies, direct problems and inverse problems. The advance that we face today in field of Information Technology makes Information Security an inseparable part. The authentication has a huge role when we deal about security. The problems that can appear in implementing and developing biometrics systems is raising many problems, and one of the goal of this article is to focus on direct and inverse problems which is a new and c...
Inverse problem in Parker's dynamo
Reshetnyak, M Yu
2015-01-01
The inverse solution of the 1D Parker dynamo equations is considered. The method is based on minimization of the cost-function, which characterize deviation of the model solution properties from the desired ones. The output is the latitude distribution of the magnetic field generation sources: the $\\alpha$- and $\\omega$-effects. Minimization is made using the Monte-Carlo method. The details of the method, as well as some applications, which can be interesting for the broad dynamo community, are considered: conditions when the invisible for the observer at the surface of the planet toroidal part of the magnetic field is much larger than the poloidal counterpart. It is shown that at some particular distributions of $\\alpha$ and $\\omega$ the well-known thesis that sign of the dynamo-number defines equatorial symmetry of the magnetic field to the equator plane, is violated. It is also demonstrated in what circumstances magnetic field in the both hemispheres have different properties, and simple physical explanati...
Linear inverse problem of the reactor dynamics
Volkov, N. P.
2017-01-01
The aim of this work is the study transient processes in nuclear reactors. The mathematical model of the reactor dynamics excluding reverse thermal coupling is investigated. This model is described by a system of integral-differential equations, consisting of a non-stationary anisotropic multispeed kinetic transport equation and a delayed neutron balance equation. An inverse problem was formulated to determine the stationary part of the function source along with the solution of the direct problem. The author obtained sufficient conditions for the existence and uniqueness of a generalized solution of this inverse problem.
Molecular seismology: an inverse problem in nanobiology.
Hinow, Peter; Boczko, Erik M
2007-05-07
The density profile of an elastic fiber like DNA will change in space and time as ligands associate with it. This observation affords a new direction in single molecule studies provided that density profiles can be measured in space and time. In fact, this is precisely the objective of seismology, where the mathematics of inverse problems have been employed with success. We argue that inverse problems in elastic media can be directly applied to biophysical problems of fiber-ligand association, and demonstrate that robust algorithms exist to perform density reconstruction in the condensed phase.
Homometric point sets and inverse problems
Grimm, Uwe; Baake, Michael
2008-01-01
The inverse problem of diffraction theory in essence amounts to the reconstruction of the atomic positions of a solid from its diffraction image. From a mathematical perspective, this is a notoriously difficult problem, even in the idealised situation of perfect diffraction from an infinite structure.\\ud \\ud Here, the problem is analysed via the autocorrelation measure of the underlying point set, where two point sets are called homometric when they share the same autocorrelation. For the cla...
Direct and Inverse problems in Electrocardiography
Boulakia, M.; Fernández, M. A.; Gerbeau, J. F.; Zemzemi, N.
2008-09-01
We present numerical results related to the direct and the inverse problems in electrocardiography. The electrical activity of the heart is described by the bidomain equations. The electrocardiograms (ECGs) recorded in different points on the body surface are obtained by coupling the bidomain equation to a Laplace equation in the torso. The simulated ECGs are quite satisfactory. As regards the inverse problem, our goal is to estimate the parameters of the bidomain-torso model. Here we present some preliminary results of a parameter estimation for the torso model.
Introduction to inverse problems for differential equations
Hasanov Hasanoğlu, Alemdar
2017-01-01
This book presents a systematic exposition of the main ideas and methods in treating inverse problems for PDEs arising in basic mathematical models, though it makes no claim to being exhaustive. Mathematical models of most physical phenomena are governed by initial and boundary value problems for PDEs, and inverse problems governed by these equations arise naturally in nearly all branches of science and engineering. The book’s content, especially in the Introduction and Part I, is self-contained and is intended to also be accessible for beginning graduate students, whose mathematical background includes only basic courses in advanced calculus, PDEs and functional analysis. Further, the book can be used as the backbone for a lecture course on inverse and ill-posed problems for partial differential equations. In turn, the second part of the book consists of six nearly-independent chapters. The choice of these chapters was motivated by the fact that the inverse coefficient and source problems considered here a...
Inverse Problem for a Curved Quantum Guide
Directory of Open Access Journals (Sweden)
Laure Cardoulis
2012-01-01
Full Text Available We consider the Dirichlet Laplacian operator −Δ on a curved quantum guide in ℝ n(n=2,3 with an asymptotically straight reference curve. We give uniqueness results for the inverse problem associated to the reconstruction of the curvature by using either observations of spectral data or a boot-strapping method.
Inverse acoustic problem of N homogeneous scatterers
DEFF Research Database (Denmark)
Berntsen, Svend
2002-01-01
The three-dimensional inverse acoustic medium problem of N homogeneous objects with known geometry and location is considered. It is proven that one scattering experiment is sufficient for the unique determination of the complex wavenumbers of the objects. The mapping from the scattered fields...
Inverse and Ill-posed Problems Theory and Applications
Kabanikhin, S I
2011-01-01
The text demonstrates the methods for proving the existence (if et all) and finding of inverse and ill-posed problems solutions in linear algebra, integral and operator equations, integral geometry, spectral inverse problems, and inverse scattering problems. It is given comprehensive background material for linear ill-posed problems and for coefficient inverse problems for hyperbolic, parabolic, and elliptic equations. A lot of examples for inverse problems from physics, geophysics, biology, medicine, and other areas of application of mathematics are included.
The inverse variational problem in classical mechanics
Lopuszánski, Jan T
1999-01-01
This book provides a concise description of the current status of a fascinating scientific problem - the inverse variational problem in classical mechanics. The essence of this problem is as follows: one is given a set of equations of motion describing a certain classical mechanical system, and the question to be answered is: Do these equations of motion correspond to some Lagrange function as its Euler-Lagrange equations? In general, not for every system of equations of motion does a Lagrange function exist; it can, however, happen that one may modify the given equations of motion in such a w
Estimating uncertainties in complex joint inverse problems
Afonso, Juan Carlos
2016-04-01
Sources of uncertainty affecting geophysical inversions can be classified either as reflective (i.e. the practitioner is aware of her/his ignorance) or non-reflective (i.e. the practitioner does not know that she/he does not know!). Although we should be always conscious of the latter, the former are the ones that, in principle, can be estimated either empirically (by making measurements or collecting data) or subjectively (based on the experience of the researchers). For complex parameter estimation problems in geophysics, subjective estimation of uncertainty is the most common type. In this context, probabilistic (aka Bayesian) methods are commonly claimed to offer a natural and realistic platform from which to estimate model uncertainties. This is because in the Bayesian approach, errors (whatever their nature) can be naturally included as part of the global statistical model, the solution of which represents the actual solution to the inverse problem. However, although we agree that probabilistic inversion methods are the most powerful tool for uncertainty estimation, the common claim that they produce "realistic" or "representative" uncertainties is not always justified. Typically, ALL UNCERTAINTY ESTIMATES ARE MODEL DEPENDENT, and therefore, besides a thorough characterization of experimental uncertainties, particular care must be paid to the uncertainty arising from model errors and input uncertainties. We recall here two quotes by G. Box and M. Gunzburger, respectively, of special significance for inversion practitioners and for this session: "…all models are wrong, but some are useful" and "computational results are believed by no one, except the person who wrote the code". In this presentation I will discuss and present examples of some problems associated with the estimation and quantification of uncertainties in complex multi-observable probabilistic inversions, and how to address them. Although the emphasis will be on sources of uncertainty related
Analog fault diagnosis by inverse problem technique
Ahmed, Rania F.
2011-12-01
A novel algorithm for detecting soft faults in linear analog circuits based on the inverse problem concept is proposed. The proposed approach utilizes optimization techniques with the aid of sensitivity analysis. The main contribution of this work is to apply the inverse problem technique to estimate the actual parameter values of the tested circuit and so, to detect and diagnose single fault in analog circuits. The validation of the algorithm is illustrated through applying it to Sallen-Key second order band pass filter and the results show that the detecting percentage efficiency was 100% and also, the maximum error percentage of estimating the parameter values is 0.7%. This technique can be applied to any other linear circuit and it also can be extended to be applied to non-linear circuits. © 2011 IEEE.
Inverse vertical migration and feeding in glacier lanternfish (Benthosema glaciale)
Dypvik, Eivind
2011-11-08
A bottom-mounted upward-facing 38-kHz echo sounder was deployed at ~400 m and cabled to shore in Masfjorden (~60 52?N, ~5 24?E), Norway. The scattering layers seen during autumn (September-October) 2008 were identified by trawling. Glacier lanternfish (Benthosema glaciale) were mainly distributed below ~200 m and displayed three different diel behavioral strategies: normal diel vertical migration (NDVM), inverse DVM (IDVM) and no DVM (NoDVM). The IDVM group was the focus of this study. It consisted of 2-year and older individuals migrating to ~200-270 m during the daytime, while descending back to deeper than ~270 m during the night. Stomach content analysis revealed increased feeding during the daytime on overwintering Calanus sp. We conclude that visually searching glacier lanternfish performing IDVM benefit from the faint daytime light in mid-waters when preying on overwintering Calanus sp. 2011 The Author(s).
Differential equations inverse and direct problems
Favini, Angelo
2006-01-01
DEGENERATE FIRST ORDER IDENTIFICATION PROBLEMS IN BANACH SPACES A NONISOTHERMAL DYNAMICAL GINZBURG-LANDAU MODEL OF SUPERCONDUCTIVITY. EXISTENCE AND UNIQUENESS THEOREMSSOME GLOBAL IN TIME RESULTS FOR INTEGRODIFFERENTIAL PARABOLIC INVERSE PROBLEMSFOURTH ORDER ORDINARY DIFFERENTIAL OPERATORS WITH GENERAL WENTZELL BOUNDARY CONDITIONSTUDY OF ELLIPTIC DIFFERENTIAL EQUATIONS IN UMD SPACESDEGENERATE INTEGRODIFFERENTIAL EQUATIONS OF PARABOLIC TYPE EXPONENTIAL ATTRACTORS FOR SEMICONDUCTOR EQUATIONSCONVERGENCE TO STATIONARY STATES OF SOLUTIONS TO THE SEMILINEAR EQUATION OF VISCOELASTICITY ASYMPTOTIC BEHA
Voltammetry: mathematical modelling and Inverse Problem
Koshev, N A; Kuzina, V V
2016-01-01
We propose the fast semi-analytical method of modelling the polarization curves in the voltammetric experiment. The method is based on usage of the special func- tions and shows a big calculation speed and a high accuracy and stability. Low computational needs of the proposed algorithm allow us to state the set of Inverse Problems of voltammetry for the reconstruction of metal ions concentrations or the other parameters of the electrolyte under investigation.
Computationally efficient Bayesian inference for inverse problems.
Energy Technology Data Exchange (ETDEWEB)
Marzouk, Youssef M.; Najm, Habib N.; Rahn, Larry A.
2007-10-01
Bayesian statistics provides a foundation for inference from noisy and incomplete data, a natural mechanism for regularization in the form of prior information, and a quantitative assessment of uncertainty in the inferred results. Inverse problems - representing indirect estimation of model parameters, inputs, or structural components - can be fruitfully cast in this framework. Complex and computationally intensive forward models arising in physical applications, however, can render a Bayesian approach prohibitive. This difficulty is compounded by high-dimensional model spaces, as when the unknown is a spatiotemporal field. We present new algorithmic developments for Bayesian inference in this context, showing strong connections with the forward propagation of uncertainty. In particular, we introduce a stochastic spectral formulation that dramatically accelerates the Bayesian solution of inverse problems via rapid evaluation of a surrogate posterior. We also explore dimensionality reduction for the inference of spatiotemporal fields, using truncated spectral representations of Gaussian process priors. These new approaches are demonstrated on scalar transport problems arising in contaminant source inversion and in the inference of inhomogeneous material or transport properties. We also present a Bayesian framework for parameter estimation in stochastic models, where intrinsic stochasticity may be intermingled with observational noise. Evaluation of a likelihood function may not be analytically tractable in these cases, and thus several alternative Markov chain Monte Carlo (MCMC) schemes, operating on the product space of the observations and the parameters, are introduced.
Inverse problems in classical and quantum physics
Energy Technology Data Exchange (ETDEWEB)
Almasy, A.A.
2007-06-29
The subject of this thesis is in the area of Applied Mathematics known as Inverse Problems. Inverse problems are those where a set of measured data is analysed in order to get as much information as possible on a model which is assumed to represent a system in the real world. We study two inverse problems in the fields of classical and quantum physics: QCD condensates from tau-decay data and the inverse conductivity problem. Despite a concentrated effort by physicists extending over many years, an understanding of QCD from first principles continues to be elusive. Fortunately, data continues to appear which provide a rather direct probe of the inner workings of the strong interactions. We use a functional method which allows us to extract within rather general assumptions phenomenological parameters of QCD (the condensates) from a comparison of the time-like experimental data with asymptotic space-like results from theory. The price to be paid for the generality of assumptions is relatively large errors in the values of the extracted parameters. Although we do not claim that our method is superior to other approaches, we hope that our results lend additional confidence to the numerical results obtained with the help of methods based on QCD sum rules. EIT is a technology developed to image the electrical conductivity distribution of a conductive medium. The technique works by performing simultaneous measurements of direct or alternating electric currents and voltages on the boundary of an object. These are the data used by an image reconstruction algorithm to determine the electrical conductivity distribution within the object. In this thesis, two approaches of EIT image reconstruction are proposed. The first is based on reformulating the inverse problem in terms of integral equations. This method uses only a single set of measurements for the reconstruction. The second approach is an algorithm based on linearisation which uses more then one set of measurements. A
An Entropic Estimator for Linear Inverse Problems
Directory of Open Access Journals (Sweden)
Amos Golan
2012-05-01
Full Text Available In this paper we examine an Information-Theoretic method for solving noisy linear inverse estimation problems which encompasses under a single framework a whole class of estimation methods. Under this framework, the prior information about the unknown parameters (when such information exists, and constraints on the parameters can be incorporated in the statement of the problem. The method builds on the basics of the maximum entropy principle and consists of transforming the original problem into an estimation of a probability density on an appropriate space naturally associated with the statement of the problem. This estimation method is generic in the sense that it provides a framework for analyzing non-normal models, it is easy to implement and is suitable for all types of inverse problems such as small and or ill-conditioned, noisy data. First order approximation, large sample properties and convergence in distribution are developed as well. Analytical examples, statistics for model comparisons and evaluations, that are inherent to this method, are discussed and complemented with explicit examples.
Heuristics for the inversion median problem
2010-01-01
Background The study of genome rearrangements has become a mainstay of phylogenetics and comparative genomics. Fundamental in such a study is the median problem: given three genomes find a fourth that minimizes the sum of the evolutionary distances between itself and the given three. Many exact algorithms and heuristics have been developed for the inversion median problem, of which the best known is MGR. Results We present a unifying framework for median heuristics, which enables us to clarify existing strategies and to place them in a partial ordering. Analysis of this framework leads to a new insight: the best strategies continue to refer to the input data rather than reducing the problem to smaller instances. Using this insight, we develop a new heuristic for inversion medians that uses input data to the end of its computation and leverages our previous work with DCJ medians. Finally, we present the results of extensive experimentation showing that our new heuristic outperforms all others in accuracy and, especially, in running time: the heuristic typically returns solutions within 1% of optimal and runs in seconds to minutes even on genomes with 25'000 genes--in contrast, MGR can take days on instances of 200 genes and cannot be used beyond 1'000 genes. Conclusion Finding good rearrangement medians, in particular inversion medians, had long been regarded as the computational bottleneck in whole-genome studies. Our new heuristic for inversion medians, ASM, which dominates all others in our framework, puts that issue to rest by providing near-optimal solutions within seconds to minutes on even the largest genomes. PMID:20122203
Crestel, Benjamin; Alexanderian, Alen; Stadler, Georg; Ghattas, Omar
2017-07-01
The computational cost of solving an inverse problem governed by PDEs, using multiple experiments, increases linearly with the number of experiments. A recently proposed method to decrease this cost uses only a small number of random linear combinations of all experiments for solving the inverse problem. This approach applies to inverse problems where the PDE solution depends linearly on the right-hand side function that models the experiment. As this method is stochastic in essence, the quality of the obtained reconstructions can vary, in particular when only a small number of combinations are used. We develop a Bayesian formulation for the definition and computation of encoding weights that lead to a parameter reconstruction with the least uncertainty. We call these weights A-optimal encoding weights. Our framework applies to inverse problems where the governing PDE is nonlinear with respect to the inversion parameter field. We formulate the problem in infinite dimensions and follow the optimize-then-discretize approach, devoting special attention to the discretization and the choice of numerical methods in order to achieve a computational cost that is independent of the parameter discretization. We elaborate our method for a Helmholtz inverse problem, and derive the adjoint-based expressions for the gradient of the objective function of the optimization problem for finding the A-optimal encoding weights. The proposed method is potentially attractive for real-time monitoring applications, where one can invest the effort to compute optimal weights offline, to later solve an inverse problem repeatedly, over time, at a fraction of the initial cost.
On Inverse Topology Problem for Laplace Operators on Graphs
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Yu. Yu. Ershova
2014-12-01
Full Text Available Laplacian operators on finite compact metric graphs are considered under the assumption that matching conditions at graph vertices are of $\\delta$ type. Under one additional assumption, the inverse topology problem is treated. Using the apparatus of boundary triples, we generalize and extend existing results on necessary conditions of isospectrality of two Laplacians defined on different graphs. A result is also given covering the case of Schrodinger operators.
Inverse scattering problem in turbulent magnetic fluctuations
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R. A. Treumann
2016-08-01
Full Text Available We apply a particular form of the inverse scattering theory to turbulent magnetic fluctuations in a plasma. In the present note we develop the theory, formulate the magnetic fluctuation problem in terms of its electrodynamic turbulent response function, and reduce it to the solution of a special form of the famous Gelfand–Levitan–Marchenko equation of quantum mechanical scattering theory. The last of these applies to transmission and reflection in an active medium. The theory of turbulent magnetic fluctuations does not refer to such quantities. It requires a somewhat different formulation. We reduce the theory to the measurement of the low-frequency electromagnetic fluctuation spectrum, which is not the turbulent spectral energy density. The inverse theory in this form enables obtaining information about the turbulent response function of the medium. The dynamic causes of the electromagnetic fluctuations are implicit to it. Thus, it is of vital interest in low-frequency magnetic turbulence. The theory is developed until presentation of the equations in applicable form to observations of turbulent electromagnetic fluctuations as input from measurements. Solution of the final integral equation should be done by standard numerical methods based on iteration. We point to the possibility of treating power law fluctuation spectra as an example. Formulation of the problem to include observations of spectral power densities in turbulence is not attempted. This leads to severe mathematical problems and requires a reformulation of inverse scattering theory. One particular aspect of the present inverse theory of turbulent fluctuations is that its structure naturally leads to spatial information which is obtained from the temporal information that is inherent to the observation of time series. The Taylor assumption is not needed here. This is a consequence of Maxwell's equations, which couple space and time evolution. The inversion procedure takes
Minimal mass solutions to inverse eigenvalue problems
Gladwell, G. M. L.
2006-04-01
One of the fundamental inverse problems in vibration theory is to construct an in-line system of masses and springs, fixed at one end, free at the other, so that it has a specified spectrum of natural frequencies. The solution, based on the work pioneered by Gantmacher and Krein, makes use of a second spectrum, that for the system fixed at both ends. We derive a closed form procedure to construct the system with a minimal mass for given overall stiffness from the first specified spectrum. The analogous problem of constructing a discrete model of a cantilever beam in flexural vibration having a specified spectrum uses two additional spectra corresponding to the previously free end being respectively pinned and sliding. We formulate the problem of finding a minimal mass solution for the given length and stiffness, and obtain explicit solutions in simple cases.
Inverse Problems and High-Dimensional Estimation
Alquier, Pierre; Stoltz, Gilles
2011-01-01
The "Stats in the Chateau" summer school was held at the CRC chateau on the campus of HEC Paris, Jouy-en-Josas, France, from August 31 to September 4, 2009. This event was organized jointly by faculty members of three French academic institutions a" ENSAE ParisTech, the Ecole Polytechnique ParisTech, and HEC Paris a" which cooperate through a scientific foundation devoted to the decision sciences. The scientific content of the summer school was conveyed in two courses, one by Laurent Cavalier (Universite Aix-Marseille I) on "Ill-posed Inverse Problems", and one by
Bilinear Inverse Problems: Theory, Algorithms, and Applications
Ling, Shuyang
We will discuss how several important real-world signal processing problems, such as self-calibration and blind deconvolution, can be modeled as bilinear inverse problems and solved by convex and nonconvex optimization approaches. In Chapter 2, we bring together three seemingly unrelated concepts, self-calibration, compressive sensing and biconvex optimization. We show how several self-calibration problems can be treated efficiently within the framework of biconvex compressive sensing via a new method called SparseLift. More specifically, we consider a linear system of equations y = DAx, where the diagonal matrix D (which models the calibration error) is unknown and x is an unknown sparse signal. By "lifting" this biconvex inverse problem and exploiting sparsity in this model, we derive explicit theoretical guarantees under which both x and D can be recovered exactly, robustly, and numerically efficiently. In Chapter 3, we study the question of the joint blind deconvolution and blind demixing, i.e., extracting a sequence of functions [special characters omitted] from observing only the sum of their convolutions [special characters omitted]. In particular, for the special case s = 1, it becomes the well-known blind deconvolution problem. We present a non-convex algorithm which guarantees exact recovery under conditions that are competitive with convex optimization methods, with the additional advantage of being computationally much more efficient. We discuss several applications of the proposed framework in image processing and wireless communications in connection with the Internet-of-Things. In Chapter 4, we consider three different self-calibration models of practical relevance. We show how their corresponding bilinear inverse problems can be solved by both the simple linear least squares approach and the SVD-based approach. As a consequence, the proposed algorithms are numerically extremely efficient, thus allowing for real-time deployment. Explicit theoretical
Energy Technology Data Exchange (ETDEWEB)
Petit, J.L.
1997-07-21
This thesis is devoted to the inversion of VSP (vertical seismic profile) seismic data in order to determine the elastic properties of horizontally stratified media. The VSP records are computed using the full wave elastic modelling in isotropic and transversely isotropic media using Hankel transform, a finite difference scheme and an inverse Hankel transform algorithm, and the propagation equations are determined and numerically solved; the importance of considering a 3D wave propagation model instead of a 1 D one is emphasized. The theoretical VSP inverse problem is then considered, with the seismic waveform inversion set as a least-squares problem, consisting in recovering the distribution of physical parameters which minimize the misfit between calculated and observed VSP. The corresponding problem requires the knowledge of the source function
Inverse problems for partial differential equations
Isakov, Victor
2017-01-01
This third edition expands upon the earlier edition by adding nearly 40 pages of new material reflecting the analytical and numerical progress in inverse problems in last 10 years. As in the second edition, the emphasis is on new ideas and methods rather than technical improvements. These new ideas include use of the stationary phase method in the two-dimensional elliptic problems and of multi frequencies\\temporal data to improve stability and numerical resolution. There are also numerous corrections and improvements of the exposition throughout. This book is intended for mathematicians working with partial differential equations and their applications, physicists, geophysicists, and financial, electrical, and mechanical engineers involved with nondestructive evaluation, seismic exploration, remote sensing, and various kinds of tomography. Review of the second edition: "The first edition of this excellent book appeared in 1998 and became a standard reference for everyone interested in analysis and numerics of...
Inverse Variational Problem for Nonstandard Lagrangians
Saha, A.; Talukdar, B.
2014-06-01
In the mathematical physics literature the nonstandard Lagrangians (NSLs) were introduced in an ad hoc fashion rather than being derived from the solution of the inverse problem of variational calculus. We begin with the first integral of the equation of motion and solve the associated inverse problem to obtain some of the existing results for NSLs. In addition, we provide a number of alternative Lagrangian representations. The case studies envisaged by us include (i) the usual modified Emden-type equation, (ii) Emden-type equation with dissipative term quadratic in velocity, (iii) Lotka-Volterra model and (vi) a number of the generic equations for dissipative-like dynamical systems. Our method works for nonstandard Lagrangians corresponding to the usual action integral of mechanical systems but requires modification for those associated with the modified actions like S =∫abe L(x ,x˙ , t) dt and S =∫abL 1 - γ(x ,x˙ , t) dt because in the latter case one cannot construct expressions for the Jacobi integrals.
The inverse gravimetric problem in gravity modelling
Sanso, F.; Tscherning, C. C.
1989-01-01
One of the main purposes of geodesy is to determine the gravity field of the Earth in the space outside its physical surface. This purpose can be pursued without any particular knowledge of the internal density even if the exact shape of the physical surface of the Earth is not known, though this seems to entangle the two domains, as it was in the old Stoke's theory before the appearance of Molodensky's approach. Nevertheless, even when large, dense and homogeneous data sets are available, it was always recognized that subtracting from the gravity field the effect of the outer layer of the masses (topographic effect) yields a much smoother field. This is obviously more important when a sparse data set is bad so that any smoothing of the gravity field helps in interpolating between the data without raising the modeling error, this approach is generally followed because it has become very cheap in terms of computing time since the appearance of spectral techniques. The mathematical description of the Inverse Gravimetric Problem (IGP) is dominated mainly by two principles, which in loose terms can be formulated as follows: the knowledge of the external gravity field determines mainly the lateral variations of the density; and the deeper the density anomaly giving rise to a gravity anomaly, the more improperly posed is the problem of recovering the former from the latter. The statistical relation between rho and n (and its inverse) is also investigated in its general form, proving that degree cross-covariances have to be introduced to describe the behavior of rho. The problem of the simultaneous estimate of a spherical anomalous potential and of the external, topographic masses is addressed criticizing the choice of the mixed collection approach.
The inverse problem for Schwinger pair production
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F. Hebenstreit
2016-02-01
Full Text Available The production of electron–positron pairs in time-dependent electric fields (Schwinger mechanism depends non-linearly on the applied field profile. Accordingly, the resulting momentum spectrum is extremely sensitive to small variations of the field parameters. Owing to this non-linear dependence it is so far unpredictable how to choose a field configuration such that a predetermined momentum distribution is generated. We show that quantum kinetic theory along with optimal control theory can be used to approximately solve this inverse problem for Schwinger pair production. We exemplify this by studying the superposition of a small number of harmonic components resulting in predetermined signatures in the asymptotic momentum spectrum. In the long run, our results could facilitate the observation of this yet unobserved pair production mechanism in quantum electrodynamics by providing suggestions for tailored field configurations.
Numerical Methods for Bayesian Inverse Problems
Ernst, Oliver
2014-01-06
We present recent results on Bayesian inversion for a groundwater flow problem with an uncertain conductivity field. In particular, we show how direct and indirect measurements can be used to obtain a stochastic model for the unknown. The main tool here is Bayes’ theorem which merges the indirect data with the stochastic prior model for the conductivity field obtained by the direct measurements. Further, we demonstrate how the resulting posterior distribution of the quantity of interest, in this case travel times of radionuclide contaminants, can be obtained by Markov Chain Monte Carlo (MCMC) simulations. Moreover, we investigate new, promising MCMC methods which exploit geometrical features of the posterior and which are suited to infinite dimensions.
Stochastic inverse problems: Models and metrics
Sabbagh, Elias H.; Sabbagh, Harold A.; Murphy, R. Kim; Aldrin, John C.; Annis, Charles; Knopp, Jeremy S.
2015-03-01
In past work, we introduced model-based inverse methods, and applied them to problems in which the anomaly could be reasonably modeled by simple canonical shapes, such as rectangular solids. In these cases the parameters to be inverted would be length, width and height, as well as the occasional probe lift-off or rotation. We are now developing a formulation that allows more flexibility in modeling complex flaws. The idea consists of expanding the flaw in a sequence of basis functions, and then solving for the expansion coefficients of this sequence, which are modeled as independent random variables, uniformly distributed over their range of values. There are a number of applications of such modeling: 1. Connected cracks and multiple half-moons, which we have noted in a POD set. Ideally we would like to distinguish connected cracks from one long shallow crack. 2. Cracks of irregular profile and shape which have appeared in cold work holes during bolt-hole eddy-current inspection. One side of such cracks is much deeper than other. 3. L or C shaped crack profiles at the surface, examples of which have been seen in bolt-hole cracks. By formulating problems in a stochastic sense, we are able to leverage the stochastic global optimization algorithms in NLSE, which is resident in VIC-3D®, to answer questions of global minimization and to compute confidence bounds using the sensitivity coefficient that we get from NLSE. We will also address the issue of surrogate functions which are used during the inversion process, and how they contribute to the quality of the estimation of the bounds.
Stochastic inverse problems: Models and metrics
Energy Technology Data Exchange (ETDEWEB)
Sabbagh, Elias H.; Sabbagh, Harold A.; Murphy, R. Kim [Victor Technologies, LLC, Bloomington, IN 47407-7706 (United States); Aldrin, John C. [Computational Tools, Gurnee, IL 60031 (United States); Annis, Charles [Statistical Engineering, Palm Beach Gardens, FL 33418 (United States); Knopp, Jeremy S. [Air Force Research Laboratory (AFRL/RXCA), Wright Patterson AFB, OH 45433-7817 (United States)
2015-03-31
In past work, we introduced model-based inverse methods, and applied them to problems in which the anomaly could be reasonably modeled by simple canonical shapes, such as rectangular solids. In these cases the parameters to be inverted would be length, width and height, as well as the occasional probe lift-off or rotation. We are now developing a formulation that allows more flexibility in modeling complex flaws. The idea consists of expanding the flaw in a sequence of basis functions, and then solving for the expansion coefficients of this sequence, which are modeled as independent random variables, uniformly distributed over their range of values. There are a number of applications of such modeling: 1. Connected cracks and multiple half-moons, which we have noted in a POD set. Ideally we would like to distinguish connected cracks from one long shallow crack. 2. Cracks of irregular profile and shape which have appeared in cold work holes during bolt-hole eddy-current inspection. One side of such cracks is much deeper than other. 3. L or C shaped crack profiles at the surface, examples of which have been seen in bolt-hole cracks. By formulating problems in a stochastic sense, we are able to leverage the stochastic global optimization algorithms in NLSE, which is resident in VIC-3D®, to answer questions of global minimization and to compute confidence bounds using the sensitivity coefficient that we get from NLSE. We will also address the issue of surrogate functions which are used during the inversion process, and how they contribute to the quality of the estimation of the bounds.
Inverse Problems in a Bayesian Setting
Matthies, Hermann G.
2016-02-13
In a Bayesian setting, inverse problems and uncertainty quantification (UQ)—the propagation of uncertainty through a computational (forward) model—are strongly connected. In the form of conditional expectation the Bayesian update becomes computationally attractive. We give a detailed account of this approach via conditional approximation, various approximations, and the construction of filters. Together with a functional or spectral approach for the forward UQ there is no need for time-consuming and slowly convergent Monte Carlo sampling. The developed sampling-free non-linear Bayesian update in form of a filter is derived from the variational problem associated with conditional expectation. This formulation in general calls for further discretisation to make the computation possible, and we choose a polynomial approximation. After giving details on the actual computation in the framework of functional or spectral approximations, we demonstrate the workings of the algorithm on a number of examples of increasing complexity. At last, we compare the linear and nonlinear Bayesian update in form of a filter on some examples.
A Bayesian Level Set Method for Geometric Inverse Problems
Iglesias, Marco; Lu, Yulong; Stuart, Andrew
2015-01-01
We introduce a level set based approach to Bayesian geometric inverse problems. In these problems the interface between different domains is the key unknown, and is realized as the level set of a function. This function itself becomes the object of the inference. Whilst the level set methodology has been widely used for the solution of geometric inverse problems, the Bayesian formulation that we develop here contains two significant advances: firstly it leads to a well-posed inverse problem i...
PREFACE: International Conference on Inverse Problems 2010
Hon, Yiu-Chung; Ling, Leevan
2011-03-01
Following the first International Conference on Inverse Problems - Recent Theoretical Development and Numerical Approaches held at the City University of Hong Kong in 2002, the fifth International Conference was held again at the City University during December 13-17, 2010. This fifth conference was jointly organized by Professor Yiu-Chung Hon (Co-Chair, City University of Hong Kong, HKSAR), Dr Leevan Ling (Co-Chair, Hong Kong Baptist University, HKSAR), Professor Jin Cheng (Fudan University, China), Professor June-Yub Lee (Ewha Womans University, South Korea), Professor Gui-Rong Liu (University of Cincinnati, USA), Professor Jenn-Nan Wang (National Taiwan University, Taiwan), and Professor Masahiro Yamamoto (The University of Tokyo, Japan). It was agreed to alternate holding the conference among the above places (China, Japan, Korea, Taiwan, and Hong Kong) once every two years. The next conference has been scheduled to be held at the Southeast University (Nanjing, China) in 2012. The purpose of this series of conferences is to establish a strong collaborative link among the universities of the Asian-Pacific regions and worldwide leading researchers in inverse problems. The conference addressed both theoretical (mathematics), applied (engineering) and developmental aspects of inverse problems. The conference was intended to nurture Asian-American-European collaborations in the evolving interdisciplinary areas and it was envisioned that the conference would lead to long-term commitments and collaborations among the participating countries and researchers. There was a total of more than 100 participants. A call for the submission of papers was sent out after the conference, and a total of 19 papers were finally accepted for publication in this proceedings. The papers included in the proceedings cover a wide scope, which reflects the current flourishing theoretical and numerical research into inverse problems. Finally, as the co-chairs of the Inverse Problems
Inverse problems and inverse scattering of plane waves
Ghosh Roy, Dilip N
2001-01-01
The purpose of this text is to present the theory and mathematics of inverse scattering, in a simple way, to the many researchers and professionals who use it in their everyday research. While applications range across a broad spectrum of disciplines, examples in this text will focus primarly, but not exclusively, on acoustics. The text will be especially valuable for those applied workers who would like to delve more deeply into the fundamentally mathematical character of the subject matter.Practitioners in this field comprise applied physicists, engineers, and technologists, whereas the theory is almost entirely in the domain of abstract mathematics. This gulf between the two, if bridged, can only lead to improvement in the level of scholarship in this highly important discipline. This is the book''s primary focus.
An inverse problem for space and time fractional evolution equation ...
African Journals Online (AJOL)
We consider an inverse problem for a space and time fractional evolution equation, interpolating the heat and wave equations, with an involution. Existence and uniqueness results for the given problem are obtained via the method of separation of variables. Key words: Inverse problem, fractional, fractional evolution ...
Large-Scale Inverse Problems and Quantification of Uncertainty
Biegler, Lorenz; Ghattas, Omar
2010-01-01
Large-scale inverse problems and associated uncertainty quantification has become an important area of research, central to a wide range of science and engineering applications. Written by leading experts in the field, Large-scale Inverse Problems and Quantification of Uncertainty focuses on the computational methods used to analyze and simulate inverse problems. The text provides PhD students, researchers, advanced undergraduate students, and engineering practitioners with the perspectives of researchers in areas of inverse problems and data assimilation, ranging from statistics and large-sca
Inverse Problem;Litho_Inversion; Geology and Geophysics
Antonio, Guillen; Gabriel, Courrioux; Bernard, Bourgine
2015-04-01
Subsurface modeling is a key tool to describe, understand and quantify geological processes. As the subsurface is inaccessible and its observation is limited by acquisition methods, 3D models of the subsurface are usually built from the interpretation of sparse data with limited resolution. Therefore, uncertainties occur during the model building process, due to possible cognitive human biais, natural variability of geological objects and intrinsic uncertainties of data. In such context, the predictibility of models is limited by uncertainties, which must be assessed in order to reduce economical and human risks linked to the use of models. This work focuses more specifically on uncertainties about geological structures. In this context, a stochastic method is developed for generating structural models with various fault and horizon geometries as well as fault connections. Realistic geological objects are obtained using implicit modeling that represents a surface by an equipotential of a volumetric scalar field. Faults have also been described by a reduced set of uncertain parameters, which opens the way to the inversion of structural objects using geophysical data by baysian methods.
Formulas in inverse and ill-posed problems
Anikonov, Yu E
1997-01-01
The Inverse and Ill-Posed Problems Series is a series of monographs publishing postgraduate level information on inverse and ill-posed problems for an international readership of professional scientists and researchers. The series aims to publish works which involve both theory and applications in, e.g., physics, medicine, geophysics, acoustics, electrodynamics, tomography, and ecology.
Inverse Modelling Problems in Linear Algebra Undergraduate Courses
Martinez-Luaces, Victor E.
2013-01-01
This paper will offer an analysis from a theoretical point of view of mathematical modelling, applications and inverse problems of both causation and specification types. Inverse modelling problems give the opportunity to establish connections between theory and practice and to show this fact, a simple linear algebra example in two different…
Ogawa, Hiroshi; Minami, Kimitaka; Kawamoto, Tohru; Kanai, Ramon; Ishikawa, Kohei; Kamimura, Ryuichi
2017-09-01
Evaluation of vertical distribution of radiocesium in bottom sediment by measuring vertical γ-ray count profile was discussed. A stable inversion formula was derived based on the maximum entropy method. Efficiency of the formula was confirmed by using a low-cost apparatus composed of an array of PIN photodiodes and a single board computer with real-time inversion code. In-door experiment by using five model sediment disks showed good reproducibility of vertical radiocesium profile. On-site experiment was also carried out at a pond in Fukushima to confirm the efficiency. It was suggested that combination of the simple apparatus and MEM inversion formula gave reasonable estimates on vertical radiocesium distribution in bottom sediment of 1 kBq/kg-wet level within about 10 min. Copyright © 2017 Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
A. Rozanov
2007-09-01
Full Text Available This paper is devoted to an intercomparison of ozone vertical profiles retrieved from the measurements of scattered solar radiation performed by the SCIAMACHY instrument in the limb viewing geometry. Three different inversion algorithms including the prototype of the operational Level 1 to 2 processor to be operated by the European Space Agency are considered. Unlike usual validation studies, this comparison removes the uncertainties arising when comparing measurements made by different instruments probing slightly different air masses and focuses on the uncertainties specific to the modeling-retrieval problem only. The intercomparison was performed for 5 selected orbits of SCIAMACHY showing a good overall agreement of the results in the middle stratosphere, whereas considerable discrepancies were identified in the lower stratosphere and upper troposphere altitude region. Additionally, comparisons with ground-based lidar measurements are shown for selected profiles demonstrating an overall correctness of the retrievals.
An inverse heat conduction problem of estimating thermal conductivity
Shidfar, S
2002-01-01
In this paper we consider an inverse heat conduction problem. We define the inverse and direct problem and solve the direct problem by method of Lines. We estimated the thermal conductivity k(u) which is assumed k(u)=k sub o +k sub 1 u+...+k sub N u sup N and contiguously in the direction normal to the surface of a sample plate.
An Inverse Eigenvalue Problem for Jacobi Matrices
Directory of Open Access Journals (Sweden)
Zhengsheng Wang
2011-01-01
eigenvectors. The solvability of the problem is discussed, and some sufficient conditions for existence of the solution of this problem are proposed. Furthermore, a numerical algorithm and two examples are presented.
REGULARIZED D-BAR METHOD FOR THE INVERSE CONDUCTIVITY PROBLEM
DEFF Research Database (Denmark)
Knudsen, Kim; Lassas, Matti; Mueller, Jennifer
2009-01-01
A strategy for regularizing the inversion procedure for the two-dimensional D-bar reconstruction algorithm based on the global uniqueness proof of Nachman [Ann. Math. 143 (1996)] for the ill-posed inverse conductivity problem is presented. The strategy utilizes truncation of the boundary integral...
Spectral solution of the inverse Mie problem
Romanov, Andrey V.; Konokhova, Anastasiya I.; Yastrebova, Ekaterina S.; Gilev, Konstantin V.; Strokotov, Dmitry I.; Chernyshev, Andrei V.; Maltsev, Valeri P.; Yurkin, Maxim A.
2017-10-01
We developed a fast method to determine size and refractive index of homogeneous spheres from the power Fourier spectrum of their light-scattering patterns (LSPs), measured with the scanning flow cytometer. Specifically, we used two spectral parameters: the location of the non-zero peak and zero-frequency amplitude, and numerically inverted the map from the space of particle characteristics (size and refractive index) to the space of spectral parameters. The latter parameters can be reliably resolved only for particle size parameter greater than 11, and the inversion is unique only in the limited range of refractive index with upper limit between 1.1 and 1.25 (relative to the medium) depending on the size parameter and particular definition of uniqueness. The developed method was tested on two experimental samples, milk fat globules and spherized red blood cells, and resulted in accuracy not worse than the reference method based on the least-square fit of the LSP with the Mie theory. Moreover, for particles with significant deviation from the spherical shape the spectral method was much closer to the Mie-fit result than the estimated uncertainty of the latter. The spectral method also showed adequate results for synthetic LSPs of spheroids with aspect ratios up to 1.4. Overall, we present a general framework, which can be used to construct an inverse algorithm for any other experimental signals.
Applications of elliptic Carleman inequalities to Cauchy and inverse problems
Choulli, Mourad
2016-01-01
This book presents a unified approach to studying the stability of both elliptic Cauchy problems and selected inverse problems. Based on elementary Carleman inequalities, it establishes three-ball inequalities, which are the key to deriving logarithmic stability estimates for elliptic Cauchy problems and are also useful in proving stability estimates for certain elliptic inverse problems. The book presents three inverse problems, the first of which consists in determining the surface impedance of an obstacle from the far field pattern. The second problem investigates the detection of corrosion by electric measurement, while the third concerns the determination of an attenuation coefficient from internal data, which is motivated by a problem encountered in biomedical imaging.
Inverse problem of Ocean Acoustic Tomography (OAT) - A numerical experiment
Digital Repository Service at National Institute of Oceanography (India)
Murty, T.V.R.; Somayajulu, Y.K.; Mahadevan, R.; Murty, C.S.
layers, or grids developEd. by solving the forward problem of the acoustic model enable build the generalized inverse operator (GIO) that operates on the travel time perturbation data. Resolution matrices obtained through SVD helped to examine...
Carleman estimates and applications to inverse problems for hyperbolic systems
Bellassoued, Mourad
2017-01-01
This book is a self-contained account of the method based on Carleman estimates for inverse problems of determining spatially varying functions of differential equations of the hyperbolic type by non-overdetermining data of solutions. The formulation is different from that of Dirichlet-to-Neumann maps and can often prove the global uniqueness and Lipschitz stability even with a single measurement. These types of inverse problems include coefficient inverse problems of determining physical parameters in inhomogeneous media that appear in many applications related to electromagnetism, elasticity, and related phenomena. Although the methodology was created in 1981 by Bukhgeim and Klibanov, its comprehensive development has been accomplished only recently. In spite of the wide applicability of the method, there are few monographs focusing on combined accounts of Carleman estimates and applications to inverse problems. The aim in this book is to fill that gap. The basic tool is Carleman estimates, the theory of wh...
Inverse kinematics problem in robotics using neural networks
Choi, Benjamin B.; Lawrence, Charles
1992-01-01
In this paper, Multilayer Feedforward Networks are applied to the robot inverse kinematic problem. The networks are trained with endeffector position and joint angles. After training, performance is measured by having the network generate joint angles for arbitrary endeffector trajectories. A 3-degree-of-freedom (DOF) spatial manipulator is used for the study. It is found that neural networks provide a simple and effective way to both model the manipulator inverse kinematics and circumvent the problems associated with algorithmic solution methods.
Piecewise polynomial solutions to linear inverse problems
DEFF Research Database (Denmark)
Hansen, Per Christian; Mosegaard, K.
1996-01-01
We have presented a new algorithm PP-TSVD that computes piecewise polynomial solutions to ill-posed problems, without a priori knowledge about the positions of the break points. In particular, we can compute piecewise constant functions that describe layered models. Such solutions are useful, e.g.......g., in seismological problems, and the algorithm can also be used as a preprocessor for other methods where break points/discontinuities must be incorporated explicitly....
An inverse problem from condensed matter physics
Lai, Ru-Yu; Shankar, Ravi; Spirn, Daniel; Uhlmann, Gunther
2017-11-01
We consider the problem of reconstructing the features of a weak anisotropic background potential by the trajectories of vortex dipoles in a nonlinear Gross–Pitaevskii equation. At leading order, the dynamics of vortex dipoles are given by a Hamiltonian system. If the background potential is sufficiently smooth and flat, the background can be reconstructed using ideas from the boundary and the lens rigidity problems. We prove that reconstructions are unique, derive an approximate reconstruction formula, and present numerical examples.
Inverse problems in vision and 3D tomography
Mohamad-Djafari, Ali
2013-01-01
The concept of an inverse problem is a familiar one to most scientists and engineers, particularly in the field of signal and image processing, imaging systems (medical, geophysical, industrial non-destructive testing, etc.) and computer vision. In imaging systems, the aim is not just to estimate unobserved images, but also their geometric characteristics from observed quantities that are linked to these unobserved quantities through the forward problem. This book focuses on imagery and vision problems that can be clearly written in terms of an inverse problem where an estimate for the image a
Inverse and Control Problems in Electromagnetics
1994-10-14
Fernandes. Automatic adjustments for the removal of irregular frequencies in frce.-surface two-dimensional problems, Int. Symp. in Offshore Eng., Rio de...arbitrary cross seccion shape, IEEE Trants. Antennas and Propagation AP-13 (1965) 334-341. [16] A. Roger, Newton -Kantorovitch algorithm applied to an
The Vertical Linear Fractional Initialization Problem
Lorenzo, Carl F.; Hartley, Tom T.
1999-01-01
This paper presents a solution to the initialization problem for a system of linear fractional-order differential equations. The scalar problem is considered first, and solutions are obtained both generally and for a specific initialization. Next the vector fractional order differential equation is considered. In this case, the solution is obtained in the form of matrix F-functions. Some control implications of the vector case are discussed. The suggested method of problem solution is shown via an example.
Stabilizing inverse problems by internal data
Kuchment, Peter
2012-07-30
Several newly developing hybrid imaging methods (e.g., those combining electrical impedance or optical imaging with acoustics) enable one to obtain some auxiliary interior information (usually some combination of the electrical conductivity and the current) about the parameters of the tissues. This information, in turn, happens to stabilize the exponentially unstable and thus low-resolution optical and electrical impedance tomography. Various known instances of this effect have been studied individually. We show that there is a simple general technique (covering all known cases) that shows what kinds of interior data stabilize the reconstruction, and why. Namely, we show when the linearized problem becomes an elliptic pseudo-differential one, and thus stable. Stability here is meant as the problem being Fredholm, so the local uniqueness is not shown and probably does not hold in such generality. © 2012 IOP Publishing Ltd.
Crookes, Kate; Hayward, William G.
2012-01-01
Presenting a face inverted (upside down) disrupts perceptual sensitivity to the spacing between the features. Recently, it has been shown that this disruption is greater for vertical than horizontal changes in eye position. One explanation for this effect proposed that inversion disrupts the processing of long-range (e.g., eye-to-mouth distance)…
On the inverse problem for a heat-like equation
Directory of Open Access Journals (Sweden)
Igor Malyshev
1987-01-01
Full Text Available Using the integral representation of the solution of the boundary value problem for the equation with one time-dependent coefficient at the highest space-derivative three inverse problems are solved. Depending on the property of the coefficient we consider cases when the equation is of the parabolic type and two special cases of the degenerate/mixed type. In the parabolic case the corresponding inverse problem is reduced to the nonlinear Volterra integral equation for which the uniqueness of the solution is proved. For the special cases explicit formulae are derived. Both Ã‚Â“minimalÃ‚Â” and overspecified boundary data are considered.
One-dimensional inverse problems of mathematical physics
Lavrent'ev, M M; Yakhno, V G; Schulenberger, J R
1986-01-01
This monograph deals with the inverse problems of determining a variable coefficient and right side for hyperbolic and parabolic equations on the basis of known solutions at fixed points of space for all times. The problems are one-dimensional in nature since the desired coefficient of the equation is a function of only one coordinate, while the desired right side is a function only of time. The authors use methods based on the spectral theory of ordinary differential operators of second order and also methods which make it possible to reduce the investigation of the inverse problems to the in
Inverse problems basics, theory and applications in geophysics
Richter, Mathias
2016-01-01
The overall goal of the book is to provide access to the regularized solution of inverse problems relevant in geophysics without requiring more mathematical knowledge than is taught in undergraduate math courses for scientists and engineers. From abstract analysis only the concept of functions as vectors is needed. Function spaces are introduced informally in the course of the text, when needed. Additionally, a more detailed, but still condensed introduction is given in Appendix B. A second goal is to elaborate the single steps to be taken when solving an inverse problem: discretization, regularization and practical solution of the regularized optimization problem. These steps are shown in detail for model problems from the fields of inverse gravimetry and seismic tomography. The intended audience is mathematicians, physicists and engineers having a good working knowledge of linear algebra and analysis at the upper undergraduate level.
Inverse problems in ordinary differential equations and applications
Llibre, Jaume
2016-01-01
This book is dedicated to study the inverse problem of ordinary differential equations, that is it focuses in finding all ordinary differential equations that satisfy a given set of properties. The Nambu bracket is the central tool in developing this approach. The authors start characterizing the ordinary differential equations in R^N which have a given set of partial integrals or first integrals. The results obtained are applied first to planar polynomial differential systems with a given set of such integrals, second to solve the 16th Hilbert problem restricted to generic algebraic limit cycles, third for solving the inverse problem for constrained Lagrangian and Hamiltonian mechanical systems, fourth for studying the integrability of a constrained rigid body. Finally the authors conclude with an analysis on nonholonomic mechanics, a generalization of the Hamiltonian principle, and the statement an solution of the inverse problem in vakonomic mechanics.
Turbulence Nature and the Inverse Problem
Pyatnitsky, L. N
2009-01-01
Hydrodynamic equations well describe averaged parameters of turbulent steady flows, at least in pipes where boundary conditions can be estimated. The equations might outline the parameters fluctuations as well, if entry conditions at current boundaries were known. This raises, in addition, the more comprehensive problem of the primary perturbation nature, noted by H.A. Lorentz, which still remains unsolved. Generally, any flow steadiness should be supported by pressure waves emitted by some external source, e.g. a piston or a receiver. The wave plane front in channels quickly takes convex configuration owing to Rayleigh's law of diffraction divergence. The Schlieren technique and pressure wave registration were employed to investigate the wave interaction with boundary layer, while reflecting from the channel wall. The reflection induces boundary-layer local separation and following pressure rapid increase within the perturbation zone. It propagates as an acoustic wave packet of spherical shape, bearing oscil...
Reducing complexity of inverse problems using geostatistical priors
DEFF Research Database (Denmark)
Hansen, Thomas Mejer; Mosegaard, Klaus; Cordua, Knud Skou
In a probabilistic formulation of inverse problems the solution can be given as a sample of the posterior probability distribution. All realizations retained in the posterior sample are consistent with both an assumed prior model and observed data. Some inverse problems are unsolvable, in that one...... can practically never hope to generate a posterior sample, others are just ’difficult’ and require special methods to become tractable, while others again are easily solved. We discuss how difficult nonlinear inverse problems can be handled such that their complexity, i.e. the time taken to obtain...... a posterior sample, can be reduced significantly using informed priors based on geostatistical models. We discuss two approaches to include such geostatistically based prior information. One is based on a parametric description of the prior likelihood that applies to 2-point based statistical models...
Iterative Reconstruction Methods for Hybrid Inverse Problems in Impedance Tomography
DEFF Research Database (Denmark)
Hoffmann, Kristoffer; Knudsen, Kim
2014-01-01
impedance imaging, magnetic resonance electrical impedance tomography, and ultrasound modulated electrical impedance tomography, and the unified approach to the reconstruction problem encompasses several algorithms suggested in the literature. The four proposed algorithms are implemented numerically in two......For a general formulation of hybrid inverse problems in impedance tomography the Picard and Newton iterative schemes are adapted and four iterative reconstruction algorithms are developed. The general problem formulation includes several existing hybrid imaging modalities such as current density...
Deep Convolutional Neural Network for Inverse Problems in Imaging.
Jin, Kyong Hwan; McCann, Michael T; Froustey, Emmanuel; Unser, Michael
2017-06-15
In this paper, we propose a novel deep convolutional neural network (CNN)-based algorithm for solving ill-posed inverse problems. Regularized iterative algorithms have emerged as the standard approach to ill-posed inverse problems in the past few decades. These methods produce excellent results, but can be challenging to deploy in practice due to factors including the high computational cost of the forward and adjoint operators and the difficulty of hyper parameter selection. The starting point of our work is the observation that unrolled iterative methods have the form of a CNN (filtering followed by point-wise nonlinearity) when the normal operator ( H*H where H* is the adjoint of the forward imaging operator, H ) of the forward model is a convolution. Based on this observation, we propose using direct inversion followed by a CNN to solve normal-convolutional inverse problems. The direct inversion encapsulates the physical model of the system, but leads to artifacts when the problem is ill-posed; the CNN combines multiresolution decomposition and residual learning in order to learn to remove these artifacts while preserving image structure. We demonstrate the performance of the proposed network in sparse-view reconstruction (down to 50 views) on parallel beam X-ray computed tomography in synthetic phantoms as well as in real experimental sinograms. The proposed network outperforms total variation-regularized iterative reconstruction for the more realistic phantoms and requires less than a second to reconstruct a 512 x 512 image on the GPU.
Deep Convolutional Neural Network for Inverse Problems in Imaging
Jin, Kyong Hwan; McCann, Michael T.; Froustey, Emmanuel; Unser, Michael
2017-09-01
In this paper, we propose a novel deep convolutional neural network (CNN)-based algorithm for solving ill-posed inverse problems. Regularized iterative algorithms have emerged as the standard approach to ill-posed inverse problems in the past few decades. These methods produce excellent results, but can be challenging to deploy in practice due to factors including the high computational cost of the forward and adjoint operators and the difficulty of hyper parameter selection. The starting point of our work is the observation that unrolled iterative methods have the form of a CNN (filtering followed by point-wise non-linearity) when the normal operator (H*H, the adjoint of H times H) of the forward model is a convolution. Based on this observation, we propose using direct inversion followed by a CNN to solve normal-convolutional inverse problems. The direct inversion encapsulates the physical model of the system, but leads to artifacts when the problem is ill-posed; the CNN combines multiresolution decomposition and residual learning in order to learn to remove these artifacts while preserving image structure. We demonstrate the performance of the proposed network in sparse-view reconstruction (down to 50 views) on parallel beam X-ray computed tomography in synthetic phantoms as well as in real experimental sinograms. The proposed network outperforms total variation-regularized iterative reconstruction for the more realistic phantoms and requires less than a second to reconstruct a 512 x 512 image on GPU.
A tutorial on inverse problems for anomalous diffusion processes
Jin, Bangti; Rundell, William
2015-03-01
Over the last two decades, anomalous diffusion processes in which the mean squares variance grows slower or faster than that in a Gaussian process have found many applications. At a macroscopic level, these processes are adequately described by fractional differential equations, which involves fractional derivatives in time or/and space. The fractional derivatives describe either history mechanism or long range interactions of particle motions at a microscopic level. The new physics can change dramatically the behavior of the forward problems. For example, the solution operator of the time fractional diffusion diffusion equation has only limited smoothing property, whereas the solution for the space fractional diffusion equation may contain weak singularity. Naturally one expects that the new physics will impact related inverse problems in terms of uniqueness, stability, and degree of ill-posedness. The last aspect is especially important from a practical point of view, i.e., stably reconstructing the quantities of interest. In this paper, we employ a formal analytic and numerical way, especially the two-parameter Mittag-Leffler function and singular value decomposition, to examine the degree of ill-posedness of several ‘classical’ inverse problems for fractional differential equations involving a Djrbashian-Caputo fractional derivative in either time or space, which represent the fractional analogues of that for classical integral order differential equations. We discuss four inverse problems, i.e., backward fractional diffusion, sideways problem, inverse source problem and inverse potential problem for time fractional diffusion, and inverse Sturm-Liouville problem, Cauchy problem, backward fractional diffusion and sideways problem for space fractional diffusion. It is found that contrary to the wide belief, the influence of anomalous diffusion on the degree of ill-posedness is not definitive: it can either significantly improve or worsen the conditioning of
Structured Sparsity Regularization Approach to the EEG Inverse Problem
DEFF Research Database (Denmark)
Montoya-Martinez, Jair; Artes-Rodriguez, Antonio; Hansen, Lars Kai
2012-01-01
Localization of brain activity involves solving the EEG inverse problem, which is an undetermined ill-posed problem. We propose a novel approach consisting in estimating, using structured sparsity regularization techniques, the Brain Electrical Sources (BES) matrix directly in the spatio......-temporal source space. We use proximal splitting optimization methods, which are efficient optimization techniques, with good convergence rates and with the ability to handle large nonsmooth convex problems, which is the typical scenario in the EEG inverse problem. We have evaluated our approach under a simulated...... scenario, consisting in estimating a synthetic BES matrix with 5124 sources. We report results using ℓ1 (LASSO), ℓ1/ℓ2 (Group LASSO) and ℓ1 + ℓ1/ℓ2 (Sparse Group LASSO) regularizers....
Dimensionality Reduction and Uncertainty Quantification for Inverse Problems
van Leeuwen, Tristan
2015-01-01
Many inverse problems in science and engineering involve multi-experiment data and thus require a large number of forward simulations. Dimensionality reduction techniques aim at reducing the number of forward solves by (randomly) subsampling the data. In the special case of non-linear least-squares
Geophysics in Hydrogeological Inverse Problem: Hero or Villain?
Alcolea, A.; Renard, P.; Mariethoz, G.
2007-12-01
Geostatistical inverse problem is a powerful tool to aid decision-makers in aquifer management. During the last few years, existing inverse problem codes have been updated in order to accommodate "non- traditional" types of observations (i.e. heads or concentrations). The potential of exhaustive geophysical data has been shown to be well-suited for aquifer characterization. However, limited attention has been devoted to the use of this information in real field hydrogeological inverse problems. In this work, we present an application of inverse problem to the management of coastal aquifers including different types of data (heads, resistivities and prior information on transmissivity and storage coefficient). Spatial variability is characterized using the regularized pilot points method. The procedure is as follows. First, we obtain a characterization of the transmissivity and storage coefficient fields from calibration data. Second, this characterization is used to design a pumping network by means of a genetic algorithm. Several constraints apply, such as operational costs or environmental side effects. Three cases are presented, depending on the calibration data sets: (1) only resistivities (no calibration is performed), (2) heads and prior information of model parameters, and (3) all of them altogether (resistivities are used as external drift). Results show that, by themselves, resistivity or head data sets (and prior information) do not suffice to obtain a reliable characterization of the system. However, the consideration of all data at the same time leads to the best characterization of the system among the ones tested.
A comparative analysis of algorithms for the magnetoencephalography inverse problem
Sorrentino, A.; Pascarella, A.; Campi, C.; Piana, M.
2008-11-01
We present a comparison of three methods for the solution of the magnetoencephalography inverse problem. The methods are: an eigenspace projected beamformer, an algorithm implementing multiple signal classification with recursively applied projection and a particle filter for Bayesian tracking. Synthetic data with neurophysiological significance are analyzed by the three methods to recover position and amplitude time course of the active sources.
A mathematical framework for inverse wave problems in heterogeneous media
Blazek, K.D.; Stolk, C.; Symes, W.W.
2013-01-01
This paper provides a theoretical foundation for some common formulations of inverse problems in wave propagation, based on hyperbolic systems of linear integro-differential equations with bounded and measurable coefficients. The coefficients of these time-dependent partial differential equations
Data-Driven Model Order Reduction for Bayesian Inverse Problems
Cui, Tiangang
2014-01-06
One of the major challenges in using MCMC for the solution of inverse problems is the repeated evaluation of computationally expensive numerical models. We develop a data-driven projection- based model order reduction technique to reduce the computational cost of numerical PDE evaluations in this context.
Solving probabilistic inverse problems rapidly with prior samples
Käufl, Paul; Valentine, Andrew P.|info:eu-repo/dai/nl/364418680; de Wit, Ralph W.|info:eu-repo/dai/nl/344668908; Trampert, Jeannot|info:eu-repo/dai/nl/304829250
2016-01-01
Owing to the increasing availability of computational resources, in recent years the probabilistic solution of non-linear, geophysical inverse problems by means of sampling methods has become increasingly feasible. Nevertheless, we still face situations in which a Monte Carlo approach is not
An inverse Sturm–Liouville problem with a fractional derivative
Jin, Bangti
2012-05-01
In this paper, we numerically investigate an inverse problem of recovering the potential term in a fractional Sturm-Liouville problem from one spectrum. The qualitative behaviors of the eigenvalues and eigenfunctions are discussed, and numerical reconstructions of the potential with a Newton method from finite spectral data are presented. Surprisingly, it allows very satisfactory reconstructions for both smooth and discontinuous potentials, provided that the order . α∈. (1,. 2) of fractional derivative is sufficiently away from 2. © 2012 Elsevier Inc.
A regularized GMRES method for inverse blackbody radiation problem
Directory of Open Access Journals (Sweden)
Wu Jieer
2013-01-01
Full Text Available The inverse blackbody radiation problem is focused on determining temperature distribution of a blackbody from measured total radiated power spectrum. This problem consists of solving a first kind of Fredholm integral equation and many numerical methods have been proposed. In this paper, a regularized GMRES method is presented to solve the linear ill-posed problem caused by the discretization of such an integral equation. This method projects the orignal problem onto a lower dimensional subspaces by the Arnoldi process. Tikhonov regularization combined with GCV criterion is applied to stabilize the numerical iteration process. Three numerical examples indicate the effectiveness of the regularized GMRES method.
Uhlmann, Gunther
2008-07-01
This volume represents the proceedings of the fourth Applied Inverse Problems (AIP) international conference and the first congress of the Inverse Problems International Association (IPIA) which was held in Vancouver, Canada, June 25 29, 2007. The organizing committee was formed by Uri Ascher, University of British Columbia, Richard Froese, University of British Columbia, Gary Margrave, University of Calgary, and Gunther Uhlmann, University of Washington, chair. The conference was part of the activities of the Pacific Institute of Mathematical Sciences (PIMS) Collaborative Research Group on inverse problems (http://www.pims.math.ca/scientific/collaborative-research-groups/past-crgs). This event was also supported by grants from NSF and MITACS. Inverse Problems (IP) are problems where causes for a desired or an observed effect are to be determined. They lie at the heart of scientific inquiry and technological development. The enormous increase in computing power and the development of powerful algorithms have made it possible to apply the techniques of IP to real-world problems of growing complexity. Applications include a number of medical as well as other imaging techniques, location of oil and mineral deposits in the earth's substructure, creation of astrophysical images from telescope data, finding cracks and interfaces within materials, shape optimization, model identification in growth processes and, more recently, modelling in the life sciences. The series of Applied Inverse Problems (AIP) Conferences aims to provide a primary international forum for academic and industrial researchers working on all aspects of inverse problems, such as mathematical modelling, functional analytic methods, computational approaches, numerical algorithms etc. The steering committee of the AIP conferences consists of Heinz Engl (Johannes Kepler Universität, Austria), Joyce McLaughlin (RPI, USA), William Rundell (Texas A&M, USA), Erkki Somersalo (Helsinki University of Technology
SIAM conference on inverse problems: Geophysical applications. Final technical report
Energy Technology Data Exchange (ETDEWEB)
NONE
1995-12-31
This conference was the second in a series devoted to a particular area of inverse problems. The theme of this series is to discuss problems of major scientific importance in a specific area from a mathematical perspective. The theme of this symposium was geophysical applications. In putting together the program we tried to include a wide range of mathematical scientists and to interpret geophysics in as broad a sense as possible. Our speaker came from industry, government laboratories, and diverse departments in academia. We managed to attract a geographically diverse audience with participation from five continents. There were talks devoted to seismology, hydrology, determination of the earth`s interior on a global scale as well as oceanographic and atmospheric inverse problems.
A Bayesian approach to linear inverse problems in seismic tomography
Tian, Y.; Zhou, Y.; Chung, J.; Chung, M.; Ning, J.
2014-12-01
Seismic tomography is often an ill-posed linear inverse problem and regularization such as damping and smoothing has been widely applied to find an approximate solution to the inverse problem. The "optimal" solution is chosen based on the tradeoff between model norm (or model roughness) and data misfit. The main difficulty associated with this deterministic approach is in determining a balance between model uncertainty and data fit. This can make interpretation of tomographic structures subjective because models at the "corner" of the tradeoff curve often show large variability. In this study, we investigate a Bayesian approach to the linear inverse problem by minimizing an empirical Bayes risk function based on training dataset generated for the tomographic problem. We show that sample average approximation can be used to find optimal spectral filters to solve the linear tomographic problem based on singular value decomposition (SVD). We compare optimal truncated SVD, optimal Tikhonov filtering as well as independent optimal spectral filtering in finite-frequency tomography and ray theoretical tomography using a global dataset of surface-wave dispersion measurements.
An Inverse Problem Approach for Elasticity Imaging through Vibroacoustics
Aguilo, Miguel A.; Brigham, J. C.; Aquino, W.; Fatemi, M.
2011-01-01
A new methodology for estimating the spatial distribution of elastic moduli using the steady-state dynamic response of solids immersed in fluids is presented. The technique relies on the ensuing acoustic pressure field from a remotely excited solid to inversely estimate the spatial distribution of Young’s modulus. This work proposes the use of Gaussian radial basis functions (GRBF) to represent the spatial variation of elastic moduli. GRBF are shown to possess the advantage of representing smooth functions with quasi-compact support, and can efficiently represent elastic moduli distributions such as those that occur in soft biological tissue in the presence of tumors. The direct problem consists of a coupled acoustic-structure interaction boundary value problem solved in the frequency domain using the finite element method. The inverse problem is cast as an optimization problem in which the objective function is defined as a measure of discrepancy between an experimentally measured response and a finite element representation of the system. Non-gradient based optimization algorithms in combination with a divide and conquer strategy are used to solve the resulting optimization problem. The feasibility of the proposed approach is demonstrated through a series of numerical and a physical experiment. For comparison purposes, the surface velocity response was also used for the inverse characterization as the measured response in place of the acoustic pressure. PMID:20335092
Integral geometry and inverse problems for hyperbolic equations
Romanov, V G
1974-01-01
There are currently many practical situations in which one wishes to determine the coefficients in an ordinary or partial differential equation from known functionals of its solution. These are often called "inverse problems of mathematical physics" and may be contrasted with problems in which an equation is given and one looks for its solution under initial and boundary conditions. Although inverse problems are often ill-posed in the classical sense, their practical importance is such that they may be considered among the pressing problems of current mathematical re search. A. N. Tihonov showed [82], [83] that there is a broad class of inverse problems for which a particular non-classical definition of well-posed ness is appropriate. This new definition requires that a solution be unique in a class of solutions belonging to a given subset M of a function space. The existence of a solution in this set is assumed a priori for some set of data. The classical requirement of continuous dependence of the solutio...
Vertical and horizontal spheroidal boundary-value problems
Šprlák, Michal; Tangdamrongsub, Natthachet
2017-12-01
Vertical and horizontal spheroidal boundary-value problems (BVPs), i.e., determination of the external gravitational potential from the components of the gravitational gradient on the spheroid, are discussed in this article. The gravitational gradient is decomposed into the series of the vertical and horizontal vector spheroidal harmonics, before being orthogonalized in a weighted sense by two different approaches. The vertical and horizontal spheroidal BVPs are then formulated and solved in the spectral and spatial domains. Both orthogonalization methods provide the same analytical solutions for the vertical spheroidal BVP, and give distinct, but equivalent, analytical solutions for the horizontal spheroidal BVP. A closed-loop simulation is performed to test the correctness of the analytical solutions, and we investigate analytical properties of the sub-integral kernels. The systematic treatment of the spheroidal BVPs and the resulting mathematical equations extend the theoretical apparatus of geodesy and of the potential theory.
Reflectance of acoustic horns and solution of the inverse problem
Rasetshwane, Daniel M.; Neely, Stephen T.; Allen, Jont B.; Shera, Christopher A.
2012-01-01
A method is described for solving the inverse problem of determining the profile of an acoustic horn when time-domain reflectance (TDR) is known only at the entrance. The method involves recasting Webster’s horn equation in terms of forward and backward propagating wave variables. An essential feature of this method is a requirement that the backward propagating wave be continuous at the wave-front at all locations beyond the entrance. Derivation of the inverse solution raises questions about the meaning of causality in the context of wave propagation in non-uniform tubes. Exact reflectance expressions are presented for infinite exponential, conical and parabolic horns based on exact solutions of the horn equation. Diameter functions obtained with the inverse solution are a good match to all three horn profiles. PMID:22423684
Inverse problem of estimating interface conductance between periodically contacting surfaces
Energy Technology Data Exchange (ETDEWEB)
Orlande, H.R.B.; Ozisik, M.N. (North Carolina State Univ., Raleigh (United States))
1993-06-01
The conjugate gradient method of minimization with adjoint equation is used to solve the inverse problem of estimating the timewise variation of interface conductance between periodically contacting solids, under quasi-steady-state conditions. It is assumed that no prior information is available on the functional form of the interface conductance, except the magnitude of the period. The accuracy of the inverse analysis is examined by using simulated inexact temperature measurements obtained at the interior of the region. Small periods are usually the most difficult on which to perform an inverse analysis. For such cases, the present method is found to be more accurate and stable than the B-Spline approach. 19 refs.
Energy Technology Data Exchange (ETDEWEB)
Ferreira, Nirardo Roberto; Porsani, Milton Jose [Bahia Univ., Salvador, BA (Brazil)
1997-07-01
Inversion of DC resistivity sounding is a nonlinear problem. Local or global optimization methods are commonly used to solve it. Local methods are fast but require that the start method be close to the true solution and may be trapped in local minimum. Global methods are robust, but computationally expensive since the space is usually very large. Here we combine the genetic algorithm (AG) with the linearized inversion method, Gauss-Newton, to overcome their limitations and explore the advantages of the two methods. The algorithm was tested with a 1-D Schlumberger resistivity sounding data and its performance was compared with pure AG. The joint operation improves the convergence even when using a reduced population of methods. (author)
A hybrid algorithm for solving inverse problems in elasticity
Directory of Open Access Journals (Sweden)
Barabasz Barbara
2014-12-01
Full Text Available The paper offers a new approach to handling difficult parametric inverse problems in elasticity and thermo-elasticity, formulated as global optimization ones. The proposed strategy is composed of two phases. In the first, global phase, the stochastic hp-HGS algorithm recognizes the basins of attraction of various objective minima. In the second phase, the local objective minimizers are closer approached by steepest descent processes executed singly in each basin of attraction. The proposed complex strategy is especially dedicated to ill-posed problems with multimodal objective functionals. The strategy offers comparatively low computational and memory costs resulting from a double-adaptive technique in both forward and inverse problem domains. We provide a result on the Lipschitz continuity of the objective functional composed of the elastic energy and the boundary displacement misfits with respect to the unknown constitutive parameters. It allows common scaling of the accuracy of solving forward and inverse problems, which is the core of the introduced double-adaptive technique. The capability of the proposed method of finding multiple solutions is illustrated by a computational example which consists in restoring all feasible Young modulus distributions minimizing an objective functional in a 3D domain of a photo polymer template obtained during step and flash imprint lithography.
Inverse Problem of Ultrasound Beamforming with Sparsity Constraints and Regularization.
Ozkan, Ece; Vishnevsky, Valeriy; Goksel, Orcun
2017-09-28
Ultrasound (US) beamforming is the process of reconstructing an image from acquired echo traces on several transducer elements. Typical beamforming approaches, such as Delay-And-Sum, perform simple projection operations, while techniques using statistical information also exist, e.g. adaptive, phase-coherence, Delay-Multiply-And-Sum, and sparse coding approaches. Inspired by the feasibility and success of inverse problem formulations in several image reconstruction problems, such as computed tomography, we herein devise an inverse problem approach for US beamforming. We define a linear forward model for the synthesis of the beamformed image, and solve its inverse problem thanks to several intuitive and physicsbased constraints and regularization terms proposed. These reflect the prior knowledge about the spectra of carrier signal and spatial coherence of modulated signal. These constraints admit effective formulation through sparse representations. Our proposed method was evaluated for plane-wave imaging (PWI) that transmits unfocused waves, enabling high frame-rates with large field of view at the expense of much lower image quality with conventional beamforming techniques. Results are evaluated in numerical simulations, as well as tissue-mimicking phantoms and in-vivo data provided by Plane-wave Imaging Challenge in Medical UltraSound (PICMUS). The best results achieved by our proposed techniques are 0.39mm full-width at half-maximum for spatial resolution and 16.3 dB contrast-to-noise ratio, using a single plane-wave transmit.
Two hybrid regularization frameworks for solving the electrocardiography inverse problem
Energy Technology Data Exchange (ETDEWEB)
Jiang Mingfeng; Xia Ling; Shou Guofa; Liu Feng [Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027 (China); Crozier, Stuart [School of Information Technology and Electrical Engineering, University of Queensland, St. Lucia, Brisbane, Queensland 4072 (Australia)], E-mail: xialing@zju.edu.cn
2008-09-21
In this paper, two hybrid regularization frameworks, LSQR-Tik and Tik-LSQR, which integrate the properties of the direct regularization method (Tikhonov) and the iterative regularization method (LSQR), have been proposed and investigated for solving ECG inverse problems. The LSQR-Tik method is based on the Lanczos process, which yields a sequence of small bidiagonal systems to approximate the original ill-posed problem and then the Tikhonov regularization method is applied to stabilize the projected problem. The Tik-LSQR method is formulated as an iterative LSQR inverse, augmented with a Tikhonov-like prior information term. The performances of these two hybrid methods are evaluated using a realistic heart-torso model simulation protocol, in which the heart surface source method is employed to calculate the simulated epicardial potentials (EPs) from the action potentials (APs), and then the acquired EPs are used to calculate simulated body surface potentials (BSPs). The results show that the regularized solutions obtained by the LSQR-Tik method are approximate to those of the Tikhonov method, the computational cost of the LSQR-Tik method, however, is much less than that of the Tikhonov method. Moreover, the Tik-LSQR scheme can reconstruct the epcicardial potential distribution more accurately, specifically for the BSPs with large noisy cases. This investigation suggests that hybrid regularization methods may be more effective than separate regularization approaches for ECG inverse problems.
Two hybrid regularization frameworks for solving the electrocardiography inverse problem
Jiang, Mingfeng; Xia, Ling; Shou, Guofa; Liu, Feng; Crozier, Stuart
2008-09-01
In this paper, two hybrid regularization frameworks, LSQR-Tik and Tik-LSQR, which integrate the properties of the direct regularization method (Tikhonov) and the iterative regularization method (LSQR), have been proposed and investigated for solving ECG inverse problems. The LSQR-Tik method is based on the Lanczos process, which yields a sequence of small bidiagonal systems to approximate the original ill-posed problem and then the Tikhonov regularization method is applied to stabilize the projected problem. The Tik-LSQR method is formulated as an iterative LSQR inverse, augmented with a Tikhonov-like prior information term. The performances of these two hybrid methods are evaluated using a realistic heart-torso model simulation protocol, in which the heart surface source method is employed to calculate the simulated epicardial potentials (EPs) from the action potentials (APs), and then the acquired EPs are used to calculate simulated body surface potentials (BSPs). The results show that the regularized solutions obtained by the LSQR-Tik method are approximate to those of the Tikhonov method, the computational cost of the LSQR-Tik method, however, is much less than that of the Tikhonov method. Moreover, the Tik-LSQR scheme can reconstruct the epcicardial potential distribution more accurately, specifically for the BSPs with large noisy cases. This investigation suggests that hybrid regularization methods may be more effective than separate regularization approaches for ECG inverse problems.
Numerical method for an inverse dynamical problem for composite beams
Morassi, Antonino; Nakamura, Gen; Shirota, Kenji; Sini, Mourad
2007-06-01
In this paper we present a numerical method for an inverse problem of nondestructive testing for a composite system formed by the connection of a steel beam and a reinforced concrete beam. The small vibrations of the composite beam are governed in space by two second order and two fourth order differential operators, which are coupled in the lower order terms by two coefficients which express the shearing and axial stiffness of the connection. Our inverse problem is to determine these stiffness coefficients by using Neumann type boundary data measured at one end of the beam and transversal displacements given in an interior portion of the beam axis. We recast the inverse problem as a constrained variational issue and an iterated projected gradient method is proposed for the numerical solution of the minimizing problem. Suitable clip-off and mollifier operators are introduced in order to describe the constrained conditions. The effectiveness of method and the sensitivity of the results to errors in the measured data are tested on the basis of an extensive series of numerical experiments.
Convolutional Neural Networks for Inverse Problems in Imaging: A Review
McCann, Michael T.; Jin, Kyong Hwan; Unser, Michael
2017-11-01
In this survey paper, we review recent uses of convolution neural networks (CNNs) to solve inverse problems in imaging. It has recently become feasible to train deep CNNs on large databases of images, and they have shown outstanding performance on object classification and segmentation tasks. Motivated by these successes, researchers have begun to apply CNNs to the resolution of inverse problems such as denoising, deconvolution, super-resolution, and medical image reconstruction, and they have started to report improvements over state-of-the-art methods, including sparsity-based techniques such as compressed sensing. Here, we review the recent experimental work in these areas, with a focus on the critical design decisions: Where does the training data come from? What is the architecture of the CNN? and How is the learning problem formulated and solved? We also bring together a few key theoretical papers that offer perspective on why CNNs are appropriate for inverse problems and point to some next steps in the field.
An agent-oriented hierarchic strategy for solving inverse problems
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Smołka Maciej
2015-09-01
Full Text Available The paper discusses the complex, agent-oriented hierarchic memetic strategy (HMS dedicated to solving inverse parametric problems. The strategy goes beyond the idea of two-phase global optimization algorithms. The global search performed by a tree of dependent demes is dynamically alternated with local, steepest descent searches. The strategy offers exceptionally low computational costs, mainly because the direct solver accuracy (performed by the hp-adaptive finite element method is dynamically adjusted for each inverse search step. The computational cost is further decreased by the strategy employed for solution inter-processing and fitness deterioration. The HMS efficiency is compared with the results of a standard evolutionary technique, as well as with the multi-start strategy on benchmarks that exhibit typical inverse problems’ difficulties. Finally, an HMS application to a real-life engineering problem leading to the identification of oil deposits by inverting magnetotelluric measurements is presented. The HMS applicability to the inversion of magnetotelluric data is also mathematically verified.
MAP estimators and their consistency in Bayesian nonparametric inverse problems
Dashti, M.
2013-09-01
We consider the inverse problem of estimating an unknown function u from noisy measurements y of a known, possibly nonlinear, map applied to u. We adopt a Bayesian approach to the problem and work in a setting where the prior measure is specified as a Gaussian random field μ0. We work under a natural set of conditions on the likelihood which implies the existence of a well-posed posterior measure, μy. Under these conditions, we show that the maximum a posteriori (MAP) estimator is well defined as the minimizer of an Onsager-Machlup functional defined on the Cameron-Martin space of the prior; thus, we link a problem in probability with a problem in the calculus of variations. We then consider the case where the observational noise vanishes and establish a form of Bayesian posterior consistency for the MAP estimator. We also prove a similar result for the case where the observation of can be repeated as many times as desired with independent identically distributed noise. The theory is illustrated with examples from an inverse problem for the Navier-Stokes equation, motivated by problems arising in weather forecasting, and from the theory of conditioned diffusions, motivated by problems arising in molecular dynamics. © 2013 IOP Publishing Ltd.
Inverse problem of HIV cell dynamics using Genetic Algorithms
González, J. A.; Guzmán, F. S.
2017-01-01
In order to describe the cell dynamics of T-cells in a patient infected with HIV, we use a flavour of Perelson's model. This is a non-linear system of Ordinary Differential Equations that describes the evolution of healthy, latently infected, infected T-cell concentrations and the free viral cells. Different parameters in the equations give different dynamics. Considering the concentration of these types of cells is known for a particular patient, the inverse problem consists in estimating the parameters in the model. We solve this inverse problem using a Genetic Algorithm (GA) that minimizes the error between the solutions of the model and the data from the patient. These errors depend on the parameters of the GA, like mutation rate and population, although a detailed analysis of this dependence will be described elsewhere.
Changes in habitat of fish populations: An inverse problem.
Levere, Kimberly M
2016-08-01
Mathematical modelling applies to a wide variety of application areas, and is an active area of research in many disciplines. It is often the case that accurate depiction of real-world phenomena require increasingly complex models. Unfortunately, this increased complexity in a model causes great difficulty when seeking solutions. What is more, developing a model with known parameters that produces results consistent with observed behaviors may prove to be a difficult or even impossible task. These difficulties have brought about an interest in inverse problems. In this paper we utilize a collage-based approach to solve an inverse problem for a model for the migration of three fish species through floodplain waters. A derivation of the mathematical model is presented and a generalized collage method is discussed and applied to this model to recover diffusion parameters. Theoretical and numerical particulars are discussed and results are presented. Copyright © 2016 Elsevier Inc. All rights reserved.
A variational Bayesian method to inverse problems with impulsive noise
Jin, Bangti
2012-01-01
We propose a novel numerical method for solving inverse problems subject to impulsive noises which possibly contain a large number of outliers. The approach is of Bayesian type, and it exploits a heavy-tailed t distribution for data noise to achieve robustness with respect to outliers. A hierarchical model with all hyper-parameters automatically determined from the given data is described. An algorithm of variational type by minimizing the Kullback-Leibler divergence between the true posteriori distribution and a separable approximation is developed. The numerical method is illustrated on several one- and two-dimensional linear and nonlinear inverse problems arising from heat conduction, including estimating boundary temperature, heat flux and heat transfer coefficient. The results show its robustness to outliers and the fast and steady convergence of the algorithm. © 2011 Elsevier Inc.
Some special cases of the electromagnetic inverse problem
Weston, V. H.
1972-01-01
A review of exact techniques for determining the surface of a three-dimensional perfectly conducting body is given, followed by some new results on the uniqueness question concerning the number of measurements that may be required to explicitly determine the surface of the body. It is then shown that the inhomogeneous but spherically symmetric dielectric electromagnetic case is reducible to a scalar inverse problem that can be treated by known techniques.
Gradiometry - an Inverse Problem in Modern Satellite Geodesy
Freeden, Willi; Schneider, F.; Schreiner, Michael
1996-01-01
Satellite gradiometry and its instrumentation is an ultra-sensitive detection technique of the space gravitational gradient (i.e. the Hesse tensor of the gravitational potential). Gradeometry will be of great significance in inertial navigation, gravity survey, geodynamics and earthquake prediction research. In this paper, satellite gradiometry formulated as an inverse problem of satellite geodesy is discussed from two mathematical aspects: Firstly, satellite gradiometry is considered as a co...
Parallel Tempering for sampling and optimization in seismic inverse problems
Sambridge, Malcolm
2013-04-01
The field of seismology is rich with inverse problems. Seismologists are constantly seeking new ways to use seismic waveforms, and data products derived from them, to constrain subsurface structure in the form of Earth properties in 1-, 2- and 3 dimensions, as well as seismic sources in space and time. Every approach has its limitations and a virtual smorgasbord of methods exist, and have been applied over thirty years, with varying degrees of success. In this presentation we discuss a new class of approach. Parallel Tempering (PT) is a technique originating in the field of computational statistics that is finding increasing success for probabilistic sampling problems in astro and quantum physics, and more recently ocean acoustics but appears to be virtually unknown in the solid earth geosciences. In seismology two classes of inference approach are common for nonlinear inverse problems, Bayesian (probabilistic) sampling and optimization. Parallel Tempering can be applied to both situations and is related to better known methods such as Simulated Annealing and Metropolis Sampling. PT is distinguished as it has a theoretical basis for being superior to both. PT is best viewed as a `meta' algorithm. In a sense wrapping around existing optimization or Bayesian sampling methods to facilitate more robust performance (optimization) and more rapid exploration of parameter space (sampling). PT has generated much interest across the physical sciences with encouraging results emerging. This presentation will describe the basic ideas, and present results of implementations on seismic waveform inversion for both sampling and optimization.
The Inverse Optimal Problem: A Dynamic Programming Approach.
Chang, Fwu-Ranq
1988-01-01
This paper solves the stochastic inverse optimal problem. Dynamic programming is used to transform the origina l problem into a differential equation. A solution exists for any pro duction function with a finite slope at the origin provided the savin gs function, starting from the origin, is steep initially and flat ev entually. Three consumption functions-linear, Keynes-ian, and Cantabr igian-are also studied with a Cobb-Douglas production technology. A w ell-known result in discrete time mo...
The Neuroelectromagnetic Inverse Problem and the Zero Dipole Localization Error
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Rolando Grave de Peralta
2009-01-01
Full Text Available A tomography of neural sources could be constructed from EEG/MEG recordings once the neuroelectromagnetic inverse problem (NIP is solved. Unfortunately the NIP lacks a unique solution and therefore additional constraints are needed to achieve uniqueness. Researchers are then confronted with the dilemma of choosing one solution on the basis of the advantages publicized by their authors. This study aims to help researchers to better guide their choices by clarifying what is hidden behind inverse solutions oversold by their apparently optimal properties to localize single sources. Here, we introduce an inverse solution (ANA attaining perfect localization of single sources to illustrate how spurious sources emerge and destroy the reconstruction of simultaneously active sources. Although ANA is probably the simplest and robust alternative for data generated by a single dominant source plus noise, the main contribution of this manuscript is to show that zero localization error of single sources is a trivial and largely uninformative property unable to predict the performance of an inverse solution in presence of simultaneously active sources. We recommend as the most logical strategy for solving the NIP the incorporation of sound additional a priori information about neural generators that supplements the information contained in the data.
Obtaining sparse distributions in 2D inverse problems
Reci, A.; Sederman, A. J.; Gladden, L. F.
2017-08-01
The mathematics of inverse problems has relevance across numerous estimation problems in science and engineering. L1 regularization has attracted recent attention in reconstructing the system properties in the case of sparse inverse problems; i.e., when the true property sought is not adequately described by a continuous distribution, in particular in Compressed Sensing image reconstruction. In this work, we focus on the application of L1 regularization to a class of inverse problems; relaxation-relaxation, T1-T2, and diffusion-relaxation, D-T2, correlation experiments in NMR, which have found widespread applications in a number of areas including probing surface interactions in catalysis and characterizing fluid composition and pore structures in rocks. We introduce a robust algorithm for solving the L1 regularization problem and provide a guide to implementing it, including the choice of the amount of regularization used and the assignment of error estimates. We then show experimentally that L1 regularization has significant advantages over both the Non-Negative Least Squares (NNLS) algorithm and Tikhonov regularization. It is shown that the L1 regularization algorithm stably recovers a distribution at a signal to noise ratio concentrations of a mixture of hexane and dodecane present within porous silica beads immersed within a bulk liquid phase; neither NNLS nor Tikhonov regularization are able to provide this resolution. This experimental study shows that the approach enables discrimination between different chemical species when direct spectroscopic discrimination is impossible, and hence measurement of chemical composition within porous media, such as catalysts or rocks, is possible while still being stable to high levels of noise.
Source localization in electromyography using the inverse potential problem
van den Doel, Kees; Ascher, Uri M.; Pai, Dinesh K.
2011-02-01
We describe an efficient method for reconstructing the activity in human muscles from an array of voltage sensors on the skin surface. MRI is used to obtain morphometric data which are segmented into muscle tissue, fat, bone and skin, from which a finite element model for volume conduction is constructed. The inverse problem of finding the current sources in the muscles is solved using a careful regularization technique which adds a priori information, yielding physically reasonable solutions from among those that satisfy the basic potential problem. Several regularization functionals are considered and numerical experiments on a 2D test model are performed to determine which performs best. The resulting scheme leads to numerical difficulties when applied to large-scale 3D problems. We clarify the nature of these difficulties and provide a method to overcome them, which is shown to perform well in the large-scale problem setting.
Inference in infinite-dimensional inverse problems - Discretization and duality
Stark, Philip B.
1992-01-01
Many techniques for solving inverse problems involve approximating the unknown model, a function, by a finite-dimensional 'discretization' or parametric representation. The uncertainty in the computed solution is sometimes taken to be the uncertainty within the parametrization; this can result in unwarranted confidence. The theory of conjugate duality can overcome the limitations of discretization within the 'strict bounds' formalism, a technique for constructing confidence intervals for functionals of the unknown model incorporating certain types of prior information. The usual computational approach to strict bounds approximates the 'primal' problem in a way that the resulting confidence intervals are at most long enough to have the nominal coverage probability. There is another approach based on 'dual' optimization problems that gives confidence intervals with at least the nominal coverage probability. The pair of intervals derived by the two approaches bracket a correct confidence interval. The theory is illustrated with gravimetric, seismic, geomagnetic, and helioseismic problems and a numerical example in seismology.
Reconstruction Methods for Inverse Problems with Partial Data
DEFF Research Database (Denmark)
Hoffmann, Kristoffer
Impedance Tomography, and Ultrasound Modulated Electrical Impedance Tomography. After giving an introduction to hybrid inverse problems in impedance tomography and the mathematical tools that facilitate the related analysis, we explain in detail the stability properties associated with the classification...... in the case of a non-elliptic problem. To conduct a numerical analysis, we develop four iterative reconstruction methods using the Picard and Newton iterative schemes, and the unified approach to the reconstruction problem encompasses several algorithms suggested in the literature. The algorithms...... are implemented numerically in two dimensions and the properties of the algorithms and their implementations are investigated theoretically. Novel numerical results are presented for both the full and partial data problem, and they show similarities and differences between the proposed algorithms, which...
A model for the inverse 1-median problem on trees under uncertain costs
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Kien Trung Nguyen
2016-01-01
Full Text Available We consider the problem of justifying vertex weights of a tree under uncertain costs so that a prespecified vertex become optimal and the total cost should be optimal in the uncertainty scenario. We propose a model which delivers the information about the optimal cost which respect to each confidence level \\(\\alpha \\in [0,1]\\. To obtain this goal, we first define an uncertain variable with respect to the minimum cost in each confidence level. If all costs are independently linear distributed, we present the inverse distribution function of this uncertain variable in \\(O(n^{2}\\log n\\ time, where \\(n\\ is the number of vertices in the tree.
Inverse problem for in vivo NMR spatial localization
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Hasenfeld, A.C.
1985-11-01
The basic physical problem of NMR spatial localization is considered. To study diseased sites, one must solve the problem of adequately localizing the NMR signal. We formulate this as an inverse problem. As the NMR Bloch equations determine the motion of nuclear spins in applied magnetic fields, a theoretical study is undertaken to answer the question of how to design magnetic field configurations to achieve these localized excited spin populations. Because of physical constraints in the production of the relevant radiofrequency fields, the problem factors into a temporal one and a spatial one. We formulate the temporal problem as a nonlinear transformation, called the Bloch Transform, from the rf input to the magnetization response. In trying to invert this transformation, both linear (for the Fourier Transform) and nonlinear (for the Bloch Transform) modes of radiofrequency excitation are constructed. The spatial problem is essentially a statics problem for the Maxwell equations of electromagnetism, as the wavelengths of the radiation considered are on the order of ten meters, and so propagation effects are negligible. In the general case, analytic solutions are unavailable, and so the methods of computer simulation are used to map the rf field spatial profiles. Numerical experiments are also performed to verify the theoretical analysis, and experimental confirmation of the theory is carried out on the 0.5 Tesla IBM/Oxford Imaging Spectrometer at the LBL NMR Medical Imaging Facility. While no explicit inverse is constructed to ''solve'' this problem, the combined theoretical/numerical analysis is validated experimentally, justifying the approximations made. 56 refs., 31 figs.
Sparse stochastic processes and discretization of linear inverse problems.
Bostan, Emrah; Kamilov, Ulugbek S; Nilchian, Masih; Unser, Michael
2013-07-01
We present a novel statistically-based discretization paradigm and derive a class of maximum a posteriori (MAP) estimators for solving ill-conditioned linear inverse problems. We are guided by the theory of sparse stochastic processes, which specifies continuous-domain signals as solutions of linear stochastic differential equations. Accordingly, we show that the class of admissible priors for the discretized version of the signal is confined to the family of infinitely divisible distributions. Our estimators not only cover the well-studied methods of Tikhonov and l1-type regularizations as particular cases, but also open the door to a broader class of sparsity-promoting regularization schemes that are typically nonconvex. We provide an algorithm that handles the corresponding nonconvex problems and illustrate the use of our formalism by applying it to deconvolution, magnetic resonance imaging, and X-ray tomographic reconstruction problems. Finally, we compare the performance of estimators associated with models of increasing sparsity.
Burton, Brett M; Tate, Jess D; Erem, Burak; Swenson, Darrell J; Wang, Dafang F; Steffen, Michael; Brooks, Dana H; van Dam, Peter M; Macleod, Rob S
2012-01-01
Computational modeling in electrocardiography often requires the examination of cardiac forward and inverse problems in order to non-invasively analyze physiological events that are otherwise inaccessible or unethical to explore. The study of these models can be performed in the open-source SCIRun problem solving environment developed at the Center for Integrative Biomedical Computing (CIBC). A new toolkit within SCIRun provides researchers with essential frameworks for constructing and manipulating electrocardiographic forward and inverse models in a highly efficient and interactive way. The toolkit contains sample networks, tutorials and documentation which direct users through SCIRun-specific approaches in the assembly and execution of these specific problems. PMID:22254301
The weighted Fermat-Torricelli problem on a surface and an "inverse" problem
National Research Council Canada - National Science Library
Zachos, Anastasios; Cotsiolis, Athanase
2011-01-01
We study the weighted Fermat-Torricelli (w.F-T) problem for geodesic triangles on a C.sup.2 complete surface and on an Aleksandrov space of curvature bounded above by a real number K and solve an "inverse" problem...
The Adjoint Method for the Inverse Problem of Option Pricing
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Shou-Lei Wang
2014-01-01
Full Text Available The estimation of implied volatility is a typical PDE inverse problem. In this paper, we propose the TV-L1 model for identifying the implied volatility. The optimal volatility function is found by minimizing the cost functional measuring the discrepancy. The gradient is computed via the adjoint method which provides us with an exact value of the gradient needed for the minimization procedure. We use the limited memory quasi-Newton algorithm (L-BFGS to find the optimal and numerical examples shows the effectiveness of the presented method.
A direct sampling method to an inverse medium scattering problem
Ito, Kazufumi
2012-01-10
In this work we present a novel sampling method for time harmonic inverse medium scattering problems. It provides a simple tool to directly estimate the shape of the unknown scatterers (inhomogeneous media), and it is applicable even when the measured data are only available for one or two incident directions. A mathematical derivation is provided for its validation. Two- and three-dimensional numerical simulations are presented, which show that the method is accurate even with a few sets of scattered field data, computationally efficient, and very robust with respect to noises in the data. © 2012 IOP Publishing Ltd.
Introduction to the 30th volume of Inverse Problems
Louis, Alfred K.
2014-01-01
The field of inverse problems is a fast-developing domain of research originating from the practical demands of finding the cause when a result is observed. The woodpecker, searching for insects, is probing a tree using sound waves: the information searched for is whether there is an insect or not, hence a 0-1 decision. When the result has to contain more information, ad hoc solutions are not at hand and more sophisticated methods have to be developed. Right from its first appearance, the field of inverse problems has been characterized by an interdisciplinary nature: the interpretation of measured data, reinforced by mathematical models serving the analyzing questions of observability, stability and resolution, developing efficient, stable and accurate algorithms to gain as much information as possible from the input and to feedback to the questions of optimal measurement configuration. As is typical for a new area of research, facets of it are separated and studied independently. Hence, fields such as the theory of inverse scattering, tomography in general and regularization methods have developed. However, all aspects have to be reassembled to arrive at the best possible solution to the problem at hand. This development is reflected by the first and still leading journal in the field, Inverse Problems. Founded by pioneers Roy Pike from London and Pierre Sabatier from Montpellier, who enjoyably describes the journal's nascence in his book Rêves et Combats d'un Enseignant-Chercheur, Retour Inverse [1], the journal has developed successfully over the last few decades. Neither the Editors-in-Chief, formerly called Honorary Editors, nor the board or authors could have set the path to success alone. Their fruitful interplay, complemented by the efficient and highly competent publishing team at IOP Publishing, has been fundamental. As such it is my honor and pleasure to follow my renowned colleagues Pierre Sabatier, Mario Bertero, Frank Natterer, Alberto Grünbaum and
A New Inexact Inverse Subspace Iteration for Generalized Eigenvalue Problems
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Fatemeh Mohammad
2014-05-01
Full Text Available In this paper, we represent an inexact inverse subspace iteration method for computing a few eigenpairs of the generalized eigenvalue problem $Ax = \\lambda Bx$[Q.~Ye and P.~Zhang, Inexact inverse subspace iteration for generalized eigenvalue problems, Linear Algebra and its Application, 434 (2011 1697-1715]. In particular, the linear convergence property of the inverse subspace iteration is preserved.
Stability analysis of the inverse transmembrane potential problem in electrocardiography
Burger, Martin; Mardal, Kent-André; Nielsen, Bjørn Fredrik
2010-10-01
In this paper we study some mathematical properties of an inverse problem arising in connection with electrocardiograms (ECGs). More specifically, we analyze the possibility for recovering the transmembrane potential in the heart from ECG recordings, a challenge currently investigated by a growing number of groups. Our approach is based on the bidomain model for the electrical activity in the myocardium, and leads to a parameter identification problem for elliptic partial differential equations (PDEs). It turns out that this challenge can be split into two subproblems: the task of recovering the potential at the heart surface from body surface recordings; the problem of computing the transmembrane potential inside the heart from the potential determined at the heart surface. Problem (1), which can be formulated as the Cauchy problem for an elliptic PDE, has been extensively studied and is well known to be severely ill-posed. The main purpose of this paper is to prove that problem (2) is stable and well posed if a suitable prior is available. Moreover, our theoretical findings are illuminated by a series of numerical experiments. Finally, we discuss some aspects of uniqueness related to the anisotropy in the heart.
Review on solving the inverse problem in EEG source analysis
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Fabri Simon G
2008-11-01
Full Text Available Abstract In this primer, we give a review of the inverse problem for EEG source localization. This is intended for the researchers new in the field to get insight in the state-of-the-art techniques used to find approximate solutions of the brain sources giving rise to a scalp potential recording. Furthermore, a review of the performance results of the different techniques is provided to compare these different inverse solutions. The authors also include the results of a Monte-Carlo analysis which they performed to compare four non parametric algorithms and hence contribute to what is presently recorded in the literature. An extensive list of references to the work of other researchers is also provided. This paper starts off with a mathematical description of the inverse problem and proceeds to discuss the two main categories of methods which were developed to solve the EEG inverse problem, mainly the non parametric and parametric methods. The main difference between the two is to whether a fixed number of dipoles is assumed a priori or not. Various techniques falling within these categories are described including minimum norm estimates and their generalizations, LORETA, sLORETA, VARETA, S-MAP, ST-MAP, Backus-Gilbert, LAURA, Shrinking LORETA FOCUSS (SLF, SSLOFO and ALF for non parametric methods and beamforming techniques, BESA, subspace techniques such as MUSIC and methods derived from it, FINES, simulated annealing and computational intelligence algorithms for parametric methods. From a review of the performance of these techniques as documented in the literature, one could conclude that in most cases the LORETA solution gives satisfactory results. In situations involving clusters of dipoles, higher resolution algorithms such as MUSIC or FINES are however preferred. Imposing reliable biophysical and psychological constraints, as done by LAURA has given superior results. The Monte-Carlo analysis performed, comparing WMN, LORETA, sLORETA and SLF
Review on solving the inverse problem in EEG source analysis.
Grech, Roberta; Cassar, Tracey; Muscat, Joseph; Camilleri, Kenneth P; Fabri, Simon G; Zervakis, Michalis; Xanthopoulos, Petros; Sakkalis, Vangelis; Vanrumste, Bart
2008-11-07
In this primer, we give a review of the inverse problem for EEG source localization. This is intended for the researchers new in the field to get insight in the state-of-the-art techniques used to find approximate solutions of the brain sources giving rise to a scalp potential recording. Furthermore, a review of the performance results of the different techniques is provided to compare these different inverse solutions. The authors also include the results of a Monte-Carlo analysis which they performed to compare four non parametric algorithms and hence contribute to what is presently recorded in the literature. An extensive list of references to the work of other researchers is also provided. This paper starts off with a mathematical description of the inverse problem and proceeds to discuss the two main categories of methods which were developed to solve the EEG inverse problem, mainly the non parametric and parametric methods. The main difference between the two is to whether a fixed number of dipoles is assumed a priori or not. Various techniques falling within these categories are described including minimum norm estimates and their generalizations, LORETA, sLORETA, VARETA, S-MAP, ST-MAP, Backus-Gilbert, LAURA, Shrinking LORETA FOCUSS (SLF), SSLOFO and ALF for non parametric methods and beamforming techniques, BESA, subspace techniques such as MUSIC and methods derived from it, FINES, simulated annealing and computational intelligence algorithms for parametric methods. From a review of the performance of these techniques as documented in the literature, one could conclude that in most cases the LORETA solution gives satisfactory results. In situations involving clusters of dipoles, higher resolution algorithms such as MUSIC or FINES are however preferred. Imposing reliable biophysical and psychological constraints, as done by LAURA has given superior results. The Monte-Carlo analysis performed, comparing WMN, LORETA, sLORETA and SLF, for different noise levels
Inverse Sturm-Liouville problem with discontinuity conditions
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Mohammad Shahriari
2014-02-01
Full Text Available This paper deals with the boundary value problem involving the dierential equation ly := -y''+qy = λy, subject to the standard boundary conditions along with the following discontinuity conditions at a point a ε(0,π y(a + 0 = a1y(a - 0, y'(a + 0 = a1-1y'(a - 0 + a2y(a - 0, where q(x, a1,a2 are real, q ε L2(0,π and λ is a parameter independent of x. We develop the Hochestadt's result based on the transformation operator for inverse Sturm-Liouville problem when there are discontinuous conditions. Furthermore, we establish a formula for q(x - q~(x in the nite interval where q(x and q~(x are analogous functions.
Waterjet and laser etching: the nonlinear inverse problem
Bilbao-Guillerna, A.; Axinte, D. A.; Billingham, J.; Cadot, G. B. J.
2017-07-01
In waterjet and laser milling, material is removed from a solid surface in a succession of layers to create a new shape, in a depth-controlled manner. The inverse problem consists of defining the control parameters, in particular, the two-dimensional beam path, to arrive at a prescribed freeform surface. Waterjet milling (WJM) and pulsed laser ablation (PLA) are studied in this paper, since a generic nonlinear material removal model is appropriate for both of these processes. The inverse problem is usually solved for this kind of process by simply controlling dwell time in proportion to the required depth of milling at a sequence of pixels on the surface. However, this approach is only valid when shallow surfaces are etched, since it does not take into account either the footprint of the beam or its overlapping on successive passes. A discrete adjoint algorithm is proposed in this paper to improve the solution. Nonlinear effects and non-straight passes are included in the optimization, while the calculation of the Jacobian matrix does not require large computation times. Several tests are performed to validate the proposed method and the results show that tracking error is reduced typically by a factor of two in comparison to the pixel-by-pixel approach and the classical raster path strategy with straight passes. The tracking error can be as low as 2-5% and 1-2% for WJM and PLA, respectively, depending on the complexity of the target surface.
A mathematical framework for inverse wave problems in heterogeneous media
Blazek, Kirk D.; Stolk, Christiaan; Symes, William W.
2013-06-01
This paper provides a theoretical foundation for some common formulations of inverse problems in wave propagation, based on hyperbolic systems of linear integro-differential equations with bounded and measurable coefficients. The coefficients of these time-dependent partial differential equations represent parametrically the spatially varying mechanical properties of materials. Rocks, manufactured materials, and other wave propagation environments often exhibit spatial heterogeneity in mechanical properties at a wide variety of scales, and coefficient functions representing these properties must mimic this heterogeneity. We show how to choose domains (classes of nonsmooth coefficient functions) and data definitions (traces of weak solutions) so that optimization formulations of inverse wave problems satisfy some of the prerequisites for application of Newton’s method and its relatives. These results follow from the properties of a class of abstract first-order evolution systems, of which various physical wave systems appear as concrete instances. Finite speed of propagation for linear waves with bounded, measurable mechanical parameter fields is one of the by-products of this theory.
Alloy design as an inverse problem of cluster expansion models
DEFF Research Database (Denmark)
Larsen, Peter Mahler; Kalidindi, Arvind R.; Schmidt, Søren
2017-01-01
Central to a lattice model of an alloy system is the description of the energy of a given atomic configuration, which can be conveniently developed through a cluster expansion. Given a specific cluster expansion, the ground state of the lattice model at 0 K can be solved by finding the configurat......Central to a lattice model of an alloy system is the description of the energy of a given atomic configuration, which can be conveniently developed through a cluster expansion. Given a specific cluster expansion, the ground state of the lattice model at 0 K can be solved by finding...... the configuration of solutes that minimizes the energy of the system. In this paper, we develop a method for solving the inverse lattice problem, where, given a broad class of potential, we find the ground states for all possible values of the effective cluster interaction energies. To do so, we formulate...... the inverse problem in terms of energetically distinct configurations, using a constraint satisfaction model to identify constructible configurations, and show that a convex hull can be used to identify ground states. To demonstrate the approach, we solve for all ground states for a binary alloy in a 2D...
Inverse optical imaging viewed as a backward channel communication problem
De Micheli, Enrico
2013-01-01
The inverse problem in optics, which is closely related to the classical question of the resolving power, is reconsidered as a communication channel problem. The main result is the evaluation of the maximum number $M_\\epsilon$ of $\\epsilon$-distinguishable messages ($\\epsilon$ being a bound on the noise of the image) which can be conveyed back from the image to reconstruct the object. We study the case of coherent illumination. By using the concept of Kolmogorov's $\\epsilon$-capacity, we obtain: $M_\\epsilon ~ 2^{S \\log(1/\\epsilon)} \\to \\infty$ as $\\epsilon \\to 0$, where S is the Shannon number. Moreover, we show that the $\\epsilon$-capacity in inverse optical imaging is nearly equal to the amount of information on the object which is contained in the image. We thus compare the results obtained through the classical information theory, which is based on the probability theory, with those derived from a form of topological information theory, based on Kolmogorov's $\\epsilon$-entropy and $\\epsilon$-capacity, whi...
Koepke, C.; Irving, J.; Roubinet, D.
2014-12-01
Geophysical methods have gained much interest in hydrology over the past two decades because of their ability to provide estimates of the spatial distribution of subsurface properties at a scale that is often relevant to key hydrological processes. Because of an increased desire to quantify uncertainty in hydrological predictions, many hydrogeophysical inverse problems have recently been posed within a Bayesian framework, such that estimates of hydrological properties and their corresponding uncertainties can be obtained. With the Bayesian approach, it is often necessary to make significant approximations to the associated hydrological and geophysical forward models such that stochastic sampling from the posterior distribution, for example using Markov-chain-Monte-Carlo (MCMC) methods, is computationally feasible. These approximations lead to model structural errors, which, so far, have not been properly treated in hydrogeophysical inverse problems. Here, we study the inverse problem of estimating unsaturated hydraulic properties, namely the van Genuchten-Mualem (VGM) parameters, in a layered subsurface from time-lapse, zero-offset-profile (ZOP) ground penetrating radar (GPR) data, collected over the course of an infiltration experiment. In particular, we investigate the effects of assumptions made for computational tractability of the stochastic inversion on model prediction errors as a function of depth and time. These assumptions are that (i) infiltration is purely vertical and can be modeled by the 1D Richards equation, and (ii) the petrophysical relationship between water content and relative dielectric permittivity is known. Results indicate that model errors for this problem are far from Gaussian and independently identically distributed, which has been the common assumption in previous efforts in this domain. In order to develop a more appropriate likelihood formulation, we use (i) a stochastic description of the model error that is obtained through
Comparison of optimal design methods in inverse problems
Banks, H. T.; Holm, K.; Kappel, F.
2011-07-01
Typical optimal design methods for inverse or parameter estimation problems are designed to choose optimal sampling distributions through minimization of a specific cost function related to the resulting error in parameter estimates. It is hoped that the inverse problem will produce parameter estimates with increased accuracy using data collected according to the optimal sampling distribution. Here we formulate the classical optimal design problem in the context of general optimization problems over distributions of sampling times. We present a new Prohorov metric-based theoretical framework that permits one to treat succinctly and rigorously any optimal design criteria based on the Fisher information matrix. A fundamental approximation theory is also included in this framework. A new optimal design, SE-optimal design (standard error optimal design), is then introduced in the context of this framework. We compare this new design criterion with the more traditional D-optimal and E-optimal designs. The optimal sampling distributions from each design are used to compute and compare standard errors; the standard errors for parameters are computed using asymptotic theory or bootstrapping and the optimal mesh. We use three examples to illustrate ideas: the Verhulst-Pearl logistic population model (Banks H T and Tran H T 2009 Mathematical and Experimental Modeling of Physical and Biological Processes (Boca Raton, FL: Chapman and Hall/CRC)), the standard harmonic oscillator model (Banks H T and Tran H T 2009) and a popular glucose regulation model (Bergman R N, Ider Y Z, Bowden C R and Cobelli C 1979 Am. J. Physiol. 236 E667-77 De Gaetano A and Arino O 2000 J. Math. Biol. 40 136-68 Toffolo G, Bergman R N, Finegood D T, Bowden C R and Cobelli C 1980 Diabetes 29 979-90).
Basis set expansion for inverse problems in plasma diagnostic analysis
Energy Technology Data Exchange (ETDEWEB)
Jones, B.; Ruiz, C. L. [Sandia National Laboratories, PO Box 5800, Albuquerque, New Mexico 87185 (United States)
2013-07-15
A basis set expansion method [V. Dribinski, A. Ossadtchi, V. A. Mandelshtam, and H. Reisler, Rev. Sci. Instrum. 73, 2634 (2002)] is applied to recover physical information about plasma radiation sources from instrument data, which has been forward transformed due to the nature of the measurement technique. This method provides a general approach for inverse problems, and we discuss two specific examples relevant to diagnosing fast z pinches on the 20–25 MA Z machine [M. E. Savage, L. F. Bennett, D. E. Bliss, W. T. Clark, R. S. Coats, J. M. Elizondo, K. R. LeChien, H. C. Harjes, J. M. Lehr, J. E. Maenchen, D. H. McDaniel, M. F. Pasik, T. D. Pointon, A. C. Owen, D. B. Seidel, D. L. Smith, B. S. Stoltzfus, K. W. Struve, W. A. Stygar, L. K. Warne, J. R. Woodworth, C. W. Mendel, K. R. Prestwich, R. W. Shoup, D. L. Johnson, J. P. Corley, K. C. Hodge, T. C. Wagoner, and P. E. Wakeland, in Proceedings of the Pulsed Power Plasma Sciences Conference (IEEE, 2007), p. 979]. First, Abel inversion of time-gated, self-emission x-ray images from a wire array implosion is studied. Second, we present an approach for unfolding neutron time-of-flight measurements from a deuterium gas puff z pinch to recover information about emission time history and energy distribution. Through these examples, we discuss how noise in the measured data limits the practical resolution of the inversion, and how the method handles discontinuities in the source function and artifacts in the projected image. We add to the method a propagation of errors calculation for estimating uncertainties in the inverted solution.
Detecting multi-spin interactions in the inverse Ising problem
Albert, Joseph; Swendsen, Robert H.
2017-10-01
While the usual goal in Monte Carlo (MC) simulations of Ising models is the efficient generation of spin configurations with Boltzmann probabilities, the inverse problem is to determine the coupling constants from a given set of spin configurations. Most recent work has been limited to local magnetic fields and pair-wise interactions. We have extended solutions to multi-spin interactions, using correlation function matching (CFM). A more serious limitation of previous work has been the uncertainty of whether a chosen set of interactions is capable of faithfully representing real data. We show how our confirmation testing method uses an additional MC simulation to detect significant interactions that might be missing in the assumed representation of the data.
The inverse problem of estimating the gravitational time dilation
Gusev, A. V.; Litvinov, D. A.; Rudenko, V. N.
2016-11-01
Precise testing of the gravitational time dilation effect suggests comparing the clocks at points with different gravitational potentials. Such a configuration arises when radio frequency standards are installed at orbital and ground stations. The ground-based standard is accessible directly, while the spaceborne one is accessible only via the electromagnetic signal exchange. Reconstructing the current frequency of the spaceborne standard is an ill-posed inverse problem whose solution depends significantly on the characteristics of the stochastic electromagnetic background. The solution for Gaussian noise is known, but the nature of the standards themselves is associated with nonstationary fluctuations of a wide class of distributions. A solution is proposed for a background of flicker fluctuations with a spectrum (1/ f)γ, where 1 < γ < 3, and stationary increments. The results include formulas for the error in reconstructing the frequency of the spaceborne standard and numerical estimates for the accuracy of measuring the relativistic redshift effect.
The inverse problem of estimating the gravitational time dilation
Energy Technology Data Exchange (ETDEWEB)
Gusev, A. V., E-mail: avg@sai.msu.ru; Litvinov, D. A.; Rudenko, V. N. [Moscow State University, Sternberg Astronomical Institute (Russian Federation)
2016-11-15
Precise testing of the gravitational time dilation effect suggests comparing the clocks at points with different gravitational potentials. Such a configuration arises when radio frequency standards are installed at orbital and ground stations. The ground-based standard is accessible directly, while the spaceborne one is accessible only via the electromagnetic signal exchange. Reconstructing the current frequency of the spaceborne standard is an ill-posed inverse problem whose solution depends significantly on the characteristics of the stochastic electromagnetic background. The solution for Gaussian noise is known, but the nature of the standards themselves is associated with nonstationary fluctuations of a wide class of distributions. A solution is proposed for a background of flicker fluctuations with a spectrum (1/f){sup γ}, where 1 < γ < 3, and stationary increments. The results include formulas for the error in reconstructing the frequency of the spaceborne standard and numerical estimates for the accuracy of measuring the relativistic redshift effect.
Geomagnetic inverse problem and data assimilation: a progress report
Aubert, Julien; Fournier, Alexandre
2013-04-01
In this presentation I will present two studies recently undertaken by our group in an effort to bring the benefits of data assimilation to the study of Earth's magnetic field and the dynamics of its liquid iron core, where the geodynamo operates. In a first part I will focus on the geomagnetic inverse problem, which attempts to recover the fluid flow in the core from the temporal variation of the magnetic field (known as the secular variation). Geomagnetic data can be downward continued from the surface of the Earth down to the core-mantle boundary, but not further below, since the core is an electrical conductor. Historically, solutions to the geomagnetic inverse problem in such a sparsely observed system were thus found only for flow immediately below the core mantle boundary. We have recently shown that combining a numerical model of the geodynamo together with magnetic observations, through the use of Kalman filtering, now allows to present solutions for flow throughout the core. In a second part, I will present synthetic tests of sequential geomagnetic data assimilation aiming at evaluating the range at which the future of the geodynamo can be predicted, and our corresponding prospects to refine the current geomagnetic predictions. Fournier, Aubert, Thébault: Inference on core surface flow from observations and 3-D dynamo modelling, Geophys. J. Int. 186, 118-136, 2011, doi: 10.1111/j.1365-246X.2011.05037.x Aubert, Fournier: Inferring internal properties of Earth's core dynamics and their evolution from surface observations and a numerical geodynamo model, Nonlinear Proc. Geoph. 18, 657-674, 2011, doi:10.5194/npg-18-657-2011 Aubert: Flow throughout the Earth's core inverted from geomagnetic observations and numerical dynamo models, Geophys. J. Int., 2012, doi: 10.1093/gji/ggs051
Geometric MCMC for infinite-dimensional inverse problems
Beskos, Alexandros; Girolami, Mark; Lan, Shiwei; Farrell, Patrick E.; Stuart, Andrew M.
2017-04-01
Bayesian inverse problems often involve sampling posterior distributions on infinite-dimensional function spaces. Traditional Markov chain Monte Carlo (MCMC) algorithms are characterized by deteriorating mixing times upon mesh-refinement, when the finite-dimensional approximations become more accurate. Such methods are typically forced to reduce step-sizes as the discretization gets finer, and thus are expensive as a function of dimension. Recently, a new class of MCMC methods with mesh-independent convergence times has emerged. However, few of them take into account the geometry of the posterior informed by the data. At the same time, recently developed geometric MCMC algorithms have been found to be powerful in exploring complicated distributions that deviate significantly from elliptic Gaussian laws, but are in general computationally intractable for models defined in infinite dimensions. In this work, we combine geometric methods on a finite-dimensional subspace with mesh-independent infinite-dimensional approaches. Our objective is to speed up MCMC mixing times, without significantly increasing the computational cost per step (for instance, in comparison with the vanilla preconditioned Crank-Nicolson (pCN) method). This is achieved by using ideas from geometric MCMC to probe the complex structure of an intrinsic finite-dimensional subspace where most data information concentrates, while retaining robust mixing times as the dimension grows by using pCN-like methods in the complementary subspace. The resulting algorithms are demonstrated in the context of three challenging inverse problems arising in subsurface flow, heat conduction and incompressible flow control. The algorithms exhibit up to two orders of magnitude improvement in sampling efficiency when compared with the pCN method.
AMP-Inspired Deep Networks for Sparse Linear Inverse Problems
Borgerding, Mark; Schniter, Philip; Rangan, Sundeep
2017-08-01
Deep learning has gained great popularity due to its widespread success on many inference problems. We consider the application of deep learning to the sparse linear inverse problem, where one seeks to recover a sparse signal from a few noisy linear measurements. In this paper, we propose two novel neural-network architectures that decouple prediction errors across layers in the same way that the approximate message passing (AMP) algorithms decouple them across iterations: through Onsager correction. First, we propose a "learned AMP" network that significantly improves upon Gregor and LeCun's "learned ISTA." Second, inspired by the recently proposed "vector AMP" (VAMP) algorithm, we propose a "learned VAMP" network that offers increased robustness to deviations in the measurement matrix from i.i.d. Gaussian. In both cases, we jointly learn the linear transforms and scalar nonlinearities of the network. Interestingly, with i.i.d. signals, the linear transforms and scalar nonlinearities prescribed by the VAMP algorithm coincide with the values learned through back-propagation, leading to an intuitive interpretation of learned VAMP. Finally, we apply our methods to two problems from 5G wireless communications: compressive random access and massive-MIMO channel estimation.
Goffaux, Valerie; Rossion, Bruno; Sorger, Bettina; Schiltz, Christine; Goebel, Rainer
2009-03-01
The impact of inversion on the extraction of relational and featural face information was investigated in two fMRI experiments. Unlike previous studies, the contribution of horizontal and vertical spatial relations were considered separately since they have been shown to be differentially vulnerable to face inversion (Goffaux & Rossion, 2007). Hence, inversion largely affects the perception of vertical relations (e.g. eye or mouth height) while the processing of features (e.g. eye shape and surface) and of horizontal relations (e.g. inter-ocular distance) is affected to a far lesser extent. Participants viewed pairs of faces that differed either at the level of one local feature (i.e. the eyes) or of the spatial relations of this feature with adjacent features. Changes of spatial relations were divided into two conditions, depending on the vertical or horizontal axis of the modifications. These stimulus conditions were presented in separate blocks in the first (block) experiment while they were presented in a random order in the second event-related (ER) experiment. Face-preferring voxels located in the right-lateralized middle fusiform gyrus (rMFG) largely decreased their activity with inversion. Inversion-related decreases were more moderate in left-lateralized middle fusiform gyrus (lMFG). ER experiment revealed that inversion affected rMFG and lMFG activity in distinct stimulus conditions. Whereas inversion affected lMFG processing only in featural condition, inversion selectively affected the processing of vertical relations in rMFG. Correlation analyses further indicated that the inversion effect (IE) observed in rMFG and right inferior occipital gyrus (rIOG) reliably predicted the large behavioural IE observed for the processing of vertical relations. In contrast, lMFG IE correlated with the weak behavioural IE observed for the processing of horizontal relations. Our findings suggest that face configuration is mostly encoded in rMFG, whereas more local
Direct and inverse source problems for a space fractional advection dispersion equation
Aldoghaither, Abeer
2016-05-15
In this paper, direct and inverse problems for a space fractional advection dispersion equation on a finite domain are studied. The inverse problem consists in determining the source term from final observations. We first derive the analytic solution to the direct problem which we use to prove the uniqueness and the unstability of the inverse source problem using final measurements. Finally, we illustrate the results with a numerical example.
Inverse Ising problem in continuous time: A latent variable approach
Donner, Christian; Opper, Manfred
2017-12-01
We consider the inverse Ising problem: the inference of network couplings from observed spin trajectories for a model with continuous time Glauber dynamics. By introducing two sets of auxiliary latent random variables we render the likelihood into a form which allows for simple iterative inference algorithms with analytical updates. The variables are (1) Poisson variables to linearize an exponential term which is typical for point process likelihoods and (2) Pólya-Gamma variables, which make the likelihood quadratic in the coupling parameters. Using the augmented likelihood, we derive an expectation-maximization (EM) algorithm to obtain the maximum likelihood estimate of network parameters. Using a third set of latent variables we extend the EM algorithm to sparse couplings via L1 regularization. Finally, we develop an efficient approximate Bayesian inference algorithm using a variational approach. We demonstrate the performance of our algorithms on data simulated from an Ising model. For data which are simulated from a more biologically plausible network with spiking neurons, we show that the Ising model captures well the low order statistics of the data and how the Ising couplings are related to the underlying synaptic structure of the simulated network.
Solving Inverse Detection Problems Using Passive Radiation Signatures
Energy Technology Data Exchange (ETDEWEB)
Favorite, Jeffrey A. [Los Alamos National Laboratory; Armstrong, Jerawan C. [Los Alamos National Laboratory; Vaquer, Pablo A. [Los Alamos National Laboratory
2012-08-15
The ability to reconstruct an unknown radioactive object based on its passive gamma-ray and neutron signatures is very important in homeland security applications. Often in the analysis of unknown radioactive objects, for simplicity or speed or because there is no other information, they are modeled as spherically symmetric regardless of their actual geometry. In these presentation we discuss the accuracy and implications of this approximation for decay gamma rays and for neutron-induced gamma rays. We discuss an extension of spherical raytracing (for uncollided fluxes) that allows it to be used when the exterior shielding is flat or cylindrical. We revisit some early results in boundary perturbation theory, showing that the Roussopolos estimate is the correct one to use when the quantity of interest is the flux or leakage on the boundary. We apply boundary perturbation theory to problems in which spherically symmetric systems are perturbed in asymmetric nonspherical ways. We apply mesh adaptive direct search (MADS) algorithms to object reconstructions. We present a benchmark test set that may be used to quantitatively evaluate inverse detection methods.
Beamforming through regularized inverse problems in ultrasound medical imaging.
Szasz, Teodora; Basarab, Adrian; Kouame, Denis
2016-09-13
Beamforming in ultrasound imaging has significant impact on the quality of the final image, controlling its resolution and contrast. Despite its low spatial resolution and contrast, delay-and-sum is still extensively used nowadays in clinical applications, due to its real-time capabilities. The most common alternatives are minimum variance method and its variants, which overcome the drawbacks of delay-and-sum, at the cost of higher computational complexity that limits its utilization in real-time applications. In this paper, we propose to perform beamforming in ultrasound imaging through a regularized inverse problem based on a linear model relating the reflected echoes to the signal to be recovered. Our approach presents two major advantages: i) its flexibility in the choice of statistical assumptions on the signal to be beamformed (Laplacian and Gaussian statistics are tested herein) and ii) its robustness to a reduced number of pulse emissions. The proposed framework is flexible and allows for choosing the right trade-off between noise suppression and sharpness of the resulted image. We illustrate the performance of our approach on both simulated and experimental data, with in vivo examples of carotid and thyroid. Compared to delay-and-sum, minimimum variance and two other recently published beamforming techniques, our method offers better spatial resolution, respectively contrast, when using Laplacian and Gaussian priors.
DEFF Research Database (Denmark)
Hansen, Thomas Mejer; Cordua, Knud Skou; Holm Jacobsen, Bo
2014-01-01
Inversion of geophysical data relies on knowledge about how to solve the forward problem, that is, computing data from a given set of model parameters. In many applications of inverse problems, the solution to the forward problem is assumed to be known perfectly, without any error. In reality, so...
2010-06-15
demonstrate that in a number of image inverse problems, including inpainting , zooming, and deblurring, the same algorithm produces either equal, often...inverse problems, including inpainting , zooming, and deblurring, the same algorithm produces either equal, often significantly better, or very small...problems often named inpainting or interpolation, zooming and deblurring. Estimating f requires some prior information on the image, or equivalently image
Benson, R. F.; Truhlik, V.; Huang, X.; Wang, Y.; Bilitza, D.
2011-01-01
The topside-sounders on the four satellites of the International Satellites for Ionospheric Studies (ISIS) program were designed as analog systems. The resulting ionograms were displayed on 35-mm film for analysis by visual inspection. Each of these satellites, launched between 1962 and 1971, produced data for 10 to 20 years. A number of the original telemetry tapes from this large data set have been converted directly into digital records. Software, known as the TOPside Ionogram Scalar with True-height (TOPIST) algorithm has been produced that enables the automatic inversion of ISIS-2 ionogram reflection traces into topside vertical electron-density profiles Ne(h). More than million digital Alouette/ISIS topside ionograms have been produced and over 300,000 are from ISIS 2. Many of these ISIS-2 ionograms correspond to a passive mode of operation for the detection of natural radio emissions and thus do not contain ionospheric reflection traces. TOPIST, however, is not able to produce Ne(h) profiles from all of the ISIS-2 ionograms with reflection traces because some of them did not contain frequency information. This information was missing due to difficulties encountered during the analog-to-digital conversion process in the detection of the ionogram frame-sync pulse and/or the frequency markers. Of the many digital topside ionograms that TOPIST was able to process, over 200 were found where direct comparisons could be made with Ne(h) profiles that were produced by manual scaling in the early days of the ISIS program. While many of these comparisons indicated excellent agreement (inversion process: (1) improve the quality of the digital ionogram database by remedying the missing frequency-information problem when possible, and (2) using the above-mentioned comparisons as teaching examples of how to improve the original TOPIST software.
A solution to the inverse problem in ocean acoustics
Digital Repository Service at National Institute of Oceanography (India)
Murty, T.V.R.; Somayajulu, Y.K.; Mahadevan, R.; Murty, C.S.; Sastry, J.S.
The methodology and software developed to reconstruct a vertical sound speed profile as a part of studies on the marine acoustic modelling, using the ray path lengths and the travel time perturbations in tomographic layers are outlined. For a...
Solving inverse problems of mathematical physics by means of the PHOENICS software package
Energy Technology Data Exchange (ETDEWEB)
Matsevity, Y.; Lushpenko, S. [Institute for Problems in Machinery, National Academy of Sciences of Ukraine Pozharskogo, Kharkov (Ukraine)
1997-12-31
Several approaches on organizing solution of inverse problems by means of PHOENICS on the basis of the technique of automated fitting are proposing. A version of a `nondestructive` method of using PHOENICS in the inverse problem solution regime and the ways of altering the program in the case of introducing optimization facilities in it are under consideration. (author) 12 refs.
Brown, Malcolm
2009-01-01
Inversions are fascinating phenomena. They are reversals of the normal or expected order. They occur across a wide variety of contexts. What do inversions have to do with learning spaces? The author suggests that they are a useful metaphor for the process that is unfolding in higher education with respect to education. On the basis of…
Model error estimation and correction by solving a inverse problem
Xue, Haile
2016-04-01
Nowadays, the weather forecasts and climate predictions are increasingly relied on numerical models. Yet, errors inevitably exist in model due to the imperfect numeric and parameterizations. From the practical point of view, model correction is an efficient strategy. Despite of the different complexity of forecast error correction algorithms, the general idea is to estimate the forecast errors by considering the NWP as a direct problem. Chou (1974) suggested an alternative view by considering the NWP as an inverse problem. The model error tendency term (ME) due to the model deficiency is assumed as an unknown term in NWP model, which can be discretized into short intervals (for example 6 hour) and considered as a constant or linear form in each interval. Given the past re-analyses and NWP model, the discretized MEs in the past intervals can be solved iteratively as a constant or linear-increased tendency term in each interval. These MEs can be further used as the online corrections. In this study, an iterative method for obtaining the MEs in past intervals was presented, and its convergence had been confirmed with sets of experiments in the global forecast system of the Global and Regional Assimilation and Prediction System (GRAPES-GFS) for July-August (JA) 2009 and January-February (JF) 2010. Then these MEs were used to get online model corretions based of systematic errors of GRAPES-GFS for July 2009 and January 2010. The data sets associated with initial condition and sea surface temperature (SST) used in this study are both based on NCEP final (FNL) data. According to the iterative numerical experiments, the following key conclusions can be drawn:(1) Batches of iteration test results indicated that the hour 6 forecast errors were reduced to 10% of their original value after 20 steps of iteration.(2) By offlinely comparing the error corrections estimated by MEs to the mean forecast errors, the patterns of estimated errors were considered to agree well with those
Energy Technology Data Exchange (ETDEWEB)
Huang, C.-H.; Wu, H.-H. [Department of Systems and Naval Mechatronic Engineering National Cheng Kung University Tainan, Taiwan 701 (China)
2006-09-21
In the present study an inverse hyperbolic heat conduction problem is solved by the conjugate gradient method (CGM) in estimating the unknown boundary heat flux based on the boundary temperature measurements. Results obtained in this inverse problem will be justified based on the numerical experiments where three different heat flux distributions are to be determined. Results show that the inverse solutions can always be obtained with any arbitrary initial guesses of the boundary heat flux. Moreover, the drawbacks of the previous study for this similar inverse problem, such as (1) the inverse solution has phase error and (2) the inverse solution is sensitive to measurement error, can be avoided in the present algorithm. Finally, it is concluded that accurate boundary heat flux can be estimated in this study.
IPDO-2007: Inverse Problems, Design and Optimization Symposium
2007-08-01
science, materials processing, algorithm developments, solid mechanics, fluid mechanics, electromagnetism, aerospace, structural dynamics, heat transfer...NUMBERS, TITLES AND PAGES IN THE PROCEEDINGS PAPER TITLE PAGE 003 INVERSE ANALISYS APPLIED FOR DETERMINATION OF STRAIN – STRESS CURVES FOR STEEL...VISCOUS FLOW FIELDS 122 035 A NOVEL ADAPTIVE LASER SCANNING SENSOR FOR REVERSE ENGINEERING 129 039 A NOVEL STRUCTURED LIGHT VISUAL SENSOR WITH ADAPTIVE
Energy Technology Data Exchange (ETDEWEB)
Aguilo Valentin, Miguel Alejandro [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2016-07-01
This study presents a new nonlinear programming formulation for the solution of inverse problems. First, a general inverse problem formulation based on the compliance error functional is presented. The proposed error functional enables the computation of the Lagrange multipliers, and thus the first order derivative information, at the expense of just one model evaluation. Therefore, the calculation of the Lagrange multipliers does not require the solution of the computationally intensive adjoint problem. This leads to significant speedups for large-scale, gradient-based inverse problems.
An inverse natural convection problem of estimating the strength of a heat source
Energy Technology Data Exchange (ETDEWEB)
Park, H.M.; Chung, O.Y. [Sogang University, Seoul (D.P.R. of Korea). Dpt. of Chemical Engineering
1999-12-01
The inverse problem of determining the time-varying strength of a heat source, which causes natural convection in a two-dimensional cavity, is considered. The Boussinesq equation is used to model the natural convection induced by the heat source. The inverse natural convection problem is posed as a minimization problem of the least-square criterion, which is solved by a conjugate gradient method employing the adjoint equation to determine the descent direction. The present method solves the inverse natural convection problem accurately without any simplification of the governing Boussinesq equation. (author)
Higher order Nevanlinna functions and the inverse three spectra problem
Directory of Open Access Journals (Sweden)
Olga Boyko
2016-01-01
Full Text Available The three spectra problem of recovering the Sturm-Liouville equation by the spectrum of the Dirichlet-Dirichlet boundary value problem on \\([0,a]\\, the Dirichlet-Dirichlet problem on \\([0,a/2]\\ and the Neumann-Dirichlet problem on \\([a/2,a]\\ is considered. Sufficient conditions of solvability and of uniqueness of the solution to such a problem are found.
Energy Technology Data Exchange (ETDEWEB)
Khan, T.; Ramuhalli, Pradeep; Dass, Sarat
2011-06-30
Flaw profile characterization from NDE measurements is a typical inverse problem. A novel transformation of this inverse problem into a tracking problem, and subsequent application of a sequential Monte Carlo method called particle filtering, has been proposed by the authors in an earlier publication [1]. In this study, the problem of flaw characterization from multi-sensor data is considered. The NDE inverse problem is posed as a statistical inverse problem and particle filtering is modified to handle data from multiple measurement modes. The measurement modes are assumed to be independent of each other with principal component analysis (PCA) used to legitimize the assumption of independence. The proposed particle filter based data fusion algorithm is applied to experimental NDE data to investigate its feasibility.
Zhang, Zhendong
2017-07-11
Full waveform inversion for reection events is limited by its linearized update re-quirements given by a process equivalent to migration. Unless the background velocity model is reasonably accurate, the resulting gradient can have an inaccurate update direction leading the inversion to converge what we refer to as local minima of the objective function. In our approach, we consider mild lateral variation in the model, and thus, use a gradient given by the oriented time-domain imaging method. Specifically, we apply the oriented time-domain imaging on the data residual to obtain the geometrical features of the velocity perturbation. After updating the model in the time domain, we convert the perturbation from the time domain to depth using the average velocity. Considering density is constant, we can expand the conventional 1D impedance inversion method to 2D or 3D velocity inversion within the process of full waveform inversion. This method is not only capable of inverting for velocity, but it is also capable of retrieving anisotropic parameters relying on linearized representations of the reection response. To eliminate the cross-talk artifacts between different parameters, we utilize what we consider being an optimal parametrization for this step. To do so, we extend the prestack time-domain migration image in incident angle dimension to incorporate angular dependence needed by the multiparameter inversion. For simple models, this approach provides an efficient and stable way to do full waveform inversion or modified seismic inversion and makes the anisotropic inversion more practicable. The proposed method still needs kinematically accurate initial models since it only recovers the high-wavenumber part as conventional full waveform inversion method does. Results on synthetic data of isotropic and anisotropic cases illustrate the benefits and limitations of this method.
Inversion problem for ion-atom differential elastic scattering.
Rich, W. G.; Bobbio, S. M.; Champion, R. L.; Doverspike, L. D.
1971-01-01
The paper describes a practical application of Remler's (1971) method by which one constructs a set of phase shifts from high resolution measurements of the differential elastic scattering of protons by rare-gas atoms. These JWKB phase shifts are then formally inverted to determine the corresponding intermolecular potentials. The validity of the method is demonstrated by comparing an intermolecular potential obtained by direct inversion of experimental data with a fairly accurate calculation by Wolniewicz (1965).
Ashyralyyev, Charyyar; Akyüz, Gulzipa
2016-08-01
In this study, we discuss well-posedness of Bitsadze-Samarskii type inverse elliptic problem with Dirichlet conditions. We establish abstract results on stability and coercive stability estimates for the solution of this inverse problem. Then, the abstract results are applied to three overdetermined problems for the multi-dimensional elliptic equation with different boundary conditions. Stability inequalities for solutions of these applications are obtained.
Propagation of Singularities and Some Inverse Problems in Wave Propagation
National Research Council Canada - National Science Library
Symes, William W
1989-01-01
... in various useful coefficient classes, separation of scales,...We explain the essential role of travel time in the study of these problems, and show how its function may be generalized to multidimensional (i.e. non-layered) problems.
Physics-based Inverse Problem to Deduce Marine Atmospheric Boundary Layer Parameters
2017-03-07
please find the Final Technical Report with SF 298 for Dr. Erin E. Hackett’s ONR grant entitled Physics -based Inverse Problem to Deduce Marine...From- To) 07/03/2017 Final Technica l Dec 2012- Dec 2016 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Physics -based Inverse Problem to Deduce Marine...19b. TELEPHONE NUMBER (Include area code) 843-349-4087 Standard Form 298 (Rev. 8/98) Prescribed by ANSI Std. Z39.18 Physics -Based Inverse Problem To
Solving inverse problems through a smooth formulation of multiple-point geostatistics
DEFF Research Database (Denmark)
Melnikova, Yulia
into inversion procedure. Errors associated with conversion from depth to time are handled with a novel mapping approach.This thesis reviews the latest developments in the field of geoscientific inverse problems with a focus on the history matching problem. The work contains detailed explanation of our...... be inferred, for instance, from a conceptual geological model termed a training image.The main motivation for this study was the challenge posed by history matching, an inverse problem aimed at estimating rock properties from production data. We addressed two main difficulties of the history matching problem......: existence of multiple, most often geologically unfeasible, solutions and high computational cost of the forward simulation. The developed methodology resulted in a new method for solving inverse problems with training-image based a priori information, when the computational time matters.Specifically, we...
Inverse natural convection problem of estimating wall heat flux using a moving sensor
Energy Technology Data Exchange (ETDEWEB)
Park, H.M.; Chung, O.Y.
1999-11-01
Inverse heat transfer problems have many applications in various branch of science and engineering. Here, the inverse problem of determining heat flux at the bottom wall of a two-dimensional cavity from temperature measurement in the domain is considered. The Boussinesq equation is used to model the natural convection induced by the wall heat flux. The inverse natural convection problem is posed as a minimization problem of the performance function, which is the sum of square residuals between calculated and observed temperature, by means of a conjugate gradient method. Instead of employing several fixed sensors, a single sensor is used which is moving at a given frequency over the bottom wall. The present method solves the inverse natural convection problem accurately without a priori information about the unknown function to be estimated.
Energy Technology Data Exchange (ETDEWEB)
Jiang Mingfeng [Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027 (China); Xia Ling [Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027 (China); Shou Guofa [Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027 (China); Tang Min [Department of Arrhythmia, Cardiovascular Institute and Fuwai Hospital, Chinese Academy of Medical Science and Chinese Union Medical College, Beijing 100037 (China)
2007-03-07
Computing epicardial potentials from body surface potentials constitutes one form of ill-posed inverse problem of electrocardiography (ECG). To solve this ECG inverse problem, the Tikhonov regularization and truncated singular-value decomposition (TSVD) methods have been commonly used to overcome the ill-posed property by imposing constraints on the magnitudes or derivatives of the computed epicardial potentials. Such direct regularization methods, however, are impractical when the transfer matrix is large. The least-squares QR (LSQR) method, one of the iterative regularization methods based on Lanczos bidiagonalization and QR factorization, has been shown to be numerically more reliable in various circumstances than the other methods considered. This LSQR method, however, to our knowledge, has not been introduced and investigated for the ECG inverse problem. In this paper, the regularization properties of the Krylov subspace iterative method of LSQR for solving the ECG inverse problem were investigated. Due to the 'semi-convergence' property of the LSQR method, the L-curve method was used to determine the stopping iteration number. The performance of the LSQR method for solving the ECG inverse problem was also evaluated based on a realistic heart-torso model simulation protocol. The results show that the inverse solutions recovered by the LSQR method were more accurate than those recovered by the Tikhonov and TSVD methods. In addition, by combing the LSQR with genetic algorithms (GA), the performance can be improved further. It suggests that their combination may provide a good scheme for solving the ECG inverse problem.
Jiang, Mingfeng; Xia, Ling; Shou, Guofa; Tang, Min
2007-03-01
Computing epicardial potentials from body surface potentials constitutes one form of ill-posed inverse problem of electrocardiography (ECG). To solve this ECG inverse problem, the Tikhonov regularization and truncated singular-value decomposition (TSVD) methods have been commonly used to overcome the ill-posed property by imposing constraints on the magnitudes or derivatives of the computed epicardial potentials. Such direct regularization methods, however, are impractical when the transfer matrix is large. The least-squares QR (LSQR) method, one of the iterative regularization methods based on Lanczos bidiagonalization and QR factorization, has been shown to be numerically more reliable in various circumstances than the other methods considered. This LSQR method, however, to our knowledge, has not been introduced and investigated for the ECG inverse problem. In this paper, the regularization properties of the Krylov subspace iterative method of LSQR for solving the ECG inverse problem were investigated. Due to the 'semi-convergence' property of the LSQR method, the L-curve method was used to determine the stopping iteration number. The performance of the LSQR method for solving the ECG inverse problem was also evaluated based on a realistic heart-torso model simulation protocol. The results show that the inverse solutions recovered by the LSQR method were more accurate than those recovered by the Tikhonov and TSVD methods. In addition, by combing the LSQR with genetic algorithms (GA), the performance can be improved further. It suggests that their combination may provide a good scheme for solving the ECG inverse problem.
An inverse problem for a one-dimensional time-fractional diffusion problem
Jin, Bangti
2012-06-26
We study an inverse problem of recovering a spatially varying potential term in a one-dimensional time-fractional diffusion equation from the flux measurements taken at a single fixed time corresponding to a given set of input sources. The unique identifiability of the potential is shown for two cases, i.e. the flux at one end and the net flux, provided that the set of input sources forms a complete basis in L 2(0, 1). An algorithm of the quasi-Newton type is proposed for the efficient and accurate reconstruction of the coefficient from finite data, and the injectivity of the Jacobian is discussed. Numerical results for both exact and noisy data are presented. © 2012 IOP Publishing Ltd.
Monitoring vertical wheel–rail contact forces based on freight wagon inverse modelling
National Research Council Canada - National Science Library
Sun, Yan Quan; Cole, Colin; Spiryagin, Maksym
2015-01-01
...–rail contact dynamic forces. To evaluate and monitor the wheel–rail dynamic forces based on the accelerations on the wagon components, a two-dimensional inverse wagon model has been developed...
Corrado, Cesare; Gerbeau, Jean-Frédéric; Moireau, Philippe
2015-02-01
This work addresses the inverse problem of electrocardiography from a new perspective, by combining electrical and mechanical measurements. Our strategy relies on the definition of a model of the electromechanical contraction which is registered on ECG data but also on measured mechanical displacements of the heart tissue typically extracted from medical images. In this respect, we establish in this work the convergence of a sequential estimator which combines for such coupled problems various state of the art sequential data assimilation methods in a unified consistent and efficient framework. Indeed, we aggregate a Luenberger observer for the mechanical state and a Reduced-Order Unscented Kalman Filter applied on the parameters to be identified and a POD projection of the electrical state. Then using synthetic data we show the benefits of our approach for the estimation of the electrical state of the ventricles along the heart beat compared with more classical strategies which only consider an electrophysiological model with ECG measurements. Our numerical results actually show that the mechanical measurements improve the identifiability of the electrical problem allowing to reconstruct the electrical state of the coupled system more precisely. Therefore, this work is intended to be a first proof of concept, with theoretical justifications and numerical investigations, of the advantage of using available multi-modal observations for the estimation and identification of an electromechanical model of the heart.
The band method and inverse problems for orthogonal matrix functions of Szego-Krein type
Kaashoek, M.A.; Lerer, L.
2012-01-01
A band method approach for solving inverse problems for certain orthogonal functions is developed. The inverse theorems for Szego-Kreǐn matrix polynomials and for Kreǐn orthogonal entire matrix functions are obtained as corollaries of the band method results. Other examples, including a
The inverse problem of constructing a gravimetric geoid
Zlotnicki, V.; Parsons, B.; Wunsch, C.
1982-01-01
Computation of a single geoidal height from gravity acceleration data formally requires that the latter be known everywhere on the earth. A computational procedure based on linear inverse theory for estimating geoidal heights from incomplete sets of data is presented. The same scheme can be used to estimate gravity accelerations from altimetry-derived geoids. The systematic error owing to lack of data and the choice of a particular inverse operator is described by using resolution functions and their spherical harmonic expansions. An rms value of this error is also estimated by assuming a spectrum for the unknown geoid. The influence of the size of the data region, the spacing between data, the filtering applied to the data, and the model weighting function chosen are all quantified in a spherical geometry. The examples presented show that when low degree spherical harmonic coefficients are available - from satellite orbit analysis - a band-passed version of the geoid can be constructed from local gravity data, even with a relatively restricted data set.
Cheng, Jin; Hon, Yiu-Chung; Seo, Jin Keun; Yamamoto, Masahiro
2005-01-01
The Second International Conference on Inverse Problems: Recent Theoretical Developments and Numerical Approaches was held at Fudan University, Shanghai from 16-21 June 2004. The first conference in this series was held at the City University of Hong Kong in January 2002 and it was agreed to hold the conference once every two years in a Pan-Pacific Asian country. The next conference is scheduled to be held at Hokkaido University, Sapporo, Japan in July 2006. The purpose of this series of biennial conferences is to establish and develop constant international collaboration, especially among the Pan-Pacific Asian countries. In recent decades, interest in inverse problems has been flourishing all over the globe because of both the theoretical interest and practical requirements. In particular, in Asian countries, one is witnessing remarkable new trends of research in inverse problems as well as the participation of many young talents. Considering these trends, the second conference was organized with the chairperson Professor Li Tat-tsien (Fudan University), in order to provide forums for developing research cooperation and to promote activities in the field of inverse problems. Because solutions to inverse problems are needed in various applied fields, we entertained a total of 92 participants at the second conference and arranged various talks which ranged from mathematical analyses to solutions of concrete inverse problems in the real world. This volume contains 18 selected papers, all of which have undergone peer review. The 18 papers are classified as follows: Surveys: four papers give reviews of specific inverse problems. Theoretical aspects: six papers investigate the uniqueness, stability, and reconstruction schemes. Numerical methods: four papers devise new numerical methods and their applications to inverse problems. Solutions to applied inverse problems: four papers discuss concrete inverse problems such as scattering problems and inverse problems in
Active Subspace Methods for Data-Intensive Inverse Problems
Energy Technology Data Exchange (ETDEWEB)
Wang, Qiqi [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
2017-04-27
The project has developed theory and computational tools to exploit active subspaces to reduce the dimension in statistical calibration problems. This dimension reduction enables MCMC methods to calibrate otherwise intractable models. The same theoretical and computational tools can also reduce the measurement dimension for calibration problems that use large stores of data.
Inverse problems with non-trivial priors: efficient solution through sequential Gibbs sampling
DEFF Research Database (Denmark)
Hansen, Thomas Mejer; Cordua, Knud Skou; Mosegaard, Klaus
2012-01-01
Markov chain Monte Carlo methods such as the Gibbs sampler and the Metropolis algorithm can be used to sample solutions to non-linear inverse problems. In principle, these methods allow incorporation of prior information of arbitrary complexity. If an analytical closed form description of the prior....... We propose an algorithm, called sequential Gibbs sampling, allowing the Metropolis algorithm to efficiently incorporate complex priors into the solution of an inverse problem, also for the case where no closed form description of the prior exists. First, we lay out the theoretical background...... for applying the sequential Gibbs sampler and illustrate how it works. Through two case studies, we demonstrate the application of the method to a linear image restoration problem and to a non-linear cross-borehole inversion problem. We demonstrate how prior information can reduce the complexity of an inverse...
The organization of the practical training on the inverse problems for the differential equations
Directory of Open Access Journals (Sweden)
Виктор Семенович Корнилов
2010-06-01
Full Text Available In article it is analyzed forms of the organisation of studies on inverse problems for the differential equations for students of physical and mathematical specialities of high schools.
Denisov, A. M.; Zakharov, E. V.; Kalinin, A. V.; Kalinin, V. V.
2010-07-01
A numerical method is proposed for solving an inverse electrocardiography problem for a medium with a piecewise constant electrical conductivity. The method is based on the method of boundary integral equations and Tikhonov regularization.
Grigoriev, M.; Babich, L.
2015-09-01
The article represents the main noninvasive methods of heart electrical activity examination, theoretical bases of solution of electrocardiography inverse problem, application of different methods of heart examination in clinical practice, and generalized achievements in this sphere in global experience.
Directory of Open Access Journals (Sweden)
Guangzhen Jin
2015-01-01
Full Text Available Based on an isopycnic-coordinate internal tidal model with the adjoint method, the inversion of spatially varying vertical eddy viscosity coefficient (VEVC is studied in two groups of numerical experiments. In Group One, the influences of independent point schemes (IPSs exerting on parameter inversion are discussed. Results demonstrate that the VEVCs can be inverted successfully with IPSs and the model has the best performance with the optimal IPSs. Using the optimal IPSs obtained in Group One, the inversions of VEVCs on two different Gaussian bottom topographies are carried out in Group Two. In addition, performances of two optimization methods of which one is the limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS method and the other is a simplified gradient descent method (GDM-S are also investigated. Results of the experiments indicate that this adjoint model is capable to invert the VEVC with spatially distribution, no matter which optimization method is taken. The L-BFGS method has a better performance in terms of the convergence rate and the inversion results. In general, the L-BFGS method is a more effective and efficient optimization method than the GDM-S.
Moving Least Squares Method for a One-Dimensional Parabolic Inverse Problem
Directory of Open Access Journals (Sweden)
Baiyu Wang
2014-01-01
Full Text Available This paper investigates the numerical solution of a class of one-dimensional inverse parabolic problems using the moving least squares approximation; the inverse problem is the determination of an unknown source term depending on time. The collocation method is used for solving the equation; some numerical experiments are presented and discussed to illustrate the stability and high efficiency of the method.
Solving inverse problems for biological models using the collage method for differential equations.
Capasso, V; Kunze, H E; La Torre, D; Vrscay, E R
2013-07-01
In the first part of this paper we show how inverse problems for differential equations can be solved using the so-called collage method. Inverse problems can be solved by minimizing the collage distance in an appropriate metric space. We then provide several numerical examples in mathematical biology. We consider applications of this approach to the following areas: population dynamics, mRNA and protein concentration, bacteria and amoeba cells interaction, tumor growth.
Review of the inverse scattering problem at fixed energy in quantum mechanics
Sabatier, P. C.
1972-01-01
Methods of solution of the inverse scattering problem at fixed energy in quantum mechanics are presented. Scattering experiments of a beam of particles at a nonrelativisitic energy by a target made up of particles are analyzed. The Schroedinger equation is used to develop the quantum mechanical description of the system and one of several functions depending on the relative distance of the particles. The inverse problem is the construction of the potentials from experimental measurements.
Directory of Open Access Journals (Sweden)
В С Корнилов
2015-12-01
Full Text Available In article the attention to formation at students of higher educational institutions of the physical and mathematical directions of preparation of fundamental mathematical knowledge in the course of teaching the elective courses devoted to training in the inverse problems for the differential equations is paid. The example of statement of the educational inverse problem for the differential equations which entered the content of such training is given
Globally Convergent Numerical Methods for Coefficient Inverse Problems
2008-09-23
problem (2.20a,b) is the Cauchy problem for a nonlinear integral differential equation with Volterra -like integrals depending on the parameter s, which... integral differential equation of the second order, which arises in the convexification, in a coupled system of nonlinear integral differential...of Timonov was to turn the original nonlinear integral differential equation of the second order, which arises in the convexification, in a coupled
FOREWORD: 4th International Workshop on New Computational Methods for Inverse Problems (NCMIP2014)
2014-10-01
This volume of Journal of Physics: Conference Series is dedicated to the scientific contributions presented during the 4th International Workshop on New Computational Methods for Inverse Problems, NCMIP 2014 (http://www.farman.ens-cachan.fr/NCMIP_2014.html). This workshop took place at Ecole Normale Supérieure de Cachan, on May 23, 2014. The prior editions of NCMIP also took place in Cachan, France, firstly within the scope of ValueTools Conference, in May 2011 (http://www.ncmip.org/2011/), and secondly at the initiative of Institut Farman, in May 2012 and May 2013, (http://www.farman.ens-cachan.fr/NCMIP_2012.html), (http://www.farman.ens-cachan.fr/NCMIP_2013.html). The New Computational Methods for Inverse Problems (NCMIP) Workshop focused on recent advances in the resolution of inverse problems. Indeed, inverse problems appear in numerous scientific areas such as geophysics, biological and medical imaging, material and structure characterization, electrical, mechanical and civil engineering, and finances. The resolution of inverse problems consists of estimating the parameters of the observed system or structure from data collected by an instrumental sensing or imaging device. Its success firstly requires the collection of relevant observation data. It also requires accurate models describing the physical interactions between the instrumental device and the observed system, as well as the intrinsic properties of the solution itself. Finally, it requires the design of robust, accurate and efficient inversion algorithms. Advanced sensor arrays and imaging devices provide high rate and high volume data; in this context, the efficient resolution of the inverse problem requires the joint development of new models and inversion methods, taking computational and implementation aspects into account. During this one-day workshop, researchers had the opportunity to bring to light and share new techniques and results in the field of inverse problems. The topics of the
FOREWORD: 5th International Workshop on New Computational Methods for Inverse Problems
Vourc'h, Eric; Rodet, Thomas
2015-11-01
This volume of Journal of Physics: Conference Series is dedicated to the scientific research presented during the 5th International Workshop on New Computational Methods for Inverse Problems, NCMIP 2015 (http://complement.farman.ens-cachan.fr/NCMIP_2015.html). This workshop took place at Ecole Normale Supérieure de Cachan, on May 29, 2015. The prior editions of NCMIP also took place in Cachan, France, firstly within the scope of ValueTools Conference, in May 2011, and secondly at the initiative of Institut Farman, in May 2012, May 2013 and May 2014. The New Computational Methods for Inverse Problems (NCMIP) workshop focused on recent advances in the resolution of inverse problems. Indeed, inverse problems appear in numerous scientific areas such as geophysics, biological and medical imaging, material and structure characterization, electrical, mechanical and civil engineering, and finances. The resolution of inverse problems consists of estimating the parameters of the observed system or structure from data collected by an instrumental sensing or imaging device. Its success firstly requires the collection of relevant observation data. It also requires accurate models describing the physical interactions between the instrumental device and the observed system, as well as the intrinsic properties of the solution itself. Finally, it requires the design of robust, accurate and efficient inversion algorithms. Advanced sensor arrays and imaging devices provide high rate and high volume data; in this context, the efficient resolution of the inverse problem requires the joint development of new models and inversion methods, taking computational and implementation aspects into account. During this one-day workshop, researchers had the opportunity to bring to light and share new techniques and results in the field of inverse problems. The topics of the workshop were: algorithms and computational aspects of inversion, Bayesian estimation, Kernel methods, learning methods
On rational approximation methods for inverse source problems
Rundell, William
2011-02-01
The basis of most imaging methods is to detect hidden obstacles or inclusions within a body when one can only make measurements on an exterior surface. Such is the ubiquity of these problems, the underlying model can lead to a partial differential equation of any of the major types, but here we focus on the case of steady-state electrostatic or thermal imaging and consider boundary value problems for Laplace\\'s equation. Our inclusions are interior forces with compact support and our data consists of a single measurement of (say) voltage/current or temperature/heat flux on the external boundary. We propose an algorithm that under certain assumptions allows for the determination of the support set of these forces by solving a simpler "equivalent point source" problem, and which uses a Newton scheme to improve the corresponding initial approximation. © 2011 American Institute of Mathematical Sciences.
Cleather, Daniel J; Bull, Anthony M J
2010-11-17
A vast number of biomechanical studies have employed inverse dynamics methods to calculate inter-segmental moments during movement. Although all inverse dynamics methods are rooted in classical mechanics and thus theoretically the same, there exist a number of distinct computational methods. Recent research has demonstrated a key influence of the dynamics computation of the inverse dynamics method on the calculated moments, despite the theoretical equivalence of the methods. The purpose of this study was therefore to explore the influence of the choice of inverse dynamics on the calculation of inter-segmental moments. An inverse dynamics analysis was performed to analyse vertical jumping and weightlifting movements using two distinct methods. The first method was the traditional inverse dynamics approach, in this study characterized as the 3 step method, where inter-segmental moments were calculated in the local coordinate system of each segment, thus requiring multiple coordinate system transformations. The second method (the 1 step method) was the recently proposed approach based on wrench notation that allows all calculations to be performed in the global coordinate system. In order to best compare the effect of the inverse dynamics computation a number of the key assumptions and methods were harmonized, in particular unit quaternions were used to parameterize rotation in both methods in order to standardize the kinematics. Mean peak inter-segmental moments calculated by the two methods were found to agree to 2 decimal places in all cases and were not significantly different (p > 0.05). Equally the normalized dispersions of the two methods were small. In contrast to previously documented research the difference between the two methods was found to be negligible. This study demonstrates that the 1 and 3 step method are computationally equivalent and can thus be used interchangeably in musculoskeletal modelling technology. It is important that future work
Directory of Open Access Journals (Sweden)
Cleather Daniel J
2010-11-01
Full Text Available Abstract Background A vast number of biomechanical studies have employed inverse dynamics methods to calculate inter-segmental moments during movement. Although all inverse dynamics methods are rooted in classical mechanics and thus theoretically the same, there exist a number of distinct computational methods. Recent research has demonstrated a key influence of the dynamics computation of the inverse dynamics method on the calculated moments, despite the theoretical equivalence of the methods. The purpose of this study was therefore to explore the influence of the choice of inverse dynamics on the calculation of inter-segmental moments. Methods An inverse dynamics analysis was performed to analyse vertical jumping and weightlifting movements using two distinct methods. The first method was the traditional inverse dynamics approach, in this study characterized as the 3 step method, where inter-segmental moments were calculated in the local coordinate system of each segment, thus requiring multiple coordinate system transformations. The second method (the 1 step method was the recently proposed approach based on wrench notation that allows all calculations to be performed in the global coordinate system. In order to best compare the effect of the inverse dynamics computation a number of the key assumptions and methods were harmonized, in particular unit quaternions were used to parameterize rotation in both methods in order to standardize the kinematics. Results Mean peak inter-segmental moments calculated by the two methods were found to agree to 2 decimal places in all cases and were not significantly different (p > 0.05. Equally the normalized dispersions of the two methods were small. Conclusions In contrast to previously documented research the difference between the two methods was found to be negligible. This study demonstrates that the 1 and 3 step method are computationally equivalent and can thus be used interchangeably in
An inverse heat transfer problem for optimization of the thermal ...
Indian Academy of Sciences (India)
It is evident that machining process causes development of large quantities of thermal energy within a relatively narrow area of the cutting zone. The generated thermal energy and the problems of its evacuation from the cutting zone account for high temperatures in machining. These increased temperatures exert a ...
An inverse heat transfer problem for optimization of the thermal ...
Indian Academy of Sciences (India)
Abstract. It is evident that machining process causes development of large quan- tities of thermal energy within a relatively narrow area of the cutting zone. The generated thermal energy and the problems of its evacuation from the cutting zone account for high temperatures in machining. These increased temperatures exert ...
Upper bound of errors in solving the inverse problem of identifying a voice source
Leonov, A. S.; Sorokin, V. N.
2017-09-01
The paper considers the inverse problem of finding the shape of a voice-source pulse from a specified segment of a speech signal using a special mathematical model that relates these quantities. A variational method for solving the formulated inverse problem for two new parametric classes of sources is proposed: a piecewise-linear source and an A-source. The error in the obtained approximate solutions of the inverse problem is considered, and a technique to numerically estimate this error is proposed, which is based on the theory of a posteriori estimates of the accuracy in solving ill-posed problems. A computer study of the adequacy of the proposed models of sources, and a study of the a posteriori estimates of the accuracy in solving inverse problems for such sources were performed using various types of voice signals. Numerical experiments for speech signals showed satisfactory properties of such a posteriori estimates, which represent the upper bounds of possible errors in solving the inverse problem. The estimate of the most probable error in determining the source-pulse shapes for the investigated speech material is on average 7%. It is noted that the a posteriori accuracy estimates can be used as a criterion for the quality of determining the voice-source pulse shape in the speaker-identification problem.
An inverse problem of thickness design for bilayer textile materials under low temperature
Energy Technology Data Exchange (ETDEWEB)
Xu Dinghua; Cheng Jianxin; Chen Yuanbo [Department of Mathematics, College of Sciences, Zhejiang Sci-Tech University, Hangzhou 310018, Zhejiang (China); Ge Meibao, E-mail: dhxu6708@zstu.edu.cn [College of Sciences and Arts, Zhejiang Sci-Tech University, Hangzhou 311121, Zhejiang (China)
2011-04-01
The human heat-moisture-comfort level is mainly determined by heat and moisture transfer characteristics in clothing. With respect to the model of steady-state heat and moisture transfer through parallel pore textiles, we propose an inverse problem of thickness design for bilayer textile material under low temperature in this paper. Adopting the idea of regularization method, we formulate the inverse problem solving into a function minimization problem. Combining the finite difference method for ordinary differential equations with direct search method of one-dimensional minimization problems, we derive three kinds of iteration algorithms of regularized solution for the inverse problem of thickness design. Numerical simulation is achieved to verify the efficiency of proposed methods.
Fernández-Muñiz, Zulima; Fernández-Martínez, Juan L.; Srinivasan, Sanjay; Mukerji, Tapan
2015-02-01
Geophysical inverse problems try to infer the value of a physical property of the earth from data measured at the boundary of the domain. Model parameterization is a key concept to make the inverse problem less ill conditioned. In this contribution we compare the performance of four different basis functions, Fourier, Pixel, Haar and Daubechies Wavelets, for a 1D linear continuous inverse problem. Adopting the right parameterization also reduces the number of dimensions in which the inverse problem is going to be solved, allowing easy posterior analysis. To compare the different basis expansions we have studied a simple 1D linear inverse problem in gravimetric inversion for a density anomaly with Gaussian shape. For this simple toy-problem we show that the Fourier basis gives a better reconstruction using Filon's quadrature to avoid numerical instabilities caused by highly oscillating functions, both, in the noise-free and noisy cases. Besides, the Fourier base is the one that provides the lowest reconstruction error for the number of basis terms and the highest condition number. The Haar and pixel (piecewise-continuous functions) bases provide similar results, although the pixel base needs more terms to achieve lower reconstruction errors. Also, the pixel basis is the one that has the lowest condition number that is obviously related to the way the energy in the system matrix is distributed. Besides, the Daubechies Db2 basis expansion is the one that has the highest system rank, it is more difficult to apply to project the integral kernel, and provides the worst results, compared to the other basis expansions. Finally we propose how to generalize this methodology to linear inverse problems in several dimensions and to non-linear problems. A separate paper will be devoted to this subject.
Linear and Nonlinear Filtering and Related Inverse Scattering Problems.
1983-05-01
that this necessitates taking a Bayesian point of view. Stochastic Calculus of Variations could be considered as a special case of Stochastic Control...The question of smoothness of the Zakai equation as a function of y (the observations) and the use of the Malliavin Calculus to obtain bounds on...5. M.G. Krein, "On a Fundamental APproximation Problem in the Theory of Extrapolation and Filtration of Stationary Random Processes," Dokl. Akad
A two-dimensional inverse heat conduction problem for estimating heat source
Shidfar, A.; Zakeri, A.; Neisi, A.
2005-01-01
This note considers the problem of estimating unknown time-varying strength of the temporal-dependent heat source, from measurements of the temperature inside the square domain, when the prior knowledge of the source functions is not available. This problem is an inverse heat conduction problem. In this process, the direct problem will be solved by using the heat fundamental solution. Then a sequential algorithm is developed to solve a Volterra integral equation, which has been produced by...
Inverse source problem and active shielding for composite domains
National Research Council Canada - National Science Library
Ryaben’kii, V.S; Tsynkov, S.V; Utyuzhnikov, S.V
2007-01-01
... desired in the solution is shielding of a given subdomain from the effect of the sources on the complementary domain. This problem is important for many applications. For example, in acoustics one is often interested in protecting a given region of space from the unwanted sound (i.e., noise) that originates from the sources outside of this region. As the protection, or shielding, is rendered by the specially constructed additional sources of sound (rather than, say, by insulation), it is called active shie...
Solution of the Cox-Thompson inverse scattering problem using finite set of phase shifts
Apagyi, B; Scheid, W
2003-01-01
A system of nonlinear equations is presented for the solution of the Cox-Thompson inverse scattering problem (1970 J. Math. Phys. 11 805) at fixed energy. From a given finite set of phase shifts for physical angular momenta, the nonlinear equations determine related sets of asymptotic normalization constants and nonphysical (shifted) angular momenta from which all quantities of interest, including the inversion potential itself, can be calculated. As a first application of the method we use input data consisting of a finite set of phase shifts calculated from Woods-Saxon and box potentials representing interactions with diffuse or sharp surfaces, respectively. The results for the inversion potentials, their first moments and asymptotic properties are compared with those provided by the Newton-Sabatier quantum inversion procedure. It is found that in order to achieve inversion potentials of similar quality, the Cox-Thompson method requires a smaller set of phase shifts than the Newton-Sabatier procedure.
Energy Technology Data Exchange (ETDEWEB)
Krukovsky, P.G. [Institute of Engineering Thermophysics, National Academy of Sciences of Ukraine, Kiev (Ukraine)
1997-12-31
The description of method and software FRIEND which provide a possibility of solution of inverse and inverse design problems on the basis of existing (base) CFD-software for solution of direct problems (in particular, heat-transfer and fluid-flow problems using software PHOENICS) are presented. FRIEND is an independent additional module that widens the operational capacities of the base software unified with this module. This unifying does not require any change or addition to the base software. Interfacing of FRIEND and the base software takes place through input and output files of the base software. A brief description of the computational technique applied for the inverse problem solution, same detailed information on the interfacing of FRIEND and CFD-software and solution results for testing inverse and inverse design problems, obtained using the tandem CFD-software PHOENICS and FRIEND, are presented. (author) 9 refs.
Maximum a posteriori probability estimates in infinite-dimensional Bayesian inverse problems
Helin, T.; Burger, M.
2015-08-01
A demanding challenge in Bayesian inversion is to efficiently characterize the posterior distribution. This task is problematic especially in high-dimensional non-Gaussian problems, where the structure of the posterior can be very chaotic and difficult to analyse. Current inverse problem literature often approaches the problem by considering suitable point estimators for the task. Typically the choice is made between the maximum a posteriori (MAP) or the conditional mean (CM) estimate. The benefits of either choice are not well-understood from the perspective of infinite-dimensional theory. Most importantly, there exists no general scheme regarding how to connect the topological description of a MAP estimate to a variational problem. The recent results by Dashti and others (Dashti et al 2013 Inverse Problems 29 095017) resolve this issue for nonlinear inverse problems in Gaussian framework. In this work we improve the current understanding by introducing a novel concept called the weak MAP (wMAP) estimate. We show that any MAP estimate in the sense of Dashti et al (2013 Inverse Problems 29 095017) is a wMAP estimate and, moreover, how the wMAP estimate connects to a variational formulation in general infinite-dimensional non-Gaussian problems. The variational formulation enables to study many properties of the infinite-dimensional MAP estimate that were earlier impossible to study. In a recent work by the authors (Burger and Lucka 2014 Maximum a posteriori estimates in linear inverse problems with logconcave priors are proper bayes estimators preprint) the MAP estimator was studied in the context of the Bayes cost method. Using Bregman distances, proper convex Bayes cost functions were introduced for which the MAP estimator is the Bayes estimator. Here, we generalize these results to the infinite-dimensional setting. Moreover, we discuss the implications of our results for some examples of prior models such as the Besov prior and hierarchical prior.
Spectrum reconstruction from dose measurements as a linear inverse problem
Armbruster, Benjamin; Hamilton, Russell J.; Kuehl, Arthur K.
2004-11-01
There are three ways to determine the spectrum of a clinical photon beam: direct measurement, modelling the source and reconstruction from ion-chamber measurements. We focus on reconstruction because the necessary equipment is readily available and it provides independent confirmation of source models for a given machine. Reconstruction methods involve measuring the dose in an ion chamber after the beam passes through an attenuator. We gain information about the spectrum from measurements using attenuators of differing compositions and thicknesses since materials have energy dependent attenuation. Unlike the procedures used in other papers, we do not discretize or parametrize the spectrum. With either of these two approximations, reconstruction is a least squares problem. The forward problem of going from a spectrum to a series of dose measurements is a linear operator, with the composition and thickness of the attenuators as parameters. Hence the singular value decomposition (SVD) characterizes this operator. The right singular vectors form a basis for the spectrum, and, at first approximation, only those corresponding to singular values above a threshold are measurable. A more rigorous error analysis shows with what confidence different components of the spectrum can be measured. We illustrate this theory with simulations and an example utilizing six sets of dose measurements with water and lead as attenuators.
A gradient based algorithm to solve inverse plane bimodular problems of identification
Ran, Chunjiang; Yang, Haitian; Zhang, Guoqing
2018-02-01
This paper presents a gradient based algorithm to solve inverse plane bimodular problems of identifying constitutive parameters, including tensile/compressive moduli and tensile/compressive Poisson's ratios. For the forward bimodular problem, a FE tangent stiffness matrix is derived facilitating the implementation of gradient based algorithms, for the inverse bimodular problem of identification, a two-level sensitivity analysis based strategy is proposed. Numerical verification in term of accuracy and efficiency is provided, and the impacts of initial guess, number of measurement points, regional inhomogeneity, and noisy data on the identification are taken into accounts.
Subrahmanyam, P Bala; Sujith, R I; Ramakrishna, M
2003-08-01
An integral method is developed to solve the inverse problem of determining the oscillatory heat release distribution from the knowledge of the acoustic pressure field within a combustor. Unlike earlier approaches, in which the problem is formulated in terms of Fredholm integral equation, the inverse problem is reformulated in terms of Volterra integral equation. This reformulation, valid for low Mach numbers (M2 Volterra integral equation is solved using both direct numerical method and implicit least-squares method. The results show that the implicit least-squares method is superior to the direct numerical method and yields accurate determination of heat release at all frequencies.
Inverse problem theory methods for data fitting and model parameter estimation
Tarantola, A
2002-01-01
Inverse Problem Theory is written for physicists, geophysicists and all scientists facing the problem of quantitative interpretation of experimental data. Although it contains a lot of mathematics, it is not intended as a mathematical book, but rather tries to explain how a method of acquisition of information can be applied to the actual world.The book provides a comprehensive, up-to-date description of the methods to be used for fitting experimental data, or to estimate model parameters, and to unify these methods into the Inverse Problem Theory. The first part of the book deals wi
Two numerical methods for an inverse problem for the 2-D Helmholtz equation
Gryazin, Y A; Lucas, T R
2003-01-01
Two solution methods for the inverse problem for the 2-D Helmholtz equation are developed, tested, and compared. The proposed approaches are based on a marching finite-difference scheme which requires the solution of an overdetermined system at each step. The preconditioned conjugate gradient method is used for rapid solutions of these systems and an efficient preconditioner has been developed for this class of problems. Underlying target applications include the imaging of land mines, unexploded ordinance, and pollutant plumes in environmental cleanup sites, each formulated as an inverse problem for a 2-D Helmholtz equation. The images represent the electromagnetic properties of the respective underground regions. Extensive numerical results are presented.
Oblique projections and standard-form transformations for discrete inverse problems
DEFF Research Database (Denmark)
Hansen, Per Christian
2013-01-01
This tutorial paper considers a specific computational tool for the numerical solution of discrete inverse problems, known as the standard-form transformation, by which we can treat general Tikhonov regularization problems efficiently. In the tradition of B. N. Datta's expositions of numerical...
Inverse Problems for a Parabolic Integrodifferential Equation in a Convolutional Weak Form
Directory of Open Access Journals (Sweden)
Kairi Kasemets
2013-01-01
Full Text Available We deduce formulas for the Fréchet derivatives of cost functionals of several inverse problems for a parabolic integrodifferential equation in a weak formulation. The method consists in the application of an integrated convolutional form of the weak problem and all computations are implemented in regular Sobolev spaces.
On the inverse problem of blade design for centrifugal pumps and fans
Kruyt, Nicolaas P.; Westra, R.W.
2014-01-01
The inverse problem of blade design for centrifugal pumps and fans has been studied. The solution to this problem provides the geometry of rotor blades that realize specified performance characteristics, together with the corresponding flow field. Here a three-dimensional solution method is
Schuster, Thomas; Hofmann, Bernd; Kaltenbacher, Barbara
2012-10-01
Inverse problems can usually be modelled as operator equations in infinite-dimensional spaces with a forward operator acting between Hilbert or Banach spaces—a formulation which quite often also serves as the basis for defining and analyzing solution methods. The additional amount of structure and geometric interpretability provided by the concept of an inner product has rendered these methods amenable to a convergence analysis, a fact which has led to a rigorous and comprehensive study of regularization methods in Hilbert spaces over the last three decades. However, for numerous problems such as x-ray diffractometry, certain inverse scattering problems and a number of parameter identification problems in PDEs, the reasons for using a Hilbert space setting seem to be based on conventions rather than an appropriate and realistic model choice, so often a Banach space setting would be closer to reality. Furthermore, non-Hilbertian regularization and data fidelity terms incorporating a priori information on solution and noise, such as general Lp-norms, TV-type norms, or the Kullback-Leibler divergence, have recently become very popular. These facts have motivated intensive investigations on regularization methods in Banach spaces, a topic which has emerged as a highly active research field within the area of inverse problems. Meanwhile some of the most well-known regularization approaches, such as Tikhonov-type methods requiring the solution of extremal problems, and iterative ones like the Landweber method, the Gauss-Newton method, as well as the approximate inverse method, have been investigated for linear and nonlinear operator equations in Banach spaces. Convergence with rates has been proven and conditions on the solution smoothness and on the structure of nonlinearity have been formulated. Still, beyond the existing results a large number of challenging open questions have arisen, due to the more involved handling of general Banach spaces and the larger variety
Integral and Variational Formulations for the Helmholtz Equation Inverse Source Problem
Directory of Open Access Journals (Sweden)
Marcelo L. Rainha
2012-01-01
Full Text Available The purpose of this paper is to explore the Hilbert space functional structure of the Helmholtz equation inverse source problem. An integral equation for the sources reconstruction based on the composition of the trace and Green's function operators is introduced and compared with the reciprocity source reconstruction methodologies. An equivalence theorem comparing the integral inverse source equation with the variational weak reciprocity gap functional equation is then demonstrated. Some examples on applications to the unitary disk are presented.
Statistical mechanics of the inverse Ising problem and the optimal objective function
Berg, Johannes
2017-08-01
The inverse Ising problem seeks to reconstruct the parameters of an Ising Hamiltonian on the basis of spin configurations sampled from the Boltzmann measure. Over the last decade, many applications of the inverse Ising problem have arisen, driven by the advent of large-scale data across different scientific disciplines. Recently, strategies to solve the inverse Ising problem based on convex optimisation have proven to be very successful. These approaches maximise particular objective functions with respect to the model parameters. Examples are the pseudolikelihood method and interaction screening. In this paper, we establish a link between approaches to the inverse Ising problem based on convex optimisation and the statistical physics of disordered systems. We characterise the performance of an arbitrary objective function and calculate the objective function which optimally reconstructs the model parameters. We evaluate the optimal objective function within a replica-symmetric ansatz and compare the results of the optimal objective function with other reconstruction methods. Apart from giving a theoretical underpinning to solving the inverse Ising problem by convex optimisation, the optimal objective function outperforms state-of-the-art methods, albeit by a small margin.
A Bayesian setting for an inverse problem in heat transfer
Ruggeri, Fabrizio
2014-01-06
In this work a Bayesian setting is developed to infer the thermal conductivity, an unknown parameter that appears into heat equation. Temperature data are available on the basis of cooling experiments. The realistic assumption that the boundary data are noisy is introduced, for a given prescribed initial condition. We show how to derive the global likelihood function for the forward boundary-initial condition problem, given the values of the temperature field plus Gaussian noise. We assume that the thermal conductivity parameter can be modelled a priori through a lognormal distributed random variable or by means of a space-dependent stationary lognormal random field. In both cases, given Gaussian priors for the time-dependent Dirichlet boundary values, we marginalize out analytically the joint posterior distribution of and the random boundary conditions, TL and TR, using the linearity of the heat equation. Synthetic data are used to carry out the inference. We exploit the concentration of the posterior distribution of , using the Laplace approximation and therefore avoiding costly MCMC computations.
Inverse problem in archeological magnetic surveys using complex wavelet transform.
Saracco, G.; Moreau, F.; Mathe, P. E.; Hermitte, D.
2003-04-01
The wavelet transform applied to potential fields (electric, magnetic, or gravimetric, ...) has been now used from several years in geophysical applications, in particular to define the depth of potentiel sources verifying Poisson equation and responsible for potential anomalies measured at the ground surface. The complex continuous wavelet transform (CCWT) has been described, but the phase has not yet been exploited. (For these kinds of problem we construct a complex analyzing wavelet by Hilbert transforms of the Poisson or derivative of the Poisson wavelet which is real by definition). We show, here, that the phase of the CCWT provides useful information on the geometric and total magnetic inclination of the potential sources, as the modulus allows to characterize their depth and heterogenety degree. Regarding the properties of the phase compared to the modulus, it is more stable in presence of noise and we can defined it, independantly of the low level of energy of the signal. In this sense, information carried by the phase is more efficient to detect small objects or to separate close sources. We have applied a multi-scale analysis on magnetic measurements providing from a cesium magnetometer on the Fox-Amphoux site (France), to detect and localize buried structures like antik ovens. Conjointly, a rock magnetic study including susceptibility and magnetisations (induced or remanent) measurements give a better constrain on the magnetic parameters we want to extract.
Zatsiorsky, Vladimir M.
2011-01-01
One of the key problems of motor control is the redundancy problem, in particular how the central nervous system (CNS) chooses an action out of infinitely many possible. A promising way to address this question is to assume that the choice is made based on optimization of a certain cost function. A number of cost functions have been proposed in the literature to explain performance in different motor tasks: from force sharing in grasping to path planning in walking. However, the problem of uniqueness of the cost function(s) was not addressed until recently. In this article, we analyze two methods of finding additive cost functions in inverse optimization problems with linear constraints, so-called linear-additive inverse optimization problems. These methods are based on the Uniqueness Theorem for inverse optimization problems that we proved recently (Terekhov et al., J Math Biol 61(3):423–453, 2010). Using synthetic data, we show that both methods allow for determining the cost function. We analyze the influence of noise on the both methods. Finally, we show how a violation of the conditions of the Uniqueness Theorem may lead to incorrect solutions of the inverse optimization problem. PMID:21311907
Solving Large-Scale Inverse Magnetostatic Problems using the Adjoint Method
Bruckner, Florian; Wautischer, Gregor; Huber, Christian; Vogler, Christoph; Hinze, Michael; Suess, Dieter
2016-01-01
An efficient algorithm for the reconstruction of the magnetization state within magnetic components is presented. The occurring inverse magnetostatic problem is solved by means of an adjoint approach, based on the Fredkin-Koehler method for the solution of the forward problem. Due to the use of hybrid FEM-BEM coupling combined with matrix compression techniques the resulting algorithm is well suited for large-scale problems. Furthermore the reconstruction of the magnetization state within a permanent magnet is demonstrated.
On a class of inverse problems for a parabolic equation with involution
Sarsenbi, Abdisalam A.
2017-09-01
A class of inverse problems for a heat equation with involution perturbation is considered using four different bound-ary conditions, namely, Dirichlet, Neumann, periodic and anti-periodic boundary conditions. Proved theorems on existence and uniqueness of solutions to these problems are presented. Solutions are obtained in the form of series expansion using a set of appropriate orthogonal basis for each problem. Convergence of the obtained solutions is also discussed.
Uniqueness of a 3-D coefficient inverse scattering problem without the phase information
Klibanov, Michael V.; Romanov, Vladimir G.
2017-09-01
We use a new method to prove the uniqueness theorem for a coefficient inverse scattering problem without the phase information for the 3-D Helmholtz equation. We consider the case when only the modulus of the scattered wave field is measured and the phase is not measured. The spatially distributed refractive index is the subject of interest in this problem. Applications of this problem are in imaging of nanostructures and biological cells.
Fourier truncation method for an inverse source problem for space-time fractional diffusion equation
Directory of Open Access Journals (Sweden)
Nguyen Huy Tuan
2017-05-01
Full Text Available In this article, we study an inverse problem to determine an unknown source term in a space time fractional diffusion equation, whereby the data are obtained at a certain time. In general, this problem is ill-posed in the sense of Hadamard, so the Fourier truncation method is proposed to solve the problem. In the theoretical results, we propose a priori and a posteriori parameter choice rules and analyze them.
An inverse Stefan problem relevant to boilover: Heat balance integral solutions and analysis
Directory of Open Access Journals (Sweden)
Hristov Jordan
2007-01-01
Full Text Available Stefan problems relevant to burning oil-water systems are formulated. Two moving boundary sub-problems are defined: burning liquid surface and formation of a distillation ("hot zone" layer beneath it. The basic model considers a heat transfer equation with internal neat generation due to radiation flux absorbed in the fuel depth. Inverse Stefan problem corresponding to the first case solved by the heat balance integral method and dimensionless scaling of semi-analytical solutions are at issue. .
An Inverse Robust Optimisation Approach for a Class of Vehicle Routing Problems under Uncertainty
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Liang Sun
2016-01-01
Full Text Available There is a trade-off between the total penalty paid to customers (TPC and the total transportation cost (TTC in depot for vehicle routing problems under uncertainty (VRPU. The trade-off refers to the fact that the TTC in depot inevitably increases when the TPC decreases and vice versa. With respect to this issue, the vehicle routing problem (VRP with uncertain customer demand and travel time was studied to optimise the TPC and the TTC in depot. In addition, an inverse robust optimisation approach was proposed to solve this kind of VRPU by combining the ideas of inverse optimisation and robust optimisation so as to improve both the TPC and the TTC in depot. The method aimed to improve the corresponding TTC of the robust optimisation solution under the minimum TPC through minimising the adjustment of benchmark road transportation cost. According to the characteristics of the inverse robust optimisation model, a genetic algorithm (GA and column generation algorithm are combined to solve the problem. Moreover, 39 test problems are solved by using an inverse robust optimisation approach: the results show that both the TPC and TTC obtained by using the inverse robust optimisation approach are less than those calculated using a robust optimisation approach.
Efficient generalized Golub–Kahan based methods for dynamic inverse problems
Chung, Julianne; Saibaba, Arvind K.; Brown, Matthew; Westman, Erik
2018-02-01
We consider efficient methods for computing solutions to and estimating uncertainties in dynamic inverse problems, where the parameters of interest may change during the measurement procedure. Compared to static inverse problems, incorporating prior information in both space and time in a Bayesian framework can become computationally intensive, in part, due to the large number of unknown parameters. In these problems, explicit computation of the square root and/or inverse of the prior covariance matrix is not possible, so we consider efficient, iterative, matrix-free methods based on the generalized Golub–Kahan bidiagonalization that allow automatic regularization parameter and variance estimation. We demonstrate that these methods for dynamic inversion can be more flexible than standard methods and develop efficient implementations that can exploit structure in the prior, as well as possible structure in the forward model. Numerical examples from photoacoustic tomography, space-time deblurring, and passive seismic tomography demonstrate the range of applicability and effectiveness of the described approaches. Specifically, in passive seismic tomography, we demonstrate our approach on both synthetic and real data. To demonstrate the scalability of our algorithm, we solve a dynamic inverse problem with approximately 43 000 measurements and 7.8 million unknowns in under 40 s on a standard desktop.
Khalil, Mohamed A.; Santos, Fernando A. Monteiro
2013-02-01
The Wadi El Natrun area is characterized by a very complicated geological and hydrogeological system. 45 vertical electrical soundings (Schlumberger array) were measured in the study area to elucidate the peculiarity of this unique regime, specifically the nature of waterless area. 2D and 3D resistivity inversion based on the finite element technique and regularization method were applied on the data set. 2D and 3D model resolution was investigated through the use of the Depth and Volume of Investigation Indexes. A very good matching was found between the zones of high resistivity, the waterless area, and the non-productive wells. The low resistivity zones (corresponding to Lower Pliocene clay) were also identified. The middle resistivity fresh water aquifer zones were recognized. Available results can assist in the aquifer management by selecting the most productive zone of groundwater.
Energy Technology Data Exchange (ETDEWEB)
Balci, Murat [Dept. of Mechanical Engineering, Bayburt University, Bayburt (Turkmenistan); Gundogdu, Omer [Dept. of Mechanical Engineering, Ataturk University, Erzurum (Turkmenistan)
2017-01-15
In this study, estimation of some physical properties of a laminated composite plate was conducted via the inverse vibration problem. Laminated composite plate was modelled and simulated to obtain vibration responses for different length-to-thickness ratio in ANSYS. Furthermore, a numerical finite element model was developed for the laminated composite utilizing the Kirchhoff plate theory and programmed in MATLAB for simulations. Optimizing the difference between these two vibration responses, inverse vibration problem was solved to obtain some of the physical properties of the laminated composite using genetic algorithms. The estimated parameters are compared with the theoretical results, and a very good correspondence was observed.
Methane combustion kinetic rate constants determination: an ill-posed inverse problem analysis
Directory of Open Access Journals (Sweden)
Bárbara D. L. Ferreira
2013-01-01
Full Text Available Methane combustion was studied by the Westbrook and Dryer model. This well-established simplified mechanism is very useful in combustion science, for computational effort can be notably reduced. In the inversion procedure to be studied, rate constants are obtained from [CO] concentration data. However, when inherent experimental errors in chemical concentrations are considered, an ill-conditioned inverse problem must be solved for which appropriate mathematical algorithms are needed. A recurrent neural network was chosen due to its numerical stability and robustness. The proposed methodology was compared against Simplex and Levenberg-Marquardt, the most used methods for optimization problems.
The Bayesian formulation and well-posedness of fractional elliptic inverse problems
García Trillos, Nicolás; Sanz-Alonso, Daniel
2017-06-01
We study the inverse problem of recovering the order and the diffusion coefficient of an elliptic fractional partial differential equation from a finite number of noisy observations of the solution. We work in a Bayesian framework and show conditions under which the posterior distribution is given by a change of measure from the prior. Moreover, we show well-posedness of the inverse problem, in the sense that small perturbations of the observed solution lead to small Hellinger perturbations of the associated posterior measures. We thus provide a mathematical foundation to the Bayesian learning of the order—and other inputs—of fractional models.
Fractal-Based Methods and Inverse Problems for Differential Equations: Current State of the Art
Directory of Open Access Journals (Sweden)
Herb E. Kunze
2014-01-01
Full Text Available We illustrate, in this short survey, the current state of the art of fractal-based techniques and their application to the solution of inverse problems for ordinary and partial differential equations. We review several methods based on the Collage Theorem and its extensions. We also discuss two innovative applications: the first one is related to a vibrating string model while the second one considers a collage-based approach for solving inverse problems for partial differential equations on a perforated domain.
SIPPI: A Matlab toolbox for sampling the solution to inverse problems with complex prior information
DEFF Research Database (Denmark)
Hansen, Thomas Mejer; Cordua, Knud Skou; Looms, Majken Caroline
2013-01-01
We present an application of the SIPPI Matlab toolbox, to obtain a sample from the a posteriori probability density function for the classical tomographic inversion problem. We consider a number of different forward models, linear and non-linear, such as ray based forward models that rely...... sampler, for non-linear non-Gaussian inverse problems. To illustrate the applicability of the SIPPI toolbox to a tomographic field data set we use a cross-borehole traveltime data set from Arrenæs, Denmark. Both the computer code and the data are released in the public domain using open source and open...
DEFF Research Database (Denmark)
Lange, Katrine; Frydendall, Jan; Cordua, Knud Skou
2012-01-01
The frequency matching method defines a closed form expression for a complex prior that quantifies the higher order statistics of a proposed solution model to an inverse problem. While existing solution methods to inverse problems are capable of sampling the solution space while taking into account...... arbitrarily complex a priori information defined by sample algorithms, it is not possible to directly compute the maximum a posteriori model, as the prior probability of a solution model cannot be expressed. We demonstrate how the frequency matching method enables us to compute the maximum a posteriori...
A generalization of szebehely's inverse problem of dynamics in dimension three
Sarlet, W.; Mestdag, T.; Prince, G.
2017-06-01
Extending a previous paper, we present a generalization in dimension 3 of the traditional Szebehely-type inverse problem. In that traditional setting, the data are curves determined as the intersection of two families of surfaces, and the problem is to find a potential V such that the Lagrangian L = T - V, where T is the standard Euclidean kinetic energy function, generates integral curves which include the given family of curves. Our more general way of posing the problem makes use of ideas of the inverse problem of the calculus of variations and essentially consists of allowing more general kinetic energy functions, with a metric which is still constant, but need not be the standard Euclidean one. In developing our generalization, we review and clarify different aspects of the existing literature on the problem and illustrate the relevance of the newly introduced additional freedom with many examples.
Wu, Sheng-Jhih; Chu, Moody T.
2017-08-01
An inverse eigenvalue problem usually entails two constraints, one conditioned upon the spectrum and the other on the structure. This paper investigates the problem where triple constraints of eigenvalues, singular values, and diagonal entries are imposed simultaneously. An approach combining an eclectic mix of skills from differential geometry, optimization theory, and analytic gradient flow is employed to prove the solvability of such a problem. The result generalizes the classical Mirsky, Sing-Thompson, and Weyl-Horn theorems concerning the respective majorization relationships between any two of the arrays of main diagonal entries, eigenvalues, and singular values. The existence theory fills a gap in the classical matrix theory. The problem might find applications in wireless communication and quantum information science. The technique employed can be implemented as a first-step numerical method for constructing the matrix. With slight modification, the approach might be used to explore similar types of inverse problems where the prescribed entries are at general locations.
Study on Parameter Optimization for Support Vector Regression in Solving the Inverse ECG Problem
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Mingfeng Jiang
2013-01-01
Full Text Available The typical inverse ECG problem is to noninvasively reconstruct the transmembrane potentials (TMPs from body surface potentials (BSPs. In the study, the inverse ECG problem can be treated as a regression problem with multi-inputs (body surface potentials and multi-outputs (transmembrane potentials, which can be solved by the support vector regression (SVR method. In order to obtain an effective SVR model with optimal regression accuracy and generalization performance, the hyperparameters of SVR must be set carefully. Three different optimization methods, that is, genetic algorithm (GA, differential evolution (DE algorithm, and particle swarm optimization (PSO, are proposed to determine optimal hyperparameters of the SVR model. In this paper, we attempt to investigate which one is the most effective way in reconstructing the cardiac TMPs from BSPs, and a full comparison of their performances is also provided. The experimental results show that these three optimization methods are well performed in finding the proper parameters of SVR and can yield good generalization performance in solving the inverse ECG problem. Moreover, compared with DE and GA, PSO algorithm is more efficient in parameters optimization and performs better in solving the inverse ECG problem, leading to a more accurate reconstruction of the TMPs.
An automatization of Barnsley's algorithm for the inverse problem of iterated function systems.
Wadströmer, Niclas
2003-01-01
We present an automatization of Barnsley's manual algorithm for the solution of the inverse problem of iterated function systems (IFSs). The problem is to retrieve the number of mappings and the parameters of an IFS from a digital binary image approximating the attractor induced by the IFS. M.F. Barnsley et al. described a way to solve manually the inverse problem by identifying the fragments of which the collage is composed, and then computing the parameters of the mappings (Barnsley et al., Proc. Nat. Acad. Sci. USA, vol.83, p.1975-7, 1986; Barnsley, "Fractals Everywhere", Academic, 1988; Barnsley and Hurd, L., "Fractal Image Compression", A.K. Peters, 1992). The automatic algorithm searches through a finite set of points in the parameter space determining a set of affine mappings. The algorithm uses the collage theorem and the Hausdorff metric. The inverse problem of IFSs is related to the image coding of binary images. If the number of mappings and the parameters of an IFS, with not too many mappings, could be obtained from a binary image, then this would give an efficient representation of the image. It is shown that the inverse problem solved by the automatic algorithm has a solution and some experiments show that the automatic algorithm is able to retrieve an IFS, including the number of mappings, from a digital binary image approximating the attractor induced by the IFS.
Study on parameter optimization for support vector regression in solving the inverse ECG problem.
Jiang, Mingfeng; Jiang, Shanshan; Zhu, Lingyan; Wang, Yaming; Huang, Wenqing; Zhang, Heng
2013-01-01
The typical inverse ECG problem is to noninvasively reconstruct the transmembrane potentials (TMPs) from body surface potentials (BSPs). In the study, the inverse ECG problem can be treated as a regression problem with multi-inputs (body surface potentials) and multi-outputs (transmembrane potentials), which can be solved by the support vector regression (SVR) method. In order to obtain an effective SVR model with optimal regression accuracy and generalization performance, the hyperparameters of SVR must be set carefully. Three different optimization methods, that is, genetic algorithm (GA), differential evolution (DE) algorithm, and particle swarm optimization (PSO), are proposed to determine optimal hyperparameters of the SVR model. In this paper, we attempt to investigate which one is the most effective way in reconstructing the cardiac TMPs from BSPs, and a full comparison of their performances is also provided. The experimental results show that these three optimization methods are well performed in finding the proper parameters of SVR and can yield good generalization performance in solving the inverse ECG problem. Moreover, compared with DE and GA, PSO algorithm is more efficient in parameters optimization and performs better in solving the inverse ECG problem, leading to a more accurate reconstruction of the TMPs.
A numerical study of the inverse problem of breast infrared thermography modeling
Jiang, Li; Zhan, Wang; Loew, Murray H.
2010-03-01
Infrared thermography has been shown to be a useful adjunctive tool for breast cancer detection. Previous thermography modeling techniques generally dealt with the "forward problem", i.e., to estimate the breast thermogram from known properties of breast tissues. The present study aims to deal with the so-called "inverse problem", namely to estimate the thermal properties of the breast tissues from the observed surface temperature distribution. By comparison, the inverse problem is a more direct way of interpreting a breast thermogram for specific physiological and/or pathological information. In tumor detection, for example, it is particularly important to estimate the tumor-induced thermal contrast, even though the corresponding non-tumor thermal background usually is unknown due to the difficulty of measuring the individual thermal properties. Inverse problem solving is technically challenging due to its ill-posed nature, which is evident primarily by its sensitivity to imaging noise. Taking advantage of our previously developed forward-problemsolving techniques with comprehensive thermal-elastic modeling, we examine here the feasibility of solving the inverse problem of the breast thermography. The approach is based on a presumed spatial constraint applied to three major thermal properties, i.e., thermal conductivity, blood perfusion, and metabolic heat generation, for each breast tissue type. Our results indicate that the proposed inverse-problem-solving scheme can be numerically stable under imaging noise of SNR ranging 32 ~ 40 dB, and that the proposed techniques can be effectively used to improve the estimation to the tumor-induced thermal contrast, especially for smaller and deeper tumors.
Jha, Madan K.; Kumar, S.; Chowdhury, A.
2008-09-01
SummaryGrowing water scarcity in West Midnapore district of West Bengal, India, is threatening sustainable agricultural production as well as sanitation of the inhabitants. Because of its several inherent qualities, groundwater can play an important role in ensuring sustainable water supply in the district. This study was carried out to assess groundwater condition in the Salboni Block of West Midnapore district using surface resistivity method. Vertical electrical sounding (VES) surveys were carried out at 38 sites using the Schlumberger array. The apparent resistivity-depth datasets (henceforth called 'VES data') thus obtained were interpreted by the genetic algorithm (GA) optimization technique. A GA-based stand-alone computer program was developed for optimizing subsurface layer parameters (true resistivity and thickness) from the VES data. The optimal layer parameters were then correlated with the available well logs to identify aquifer and confining layers. Moreover, a groundwater potential map was created by integrating the thematic layers of aquifer resistivity and thickness in a GIS environment. In order to explore the spatial variation of layer resistivity at a particular depth, resistivity contour maps of the study area for different depths were prepared using ArcView software. The GA technique yielded layer parameters with reasonably low values of root mean square error (0.36-9.75 Ω m) for most VES datasets. It was found that shallow aquifers exist at depths ranging from 4 to 19 m and relatively deep aquifers from 24 to 60 m below the ground surface. The study area is classified into 'very good', 'good', 'moderate' and 'poor' groundwater potential zones, with a majority of the area having good to moderate groundwater prospect. The resistivity contour maps for different depths revealed that deeper aquifers are prevalent in the study area. It is concluded that the GA technique is efficient and reliable for determining subsurface layer parameters from the
Inverse problem of the vibrational band gap of periodically supported beam
Shi, Xiaona; Shu, Haisheng; Dong, Fuzhen; Zhao, Lei
2017-04-01
The researches of periodic structures have a long history with the main contents confined in the field of forward problem. In this paper, the inverse problem is considered and an overall frame is proposed which includes two main stages, i.e., the band gap criterion and its optimization. As a preliminary investigation, the inverse problem of the flexural vibrational band gap of a periodically supported beam is analyzed. According to existing knowledge of its forward problem, the band gap criterion is given in implicit form. Then, two cases with three independent parameters, namely the double supported case and the triple one, are studied in detail and the explicit expressions of the feasible domain are constructed by numerical fitting. Finally, the parameter optimization of the double supported case with three variables is conducted using genetic algorithm aiming for the best mean attenuation within specified frequency band.
SIPPI: A Matlab toolbox for sampling the solution to inverse problems with complex prior information
DEFF Research Database (Denmark)
Hansen, Thomas Mejer; Cordua, Knud Skou; Caroline Looms, Majken
2013-01-01
From a probabilistic point-of-view, the solution to an inverse problem can be seen as a combination of independent states of information quantified by probability density functions. Typically, these states of information are provided by a set of observed data and some a priori information on the ...
An inverse problem for a semilinear parabolic equation arising from cardiac electrophysiology
Beretta, Elena; Cavaterra, Cecilia; Cerutti, M. Cristina; Manzoni, Andrea; Ratti, Luca
2017-10-01
In this paper we develop theoretical analysis and numerical reconstruction techniques for the solution of an inverse boundary value problem dealing with the nonlinear, time-dependent monodomain equation, which models the evolution of the electric potential in the myocardial tissue. The goal is the detection of an inhomogeneity \
An inverse problem for Maxwell’s equations with Lipschitz parameters
Pichler, Monika
2018-02-01
We consider an inverse boundary value problem for Maxwell’s equations, which aims to recover the electromagnetic material properties of a body from measurements on the boundary. We show that a Lipschitz continuous conductivity, electric permittivity, and magnetic permeability are uniquely determined by knowledge of all tangential electric and magnetic fields on the boundary of the body at a fixed frequency.
Stritzel, J.; Melchert, O.; Wollweber, M.; Roth, B.
2017-09-01
The direct problem of optoacoustic signal generation in biological media consists of solving an inhomogeneous three-dimensional (3D) wave equation for an initial acoustic stress profile. In contrast, the more defiant inverse problem requires the reconstruction of the initial stress profile from a proper set of observed signals. In this article, we consider an effectively 1D approach, based on the assumption of a Gaussian transverse irradiation source profile and plane acoustic waves, in which the effects of acoustic diffraction are described in terms of a linear integral equation. The respective inverse problem along the beam axis can be cast into a Volterra integral equation of the second kind for which we explore here efficient numerical schemes in order to reconstruct initial stress profiles from observed signals, constituting a methodical progress of computational aspects of optoacoustics. In this regard, we explore the validity as well as the limits of the inversion scheme via numerical experiments, with parameters geared toward actual optoacoustic problem instances. The considered inversion input consists of synthetic data, obtained in terms of the effectively 1D approach, and, more generally, a solution of the 3D optoacoustic wave equation. Finally, we also analyze the effect of noise and different detector-to-sample distances on the optoacoustic signal and the reconstructed pressure profiles.
Stritzel, J; Melchert, O; Wollweber, M; Roth, B
2017-09-01
The direct problem of optoacoustic signal generation in biological media consists of solving an inhomogeneous three-dimensional (3D) wave equation for an initial acoustic stress profile. In contrast, the more defiant inverse problem requires the reconstruction of the initial stress profile from a proper set of observed signals. In this article, we consider an effectively 1D approach, based on the assumption of a Gaussian transverse irradiation source profile and plane acoustic waves, in which the effects of acoustic diffraction are described in terms of a linear integral equation. The respective inverse problem along the beam axis can be cast into a Volterra integral equation of the second kind for which we explore here efficient numerical schemes in order to reconstruct initial stress profiles from observed signals, constituting a methodical progress of computational aspects of optoacoustics. In this regard, we explore the validity as well as the limits of the inversion scheme via numerical experiments, with parameters geared toward actual optoacoustic problem instances. The considered inversion input consists of synthetic data, obtained in terms of the effectively 1D approach, and, more generally, a solution of the 3D optoacoustic wave equation. Finally, we also analyze the effect of noise and different detector-to-sample distances on the optoacoustic signal and the reconstructed pressure profiles.
Large scale inverse problems computational methods and applications in the earth sciences
Scheichl, Robert; Freitag, Melina A; Kindermann, Stefan
2013-01-01
This book is thesecond volume of three volume series recording the ""Radon Special Semester 2011 on Multiscale Simulation & Analysis in Energy and the Environment"" taking place in Linz, Austria, October 3-7, 2011. The volume addresses the common ground in the mathematical and computational procedures required for large-scale inverse problems and data assimilation in forefront applications.
Inverse Problem for the Vibrating Beam in the Free/Clamped Configuration,
1979-01-01
such as in seismic prospecting wherr this stripping-off is usually carried out in the time domain (Berkhout & van Wulfften Palthe , 1979). The Stielties...multiplicity of solutions of the inverse problem for a vibrating beam. SIAM 37, 605-613. Berkhout, A.J. & van Wulfften Palthe , D. W. 1979 Migration in
Forming ecological culture of students in teaching inverse problems for the differential equations
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Виктор Семенович Корнилов
2014-12-01
Full Text Available In article the attention to formation of ecological culture of students of physical and mathematical specialties of higher education institutions when training in the inverse problems for the differential equations is paid. Examples of educational tasks in the course of which decision students get skills of logical reasonings of ecological character are given.
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Charyyar Ashyralyyev
2015-07-01
Full Text Available This article studies the numerical solution of inverse problems for the multidimensional elliptic equation with Dirichlet-Neumann boundary conditions and Neumann type overdetermination. We present first and second order accuracy difference schemes. The stability and almost coercive stability inequalities for the solution are obtained. Numerical examples with explanation on the implementation illustrate the theoretical results.
Global stability for an inverse problem in soil-structure interaction.
Alessandrini, G; Morassi, A; Rosset, E; Vessella, S
2015-07-08
We consider the inverse problem of determining the Winkler subgrade reaction coefficient of a slab foundation modelled as a thin elastic plate clamped at the boundary. The plate is loaded by a concentrated force and its transversal deflection is measured at the interior points. We prove a global Hölder stability estimate under (mild) regularity assumptions on the unknown coefficient.
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Е Ы Бидайбеков
2015-12-01
Full Text Available In article methodical aspects of training of students of physical and mathematical and natural-science specialties in the inverse problems for the ordinary differential equations are stated. Algorithms of the solution of some statements of the inverse problems for the ordinary differential equations which are included into the content of such training are given. Results of calculations of numerical solutions of the corresponding inverse problems are given in system of computer mathematics of Mathcad.
Ryzhikov, I. S.; Semenkin, E. S.
2017-02-01
This study is focused on solving an inverse mathematical modelling problem for dynamical systems based on observation data and control inputs. The mathematical model is being searched in the form of a linear differential equation, which determines the system with multiple inputs and a single output, and a vector of the initial point coordinates. The described problem is complex and multimodal and for this reason the proposed evolutionary-based optimization technique, which is oriented on a dynamical system identification problem, was applied. To improve its performance an algorithm restart operator was implemented.
Solving the Axisymmetric Inverse Heat Conduction Problem by a Wavelet Dual Least Squares Method
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Fu Chu-Li
2009-01-01
Full Text Available We consider an axisymmetric inverse heat conduction problem of determining the surface temperature from a fixed location inside a cylinder. This problem is ill-posed; the solution (if it exists does not depend continuously on the data. A special project method—dual least squares method generated by the family of Shannon wavelet is applied to formulate regularized solution. Meanwhile, an order optimal error estimate between the approximate solution and exact solution is proved.
Variable-permittivity linear inverse problem for the H(sub z)-polarized case
Moghaddam, M.; Chew, W. C.
1993-01-01
The H(sub z)-polarized inverse problem has rarely been studied before due to the complicated way in which the unknown permittivity appears in the wave equation. This problem is equivalent to the acoustic inverse problem with variable density. We have recently reported the solution to the nonlinear variable-permittivity H(sub z)-polarized inverse problem using the Born iterative method. Here, the linear inverse problem is solved for permittivity (epsilon) and permeability (mu) using a different approach which is an extension of the basic ideas of diffraction tomography (DT). The key to solving this problem is to utilize frequency diversity to obtain the required independent measurements. The receivers are assumed to be in the far field of the object, and plane wave incidence is also assumed. It is assumed that the scatterer is weak, so that the Born approximation can be used to arrive at a relationship between the measured pressure field and two terms related to the spatial Fourier transform of the two unknowns, epsilon and mu. The term involving permeability corresponds to monopole scattering and that for permittivity to dipole scattering. Measurements at several frequencies are used and a least squares problem is solved to reconstruct epsilon and mu. It is observed that the low spatial frequencies in the spectra of epsilon and mu produce inaccuracies in the results. Hence, a regularization method is devised to remove this problem. Several results are shown. Low contrast objects for which the above analysis holds are used to show that good reconstructions are obtained for both permittivity and permeability after regularization is applied.
An inverse source problem of the Poisson equation with Cauchy data
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Ji-Chuan Liu
2017-05-01
Full Text Available In this article, we study an inverse source problem of the Poisson equation with Cauchy data. We want to find iterative algorithms to detect the hidden source within a body from measurements on the boundary. Our goal is to reconstruct the location, the size and the shape of the hidden source. This problem is ill-posed, regularization techniques should be employed to obtain the regularized solution. Numerical examples show that our proposed algorithms are valid and effective.
An inverse design problem of estimating optimal shape of cooling passages in turbine blades
Energy Technology Data Exchange (ETDEWEB)
Chenghung Huang; Taoyen Hsiung [National Cheng Kung University, Tainan (Taiwan). Dept. of Naval Architecture and Marine Engineering
1999-12-01
An inverse design problem is solved to determine the shape of complex coolant flow passages in internal cooled turbine blades by using the conjugate gradient method (CGM). One of the advantages of using CGM lies in that it can easily handle problems having a huge number of unknown parameters and it converges very fast. The boundary element method (BEM) is used to calculate the direct, sensitivity and adjoint problems due to its characteristics of easily-handling the problem considered here. Results obtained by using the CGM to solve the inverse problems are verified based on the numerical experiments in the analysis model. One concludes that the CGM is applied successfully in estimating the arbitrary shape of cavities and the rate of convergence is also very fast even when the number of unknown parameters is large. Moreover, the design model of the inverse problem is also performed to estimate the optimal shape of cooling passages in accordance with the desired blade surface temperature distributions. (author)
Analysis of forward and inverse problems in chemical dynamics and spectroscopy
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Rabitz, H. [Princeton Univ., NJ (United States)
1993-12-01
The overall scope of this research concerns the development and application of forward and inverse analysis tools for problems in chemical dynamics and chemical kinetics. The chemical dynamics work is specifically associated with relating features in potential surfaces and resultant dynamical behavior. The analogous inverse research aims to provide stable algorithms for extracting potential surfaces from laboratory data. In the case of chemical kinetics, the focus is on the development of systematic means to reduce the complexity of chemical kinetic models. Recent progress in these directions is summarized below.
Fedele, Micaela; Vernia, Cecilia
2017-10-01
In this paper we solve the inverse problem for the Curie-Weiss model and its multispecies version when multiple thermodynamic states are present as in the low temperature phase where the phase space is clustered. The inverse problem consists of reconstructing the model parameters starting from configuration data generated according to the distribution of the model. We demonstrate that, without taking into account the presence of many states, the application of the inversion procedure produces very poor inference results. To overcome this problem, we use the clustering algorithm. When the system has two symmetric states of positive and negative magnetizations, the parameter reconstruction can also be obtained with smaller computational effort simply by flipping the sign of the magnetizations from positive to negative (or vice versa). The parameter reconstruction fails when the system undergoes a phase transition: In that case we give the correct inversion formulas for the Curie-Weiss model and we show that they can be used to measure how close the system gets to being critical.
From capture to simulation: connecting forward and inverse problems in fluids
Gregson, James
2014-07-27
We explore the connection between fluid capture, simulation and proximal methods, a class of algorithms commonly used for inverse problems in image processing and computer vision. Our key finding is that the proximal operator constraining fluid velocities to be divergence-free is directly equivalent to the pressure-projection methods commonly used in incompressible flow solvers. This observation lets us treat the inverse problem of fluid tracking as a constrained flow problem all while working in an efficient, modular framework. In addition it lets us tightly couple fluid simulation into flow tracking, providing a global prior that significantly increases tracking accuracy and temporal coherence as compared to previous techniques. We demonstrate how we can use these improved results for a variety of applications, such as re-simulation, detail enhancement, and domain modification. We furthermore give an outlook of the applications beyond fluid tracking that our proximal operator framework could enable by exploring the connection of deblurring and fluid guiding.
An investigation on the solutions for the linear inverse problem in gamma ray tomography
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Araujo, Bruna G.M., E-mail: brunanau@hotmail.co [Universidade Federal de Pernambuco (UFPE), Recife, PE (Brazil). Dept. de Fisica; Dantas, Carlos C., E-mail: ccd@ufpe.b [Universidade Federal de Pernambuco (UFPE), Recife, PE (Brazil). Dept. de Energia Nuclear; Santos, Valdemir A. dos, E-mail: vas@unicap.b [Universidade Catolica de Pernambuco, Recife, PE (Brazil). Dept. de Quimica; Finkler, Christine L.L. [Universidade Federal de Pernambuco (UFPE), Vitoria de Santo Antao, PE (Brazil). Centro Academico de Vitoria; Oliveira, Eric F. de; Melo, Silvio B.; Santos, M. Graca dos, E-mail: sbm@cin.ufpe.b [Universidade Federal de Pernambuco (UFPE), Recife, PE (Brazil). Centro de Informatica
2009-07-01
This paper the results obtained in single beam gamma ray tomography are investigated according to direct problem formulation and the applied solution for the linear system of equations. By image reconstruction based algebraic computational algorithms are used. The sparse under and over-determined linear system of equations was analyzed. Build in functions of Matlab software were applied and optimal solutions were investigate. Experimentally a section of the tube is scanned from various positions and at different angles. The solution, to find the vector of coefficients mu, from the vector of measured p values through the W matrix inversion, constitutes an inverse problem. A industrial tomography process requires a numerical solution of the system of equations. The definition of inverse problem according to Hadmard's is considered and as well the requirement of a well posed problem to find stable solutions. The formulation of the basis function and the computational algorithm to structure the weight matrix W were analyzed. For W full rank matrix the obtained solution is unique as expected. Total Least Squares was implemented which theory and computation algorithm gives adequate treatment for the problems due to non-unique solutions of the system of equations. Stability of the solution was investigating by means of a regularization technique and the comparison shows that it improves the results. An optimal solution as a function of the image quality, computation time and minimum residuals were quantified. The corresponding reconstructed images are shown in 3D graphics in order to compare with the solution. (author)
Regularization and Bayesian methods for inverse problems in signal and image processing
Giovannelli , Jean-François
2015-01-01
The focus of this book is on "ill-posed inverse problems". These problems cannot be solved only on the basis of observed data. The building of solutions involves the recognition of other pieces of a priori information. These solutions are then specific to the pieces of information taken into account. Clarifying and taking these pieces of information into account is necessary for grasping the domain of validity and the field of application for the solutions built. For too long, the interest in these problems has remained very limited in the signal-image community. However, the community has si
Investigation of one inverse problem in case of modeling water areas with "liquid" boundaries
Sheloput, Tatiana; Agoshkov, Valery
2015-04-01
In hydrodynamics often appears the problem of modeling water areas (oceans, seas, rivers, etc.) with "liquid" boundaries. "Liquid" boundary means set of those parts of boundary where impermeability condition is broken (for example, straits, bays borders, estuaries, interfaces of oceans). Frequently such effects are ignored: for "liquid" boundaries the same conditions are used as for "solid" ones, "material boundary" approximation is applied [1]. Sometimes it is possible to interpolate the results received from models of bigger areas. Moreover, approximate estimates for boundary conditions are often used. However, those approximations are not always valid. Sometimes errors in boundary condition determination could lead to a significant decrease in the accuracy of the simulation results. In this work one way of considering the problem mentioned above is described. According to this way one inverse problem on reconstruction of boundary function in convection-reaction-diffusion equations which describe transfer of heat and salinity is solved. The work is based on theory of adjoint equations [2] and optimal control, as well as on common methodology of investigation inverse problems [3]. The work contains theoretical investigation and the results of computer simulation applied for the Baltic Sea. Moreover, conditions and restrictions that should be satisfied for solvability of the problem are entered and justified in the work. Submitted work could be applied for the solution of more complicated inverse problems and data assimilation problems in the areas with "liquid" boundaries; also it is a step for developing algorithms on computing level, speed, temperature and salinity that could be applied for real objects. References 1. A. E. Gill. Atmosphere-ocean dynamics. // London: Academic Press, 1982. 2. G. I. Marchuk. Adjoint equations. // Moscow: INM RAS, 2000, 175 p. (in Russian). 3. V.I. Agoshkov. The methods of optimal control and adjoint equations in problems of
Inverse problem for a nonlinear partial differential equation of the eighth order
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Tursun K. Yuldashev
2015-03-01
Full Text Available We study the questions of solvability of the inverse problem for a nonlinear partial differential equation of the eighth order, left-hand side of which is the superposition of pseudoparabolic and pseudohyperbolic operators of the fourth order. The applicability of the Fourier method of separation of variables is proved in study of mixed and inverse problems for a nonlinear partial differential equation of the eighth order. Using the method of separation of variables, the mixed problem is reduced to the study of the countable system of nonlinear Volterra integral equations of the second kind. Use the given additional conditions led us to study of nonlinear Volterra integral equation of the first kind with respect to the second unknown function (with respect to restore function. With the help of nonclassical integral transform the one-value restore of the second unknown function is reduced to study of the unique solvability of nonlinear Volterra integral equation of the second kind. As a result is obtained a system of two nonlinear Volterra integral equations of the second kind with respect to two unknown functions. This system is one-value solved by the method of successive approximations. Further the stability of solutions of the mixed and inverse problems is studied with respect to initial value and additional given functions.
Gauthier, P.-A.; Camier, C.; Pasco, Y.; Berry, A.; Chambatte, E.; Lapointe, R.; Delalay, M.-A.
2011-11-01
For sound field reproduction using multichannel spatial sound systems such as Wave Field Synthesis and Ambisonics, sound field extrapolation is a useful tool for the measurement, description and characterization of a sound environment to be reproduced in a listening area. In this paper, the inverse problem theory is adapted to sound field extrapolation around a microphone array for further spatial sound and sound environment reproduction. A general review of inverse problem theory and analysis tools is given and used for the comparative evaluation of various microphone array configurations. Classical direct regularization methods such as truncated singular value decomposition and Tikhonov regularization are recalled. On the basis of the reviewed background, a new regularization method adapted to the problem at hand is introduced. This method involves the use of an a priori beamforming measurement to define a data-dependent discrete smoothing norm for the regularization of the inverse problem. This method which represents the main contribution of this paper shows promising results and opens new research avenues.
Osman, Arafa Mohamed
1987-05-01
The inverse heat transfer problem is one of considerable practical interest in the analysis and design of experimental heat transfer investigations. The analytical and experimental investigation of the inverse heat transfer coefficients in multi-dimensional convective heat transfer applications is examined. An application considered is the sudden quenching of a hot solid in a cold liquid. Other applications include thermal analysis of forced convection over impulsively started solid bodies and investigation of short duration wind tunnel experiments. The primary aim is to describe methods and algorithms for the solution of the ill-posed inverse heat transfer coefficient problem. The solution method used is an extension of the sequential future-information method of Beck. Numerical experiments are conducted for a systematic investigation of the developed algorithms on selected heat transfer coefficient test cases. The overall objective of the experimental work is to investigate the early transients in the heat transfer coefficients from spheres in one- and two-dimensional quenching experiments. Several experiments were performed by plunging hollow spheres in either ethylene glycol or water. The developed methods are used for the analysis of the quenching experiments for the estimation of the transient heat transfer coefficients. Analysis of the results indicate that the transient inverse technique has the capability of estimating early transients and subsequent quasi-steady state values of the heat transfer coefficients in a single transient experiment.
Variational approach to direct and inverse problems of atmospheric pollution studies
Penenko, Vladimir; Tsvetova, Elena; Penenko, Alexey
2016-04-01
We present the development of a variational approach for solving interrelated problems of atmospheric hydrodynamics and chemistry concerning air pollution transport and transformations. The proposed approach allows us to carry out complex studies of different-scale physical and chemical processes using the methods of direct and inverse modeling [1-3]. We formulate the problems of risk/vulnerability and uncertainty assessment, sensitivity studies, variational data assimilation procedures [4], etc. A computational technology of constructing consistent mathematical models and methods of their numerical implementation is based on the variational principle in the weak constraint formulation specifically designed to account for uncertainties in models and observations. Algorithms for direct and inverse modeling are designed with the use of global and local adjoint problems. Implementing the idea of adjoint integrating factors provides unconditionally monotone and stable discrete-analytic approximations for convection-diffusion-reaction problems [5,6]. The general framework is applied to the direct and inverse problems for the models of transport and transformation of pollutants in Siberian and Arctic regions. The work has been partially supported by the RFBR grant 14-01-00125 and RAS Presidium Program I.33P. References: 1. V. Penenko, A.Baklanov, E. Tsvetova and A. Mahura . Direct and inverse problems in a variational concept of environmental modeling //Pure and Applied Geoph.(2012) v.169: 447-465. 2. V. V. Penenko, E. A. Tsvetova, and A. V. Penenko Development of variational approach for direct and inverse problems of atmospheric hydrodynamics and chemistry, Izvestiya, Atmospheric and Oceanic Physics, 2015, Vol. 51, No. 3, p. 311-319, DOI: 10.1134/S0001433815030093. 3. V.V. Penenko, E.A. Tsvetova, A.V. Penenko. Methods based on the joint use of models and observational data in the framework of variational approach to forecasting weather and atmospheric composition
Methods and Algorithms for Solving Inverse Problems for Fractional Advection-Dispersion Equations
Aldoghaither, Abeer
2015-11-12
Fractional calculus has been introduced as an e cient tool for modeling physical phenomena, thanks to its memory and hereditary properties. For example, fractional models have been successfully used to describe anomalous di↵usion processes such as contaminant transport in soil, oil flow in porous media, and groundwater flow. These models capture important features of particle transport such as particles with velocity variations and long-rest periods. Mathematical modeling of physical phenomena requires the identification of pa- rameters and variables from available measurements. This is referred to as an inverse problem. In this work, we are interested in studying theoretically and numerically inverse problems for space Fractional Advection-Dispersion Equation (FADE), which is used to model solute transport in porous media. Identifying parameters for such an equa- tion is important to understand how chemical or biological contaminants are trans- ported throughout surface aquifer systems. For instance, an estimate of the di↵eren- tiation order in groundwater contaminant transport model can provide information about soil properties, such as the heterogeneity of the medium. Our main contribution is to propose a novel e cient algorithm based on modulat-ing functions to estimate the coe cients and the di↵erentiation order for space FADE, which can be extended to general fractional Partial Di↵erential Equation (PDE). We also show how the method can be applied to the source inverse problem. This work is divided into two parts: In part I, the proposed method is described and studied through an extensive numerical analysis. The local convergence of the proposed two-stage algorithm is proven for 1D space FADE. The properties of this method are studied along with its limitations. Then, the algorithm is generalized to the 2D FADE. In part II, we analyze direct and inverse source problems for a space FADE. The problem consists of recovering the source term using final
Learning the solution sparsity of an ill-posed linear inverse problem with the Variational Garrote
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Andersen, Michael Riis; Hansen, Sofie Therese; Hansen, Lars Kai
2013-01-01
The Variational Garrote is a promising new approach for sparse solutions of ill-posed linear inverse problems (Kappen and Gomez, 2012). We reformulate the prior of the Variational Garrote to follow a simple Binomial law and assign a Beta hyper-prior on the parameter. With the new prior the Variat......The Variational Garrote is a promising new approach for sparse solutions of ill-posed linear inverse problems (Kappen and Gomez, 2012). We reformulate the prior of the Variational Garrote to follow a simple Binomial law and assign a Beta hyper-prior on the parameter. With the new prior...... the Variational Garrote, we show, has a wide range of parameter values for which it at the same time provides low test error and high retrieval of the true feature locations. Furthermore, the new form of the prior and associated hyper-prior leads to a simple update rule in a Bayesian variational inference scheme...
Dynamic Inverse Problem Solution Using a Kalman Filter Smoother for Neuronal Activity Estimation
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Eduardo Giraldo-Suárez
2011-12-01
Full Text Available This article presents an estimation method of neuronal activity into the brain using a Kalman smoother approach that takes into account in the solution of the inverse problem the dynamic variability of the time series. This method is applied over a realistic head model calculated with the boundary element method. A comparative analysis for the dynamic estimation methods is made up from simulated EEG signals for several noise conditions. The solution of the inverse problem is achieved by using high performance computing techniques and an evaluation of the computational cost is performed for each method. As a result, the Kalman smoother approach presents better performance in the estimation task than the regularized static solution, and the direct Kalman filter.
Reinke, Charles M; De la Mata Luque, Teofilo M; Su, Mehmet F; Sinclair, Michael B; El-Kady, Ihab
2011-06-01
The problem of designing electromagnetic metamaterials is complicated by the pseudo-infinite parameter space governing such materials. We present a general solution based on group theory for the design and optimization of the electromagnetic properties of metamaterials. Using this framework, the fundamental properties of a metamaterial design, such as anisotropy or magnetic or electrical resonances, can be elucidated based on the symmetry class into which the unit cell falls. This provides a methodology for the inverse problem of design of the electromagnetic properties of a metamaterial. We also present simulations of a zia metamaterial that provides greater design flexibility for tuning the resonant properties of the device than a structure based on a simple split-ring resonator. The power of this zia element is demonstrated by creating bianisotropic, chiral, and biaxial designs using the inverse group-theory procedure outlined in this paper.
Features of inverse problem arise from structure of a general pure Mueller matrix
Savenkov, Sergey N.; Oberemok, Yevgen A.; Nikonov, Vladimir N.
2009-08-01
Changes in the state of polarization of a beam of radiation occurring without depolarization can be described by means of a pure Mueller matrix. Pure Mueller matrix can be expressed in terms of the elements of a 2x2 Jones matrix. This results in that the pure Mueller matrix has a simple and elegant structure, which is embodied by interrelations between matrix elements. All possible interrelations for the elements of a general pure Mueller matrix are derived by Hovenier (Appl. Opt., Vol.33, No.36, pp. 8318-8324, 1994). The structure of the pure Mueller matrix enables to solve the inverse problem basing not on all sixteen matrix elements but only on certain part of them. We show that four elements which are formed each of columns and rows of the pure Mueller matrix considering them individually are dependent and the inverse problem can be solved in general case basing only on the rest of twelve matrix elements.
Inverse problem of life cycle assessment (LCA: its application in designing for environment (DfE
Directory of Open Access Journals (Sweden)
Rybaczewska-Błażejowska Magdalena
2016-12-01
Full Text Available The inverse problem of life cycle assessment, used in designing for environment, is about determining the optimal values of environmental inputs that provide the required environmental impacts. The notion of the inverse problem of life cycle assessment is explained here using a case study of a coffee machine (abstract model SimaPro, based on models Sima and Pro described in SimaPro 8.1 software. The dependencies between input and output signals were defined by nonlinear functions of several variables. Next, linearization was used and coefficient aki was calculated. On the basis of 3 hypothetical experiments, recommendations have been made on the reduction of the value of the factors that are the most detrimental for the environment: the consumption of aluminium, electricity, and paper for coffee filters, for the analysed product. The results prove the high applicability and usefulness of the proposed approach during environmental evaluation and enhancement of products over the full product life cycle.
An inverse radiation problem of estimating heat-transfer coefficient in participating media
Energy Technology Data Exchange (ETDEWEB)
Park, H.M.; Lee, W.J. [Sogang University, Seoul (Republic of Korea). Dept. of Chemical Engineering
2002-06-01
In the radiant cooler, where the hot gas from the pulverized coal gasifier or combustor is cooled to generate steam, the wall heat-transfer coefficient varies due to ash deposition. The authors investigated an inverse radiation problem of estimating the heat-transfer coefficient from temperature measurement in the radiant cooler. The inverse radiation problem is solved through the minimization of a performance function, which is expressed by the sum of square residuals between calculated and observed temperature, utilizing the conjugate gradient method. The gradient of the performance function is evaluated by means of the improved adjoint variable method, which resolves the difficulty associated with the singularity of the adjoint equation through its inherent regularization property. The effects of the number of measurement points and measurement noise on the accuracy of estimation are also investigated.
Directory of Open Access Journals (Sweden)
В С Корнилов
2016-12-01
Full Text Available The article presents scientific and methodical aspects of forming the content of education inverse problems for differential equations for students of higher educational institutions of physical, mathematical and natural science training areas. The goals are formulated and the principles of training are the content of learning inverse problems for differential equations. Attention is drawn to the particular issues of teaching courses inverse problems. Describes the classification criteria and target modules that play the role of tools to create and analyze the model and curriculum, forming learning content inverse problems for differential equations. The content classification features and target modules. Formulate conclusions that learning the inverse problems for differential equations has scientific, educational and humanitarian potential of students and as a result of this training they gain the fundamental knowledge in the applied and computational mathematics, and also develop scientific worldview, applied, environmental, information thinking.
A uniqueness result for an inverse problem in a space-time fractional diffusion equation
Directory of Open Access Journals (Sweden)
Salih Tatar
2013-11-01
Full Text Available Fractional (nonlocal diffusion equations replace the integer-order derivatives in space and time by fractional-order derivatives. This article considers a nonlocal inverse problem and shows that the exponents of the fractional time and space derivatives are determined uniquely by the data $u(t, 0= g(t,\\; 0 < t < T$. The uniqueness result is a theoretical background for determining experimentally the order of many anomalous diffusion phenomena, which are important in physics and in environmental engineering.
Inverse spectral problem for a non-uniform rod with multiple cracks
Shifrin, E. I.
2017-11-01
An inverse spectral problem for a rod of variable cross-section containing a finite number of transverse cracks is considered. The cracks are simulated by translational springs. It is proved that the number of springs, their locations and flexibilities are uniquely reconstructed by two spectra corresponding to longitudinally vibrating rod with free-free and free-fixed end conditions. A constructive procedure for reconstructing unknown damage parameters is developed. Numerical examples are considered.
Energy Technology Data Exchange (ETDEWEB)
Ando, J.; Matsumoto, D.; Maita, S.; Nakatake, K. [Kyushu University, Fukuoka (Japan). Faculty of Engineering
1997-10-01
This paper describes one method for solving an inverse problem of wing type based on the source and quasi continuous vortex lattice method (SQCM) in designing marine propellers and underwater wings. With the SQCM, vortices and control points are distributed on wing camber according to the QCM, and wing surface is divided into certain number of panels. This is the method to decide vortex intensity and blow-out intensity simultaneously from the condition that vertical speed on the camber and the wing surface is zero, upon having distributed blow-out with certain intensity inside the panel. The method solves the inverse problem with the following process: specific point distribution is so determined that the targeted velocity on the wing surface is satisfied when wing surface pressure distribution and uniform flow velocity are given; and then the panels are so rearranged as in parallel with direction of the flow on the surface of the wing calculated by using these specific points to derive the targeted wing shape. This paper describes the problem solving procedure in great detail. It also introduces examples of numerical calculations. It shows one method for solving the inverse problem in wing type using the SQCM as a simple panel method, whereas its good convergence and stability were verified. Considerations on effects of free surface and expansion of the method into three-dimensional problems will be implemented in the future. 11 refs., 8 figs.
Goncharsky, Alexander V.; Romanov, Sergey Y.
2017-02-01
We develop efficient iterative methods for solving inverse problems of wave tomography in models incorporating both diffraction effects and attenuation. In the inverse problem the aim is to reconstruct the velocity structure and the function that characterizes the distribution of attenuation properties in the object studied. We prove mathematically and rigorously the differentiability of the residual functional in normed spaces, and derive the corresponding formula for the Fréchet derivative. The computation of the Fréchet derivative includes solving both the direct problem with the Neumann boundary condition and the reversed-time conjugate problem. We develop efficient methods for numerical computations where the approximate solution is found using the detector measurements of the wave field and its normal derivative. The wave field derivative values at detector locations are found by solving the exterior boundary value problem with the Dirichlet boundary conditions. We illustrate the efficiency of this approach by applying it to model problems. The algorithms developed are highly parallelizable and designed to be run on supercomputers. Among the most promising medical applications of our results is the development of ultrasonic tomographs for differential diagnosis of breast cancer.
Hansen, T. M.; Cordua, K. S.
2017-12-01
Probabilistically formulated inverse problems can be solved using Monte Carlo-based sampling methods. In principle, both advanced prior information, based on for example, complex geostatistical models and non-linear forward models can be considered using such methods. However, Monte Carlo methods may be associated with huge computational costs that, in practice, limit their application. This is not least due to the computational requirements related to solving the forward problem, where the physical forward response of some earth model has to be evaluated. Here, it is suggested to replace a numerical complex evaluation of the forward problem, with a trained neural network that can be evaluated very fast. This will introduce a modeling error that is quantified probabilistically such that it can be accounted for during inversion. This allows a very fast and efficient Monte Carlo sampling of the solution to an inverse problem. We demonstrate the methodology for first arrival traveltime inversion of crosshole ground penetrating radar data. An accurate forward model, based on 2-D full-waveform modeling followed by automatic traveltime picking, is replaced by a fast neural network. This provides a sampling algorithm three orders of magnitude faster than using the accurate and computationally expensive forward model, and also considerably faster and more accurate (i.e. with better resolution), than commonly used approximate forward models. The methodology has the potential to dramatically change the complexity of non-linear and non-Gaussian inverse problems that have to be solved using Monte Carlo sampling techniques.
Solving ill-posed inverse problems using iterative deep neural networks
Adler, Jonas; Öktem, Ozan
2017-12-01
We propose a partially learned approach for the solution of ill-posed inverse problems with not necessarily linear forward operators. The method builds on ideas from classical regularisation theory and recent advances in deep learning to perform learning while making use of prior information about the inverse problem encoded in the forward operator, noise model and a regularising functional. The method results in a gradient-like iterative scheme, where the ‘gradient’ component is learned using a convolutional network that includes the gradients of the data discrepancy and regulariser as input in each iteration. We present results of such a partially learned gradient scheme on a non-linear tomographic inversion problem with simulated data from both the Sheep-Logan phantom as well as a head CT. The outcome is compared against filtered backprojection and total variation reconstruction and the proposed method provides a 5.4 dB PSNR improvement over the total variation reconstruction while being significantly faster, giving reconstructions of 512 × 512 pixel images in about 0.4 s using a single graphics processing unit (GPU).
Petersen, Isaac T; Lindhiem, Oliver; LeBeau, Brandon; Bates, John E; Pettit, Gregory S; Lansford, Jennifer E; Dodge, Kenneth A
2017-11-20
Manifestations of internalizing problems, such as specific symptoms of anxiety and depression, can change across development, even if individuals show strong continuity in rank-order levels of internalizing problems. This illustrates the concept of heterotypic continuity, and raises the question of whether common measures might be construct-valid for one age but not another. This study examines mean-level changes in internalizing problems across a long span of development at the same time as accounting for heterotypic continuity by using age-appropriate, changing measures. Internalizing problems from age 14-24 were studied longitudinally in a community sample (N = 585), using Achenbach's Youth Self-Report (YSR) and Young Adult Self-Report (YASR). Heterotypic continuity was evaluated with an item response theory (IRT) approach to vertical scaling, linking different measures over time to be on the same scale, as well as with a Thurstone scaling approach. With vertical scaling, internalizing problems peaked in mid-to-late adolescence and showed a group-level decrease from adolescence to early adulthood, a change that would not have been seen with the approach of using only age-common items. Individuals' trajectories were sometimes different than would have been seen with the common-items approach. Findings support the importance of considering heterotypic continuity when examining development and vertical scaling to account for heterotypic continuity with changing measures. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Definition of the form of coal spontaneous combustion source as the inverse problem of geoelectrics
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Sirota Dmitry
2017-01-01
Full Text Available The paper reviews the method of determining the shape and size of the coal self-heating source on coal pit benches and in coal piles during mining of coal by the open method. The method is based on the regularity found in the 1970s of the previous century and related to the distribution of potential of the natural electrical field arising from the temperature in the vicinity of the center of self-heating. The problem is reduced to the solution of inverse ill-posed problem of mathematical physics. The study presents the developed algorithm of its solution and the results of numerical simulation.
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S.N. Nnamchi
2010-01-01
Full Text Available Determination of the thermal conductivity and the specific heat capacity of neem seeds (Azadirachta indica A. Juss usingthe inverse method is the main subject of this work. One-dimensional formulation of heat conduction problem in a spherewas used. Finite difference method was adopted for the solution of the heat conduction problem. The thermal conductivityand the specific heat capacity were determined by least square method in conjunction with Levenberg-Marquardt algorithm.The results obtained compare favourably with those obtained experimentally. These results are useful in the analysis ofneem seeds drying and leaching processes.
Metropolis-Hastings Algorithms in Function Space for Bayesian Inverse Problems
Ernst, Oliver
2015-01-07
We consider Markov Chain Monte Carlo methods adapted to a Hilbert space setting. Such algorithms occur in Bayesian inverse problems where the solution is a probability measure on a function space according to which one would like to integrate or sample. We focus on Metropolis-Hastings algorithms and, in particular, we introduce and analyze a generalization of the existing pCN-proposal. This new proposal allows to exploit the geometry or anisotropy of the target measure which in turn might improve the statistical efficiency of the corresponding MCMC method. Numerical experiments for a real-world problem confirm the improvement.
Solutions of a Quadratic Inverse Eigenvalue Problem for Damped Gyroscopic Second-Order Systems
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Hong-Xiu Zhong
2014-01-01
Full Text Available Given k pairs of complex numbers and vectors (closed under conjugation, we consider the inverse quadratic eigenvalue problem of constructing n×n real matrices M, D, G, and K, where M>0, K and D are symmetric, and G is skew-symmetric, so that the quadratic pencil Q(λ=λ2M+λ(D+G+K has the given k pairs as eigenpairs. First, we construct a general solution to this problem with k≤n. Then, with the special properties D=0 and K<0, we construct a particular solution. Numerical results illustrate these solutions.
Energy Technology Data Exchange (ETDEWEB)
Tito, Mariella Janette Berrocal
2001-01-01
The analysis of inverse problems in participating media where emission, absorption and scattering take place has several relevant applications in engineering and medicine. Some of the techniques developed for the solution of inverse problems have as a first step the solution of the direct problem. In this work the discrete ordinates method has been used for the solution of the linearized Boltzmann equation in two dimensional cartesian geometry. The Levenberg - Marquardt method has been used for the solution of the inverse problem of internal source and absorption and scattering coefficient estimation. (author)
On parameterization of the inverse problem for estimating aquifer properties using tracer data
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Kowalsky, M. B.; Finsterle, Stefan A.; Williams, Kenneth H.; Murray, Christopher J.; Commer, Michael; Newcomer, Darrell R.; Englert, Andreas L.; Steefel, Carl I.; Hubbard, Susan
2012-06-11
We consider a field-scale tracer experiment conducted in 2007 in a shallow uranium-contaminated aquifer at Rifle, Colorado. In developing a reliable approach for inferring hydrological properties at the site through inverse modeling of the tracer data, decisions made on how to parameterize heterogeneity (i.e., how to represent a heterogeneous distribution using a limited number of parameters that are amenable to estimation) are of paramount importance. We present an approach for hydrological inversion of the tracer data and explore, using a 2D synthetic example at first, how parameterization affects the solution, and how additional characterization data could be incorporated to reduce uncertainty. Specifically, we examine sensitivity of the results to the configuration of pilot points used in a geostatistical parameterization, and to the sampling frequency and measurement error of the concentration data. A reliable solution of the inverse problem is found when the pilot point configuration is carefully implemented. In addition, we examine the use of a zonation parameterization, in which the geometry of the geological facies is known (e.g., from geophysical data or core data), to reduce the non-uniqueness of the solution and the number of unknown parameters to be estimated. When zonation information is only available for a limited region, special treatment in the remainder of the model is necessary, such as using a geostatistical parameterization. Finally, inversion of the actual field data is performed using 2D and 3D models, and results are compared with slug test data.
Avdyushev, Victor A.
2017-12-01
Orbit determination from a small sample of observations over a very short observed orbital arc is a strongly nonlinear inverse problem. In such problems an evaluation of orbital uncertainty due to random observation errors is greatly complicated, since linear estimations conventionally used are no longer acceptable for describing the uncertainty even as a rough approximation. Nevertheless, if an inverse problem is weakly intrinsically nonlinear, then one can resort to the so-called method of disturbed observations (aka observational Monte Carlo). Previously, we showed that the weaker the intrinsic nonlinearity, the more efficient the method, i.e. the more accurate it enables one to simulate stochastically the orbital uncertainty, while it is strictly exact only when the problem is intrinsically linear. However, as we ascertained experimentally, its efficiency was found to be higher than that of other stochastic methods widely applied in practice. In the present paper we investigate the intrinsic nonlinearity in complicated inverse problems of Celestial Mechanics when orbits are determined from little informative samples of observations, which typically occurs for recently discovered asteroids. To inquire into the question, we introduce an index of intrinsic nonlinearity. In asteroid problems it evinces that the intrinsic nonlinearity can be strong enough to affect appreciably probabilistic estimates, especially at the very short observed orbital arcs that the asteroids travel on for about a hundredth of their orbital periods and less. As it is known from regression analysis, the source of intrinsic nonlinearity is the nonflatness of the estimation subspace specified by a dynamical model in the observation space. Our numerical results indicate that when determining asteroid orbits it is actually very slight. However, in the parametric space the effect of intrinsic nonlinearity is exaggerated mainly by the ill-conditioning of the inverse problem. Even so, as for the
Avdyushev, Victor A.
2017-10-01
Orbit determination from a small sample of observations over a very short observed orbital arc is a strongly nonlinear inverse problem. In such problems an evaluation of orbital uncertainty due to random observation errors is greatly complicated, since linear estimations conventionally used are no longer acceptable for describing the uncertainty even as a rough approximation. Nevertheless, if an inverse problem is weakly intrinsically nonlinear, then one can resort to the so-called method of disturbed observations (aka observational Monte Carlo). Previously, we showed that the weaker the intrinsic nonlinearity, the more efficient the method, i.e. the more accurate it enables one to simulate stochastically the orbital uncertainty, while it is strictly exact only when the problem is intrinsically linear. However, as we ascertained experimentally, its efficiency was found to be higher than that of other stochastic methods widely applied in practice. In the present paper we investigate the intrinsic nonlinearity in complicated inverse problems of Celestial Mechanics when orbits are determined from little informative samples of observations, which typically occurs for recently discovered asteroids. To inquire into the question, we introduce an index of intrinsic nonlinearity. In asteroid problems it evinces that the intrinsic nonlinearity can be strong enough to affect appreciably probabilistic estimates, especially at the very short observed orbital arcs that the asteroids travel on for about a hundredth of their orbital periods and less. As it is known from regression analysis, the source of intrinsic nonlinearity is the nonflatness of the estimation subspace specified by a dynamical model in the observation space. Our numerical results indicate that when determining asteroid orbits it is actually very slight. However, in the parametric space the effect of intrinsic nonlinearity is exaggerated mainly by the ill-conditioning of the inverse problem. Even so, as for the
A regularizing iterative ensemble Kalman method for PDE-constrained inverse problems
Iglesias, Marco A.
2016-02-01
We introduce a derivative-free computational framework for approximating solutions to nonlinear PDE-constrained inverse problems. The general aim is to merge ideas from iterative regularization with ensemble Kalman methods from Bayesian inference to develop a derivative-free stable method easy to implement in applications where the PDE (forward) model is only accessible as a black box (e.g. with commercial software). The proposed regularizing ensemble Kalman method can be derived as an approximation of the regularizing Levenberg-Marquardt (LM) scheme (Hanke 1997 Inverse Problems 13 79-95) in which the derivative of the forward operator and its adjoint are replaced with empirical covariances from an ensemble of elements from the admissible space of solutions. The resulting ensemble method consists of an update formula that is applied to each ensemble member and that has a regularization parameter selected in a similar fashion to the one in the LM scheme. Moreover, an early termination of the scheme is proposed according to a discrepancy principle-type of criterion. The proposed method can be also viewed as a regularizing version of standard Kalman approaches which are often unstable unless ad hoc fixes, such as covariance localization, are implemented. The aim of this paper is to provide a detailed numerical investigation of the regularizing and convergence properties of the proposed regularizing ensemble Kalman scheme; the proof of these properties is an open problem. By means of numerical experiments, we investigate the conditions under which the proposed method inherits the regularizing properties of the LM scheme of (Hanke 1997 Inverse Problems 13 79-95) and is thus stable and suitable for its application in problems where the computation of the Fréchet derivative is not computationally feasible. More concretely, we study the effect of ensemble size, number of measurements, selection of initial ensemble and tunable parameters on the performance of the method
Analysis and solution of the ill-posed inverse heat conduction problem
Energy Technology Data Exchange (ETDEWEB)
Weber, C.F.
1981-01-01
The inverse conduction problem arises when experimental measurements are taken in the interior of a body, and it is desired to calculate temperature and heat flux values on the surface. The problem is shown to be ill-posed, as the solution exhibits unstable dependence on the given data functions. A special solution procedure is developed for the one-dimensional case which replaces the heat conduction equation with an approximating hyperbolic equation. If viewed from a new perspective, where the roles of the spatial and time variables are interchanged, then an initial value problem for the damped wave equation is obtained. Since this formulation is well-posed, both analytic and numerical solution procedures are readily available. Sample calculations confirm that this approach produces consistent, reliable results for both linear and nonlinear problems.
DEFF Research Database (Denmark)
Mariegaard, Jesper Sandvig
We consider a control problem for the wave equation: Given the initial state, find a specific boundary condition, called a control, that steers the system to a desired final state. The Hilbert uniqueness method (HUM) is a mathematical method for the solution of such control problems. It builds....... As an example, we employ a HUM solution to an inverse source problem for the wave equation: Given boundary measurements for a wave problem with a separable source, find the spatial part of the source term. The reconstruction formula depends on a set of HUM eigenfunction controls; we suggest a discretization...... and show its convergence. We compare results obtained by L-FEM controls and DG-FEM controls. The reconstruction formula is seen to be quite sensitive to control inaccuracies which indeed favors DG-FEM over L-FEM....
An inverse geometry problem in estimating frost growth on an evaporating tube
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Huang, C.H. [Department of Naval Architecture and Marine Engineering, National Cheng Kung University Tainan, Taiwan (Taiwan)
2002-08-01
When humid air comes into contact with a surface whose temperature is below the dew point of water vapor in air and also below the freezing point, frost deposition takes place over the surface. The phenomena of the frost growth are very complicated and therefore it is very difficult to model mathematically the behavior of frost growth and predict it. In the present study a transient inverse geometry heat conduction problem (shape identification problem) is solved using the conjugate gradient method (CGM) and boundary element method (BEM)-based inverse algorithm to estimate the unknown irregular frost thickness and shape. Results obtained by using the CGM to estimate the frost growth are justified based on the numerical experiments. It is concluded that the accurate frost shape can be estimated by the CGM except for the initial and final time. The reason and improvement of this singularity are addressed. Finally the effects of reducing the number of sensors and increasing the measurement errors on the inverse solutions are discussed. (orig.)
Electrostatic point charge fitting as an inverse problem: Revealing the underlying ill-conditioning
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Ivanov, Maxim V.; Talipov, Marat R.; Timerghazin, Qadir K., E-mail: qadir.timerghazin@marquette.edu [Department of Chemistry, Marquette University, Milwaukee, Wisconsin 53201-1881 (United States)
2015-10-07
Atom-centered point charge (PC) model of the molecular electrostatics—a major workhorse of the atomistic biomolecular simulations—is usually parameterized by least-squares (LS) fitting of the point charge values to a reference electrostatic potential, a procedure that suffers from numerical instabilities due to the ill-conditioned nature of the LS problem. To reveal the origins of this ill-conditioning, we start with a general treatment of the point charge fitting problem as an inverse problem and construct an analytical model with the point charges spherically arranged according to Lebedev quadrature which is naturally suited for the inverse electrostatic problem. This analytical model is contrasted to the atom-centered point-charge model that can be viewed as an irregular quadrature poorly suited for the problem. This analysis shows that the numerical problems of the point charge fitting are due to the decay of the curvatures corresponding to the eigenvectors of LS sum Hessian matrix. In part, this ill-conditioning is intrinsic to the problem and is related to decreasing electrostatic contribution of the higher multipole moments, that are, in the case of Lebedev grid model, directly associated with the Hessian eigenvectors. For the atom-centered model, this association breaks down beyond the first few eigenvectors related to the high-curvature monopole and dipole terms; this leads to even wider spread-out of the Hessian curvature values. Using these insights, it is possible to alleviate the ill-conditioning of the LS point-charge fitting without introducing external restraints and/or constraints. Also, as the analytical Lebedev grid PC model proposed here can reproduce multipole moments up to a given rank, it may provide a promising alternative to including explicit multipole terms in a force field.
Uncertainty Quantification for Adjoint-Based Inverse Problems with Sparse Data
Loose, Nora; Heimbach, Patrick; Nisancioglu, Kerim
2017-04-01
The adjoint method of data assimilation (DA) is used in many fields of Geosciences. It fits a dynamical model to observations in a least-squares optimization problem, leading to a solution that follows the model equations exactly. While the physical consistency of the obtained solution makes the adjoint method an attractive DA technique for many applications, one of its major drawbacks is that an accompanying uncertainty quantification is computationally challenging. In theory, the Hessian of the model-data misfit function can provide such an error estimate on the solution of the inverse problem because - under certain assumptions - it can be associated with the inverse of the error covariance matrix. In practice, however, studies that use adjoint-based DA into ocean GCMs usually don't deal with a quantification of uncertainties, mostly because an analysis of the Hessian is often intractable due to its high dimensionality. This work is motivated by the fact that an increasing number of studies apply the adjoint-based DA machinery to paleoceanographic problems - without considering accompanying uncertainties. In such applications, the number of observations can be of the order 102, while the dimension of the control space is still as high as of the order 106 to 108. An uncertainty quantification in such heavily underdetermined inverse problems seems even more crucial, an objective that we pursue here. We take advantage of the fact that in such situations the Hessian is of very low rank (while still of high dimension). This enables us to explore in great detail to what extent paleo proxy data from ocean sediment cores informs the solution of the inverse problem. We use the MIT general circulation model (MITgcm) and sample a sparse set of observations from a control simulation, corresponding to available data from ocean sediment cores. We then quantify how well the synthetic data constrains different quantities of interest, such as heat content of specific ocean
FOREWORD: 3rd International Workshop on New Computational Methods for Inverse Problems (NCMIP 2013)
Blanc-Féraud, Laure; Joubert, Pierre-Yves
2013-10-01
Conference logo This volume of Journal of Physics: Conference Series is dedicated to the scientific contributions presented during the 3rd International Workshop on New Computational Methods for Inverse Problems, NCMIP 2013 (http://www.farman.ens-cachan.fr/NCMIP_2013.html). This workshop took place at Ecole Normale Supérieure de Cachan, in Cachan, France, on 22 May 2013, at the initiative of Institut Farman. The prior editions of NCMIP also took place in Cachan, France, firstly within the scope of the ValueTools Conference, in May 2011 (http://www.ncmip.org/2011/), and secondly at the initiative of Institut Farman, in May 2012 (http://www.farman.ens-cachan.fr/NCMIP_2012.html). The NCMIP Workshop focused on recent advances in the resolution of inverse problems. Indeed inverse problems appear in numerous scientific areas such as geophysics, biological and medical imaging, material and structure characterization, electrical, mechanical and civil engineering, and finances. The resolution of inverse problems consists of estimating the parameters of the observed system or structure from data collected by an instrumental sensing or imaging device. Its success firstly requires the collection of relevant observation data. It also requires accurate models describing the physical interactions between the instrumental device and the observed system, as well as the intrinsic properties of the solution itself. Finally, it requires the design of robust, accurate and efficient inversion algorithms. Advanced sensor arrays and imaging devices provide high rate and high volume data; in this context, the efficient resolution of the inverse problem requires the joint development of new models and inversion methods, taking computational and implementation aspects into account. During this one-day workshop, researchers had the opportunity to bring to light and share new techniques and results in the field of inverse problems. The topics of the workshop were: algorithms and computational
FOREWORD: 2nd International Workshop on New Computational Methods for Inverse Problems (NCMIP 2012)
Blanc-Féraud, Laure; Joubert, Pierre-Yves
2012-09-01
Conference logo This volume of Journal of Physics: Conference Series is dedicated to the scientific contributions presented during the 2nd International Workshop on New Computational Methods for Inverse Problems, (NCMIP 2012). This workshop took place at Ecole Normale Supérieure de Cachan, in Cachan, France, on 15 May 2012, at the initiative of Institut Farman. The first edition of NCMIP also took place in Cachan, France, within the scope of the ValueTools Conference, in May 2011 (http://www.ncmip.org/2011/). The NCMIP Workshop focused on recent advances in the resolution of inverse problems. Indeed inverse problems appear in numerous scientific areas such as geophysics, biological and medical imaging, material and structure characterization, electrical, mechanical and civil engineering, and finance. The resolution of inverse problems consists of estimating the parameters of the observed system or structure from data collected by an instrumental sensing or imaging device. Its success firstly requires the collection of relevant observation data. It also requires accurate models describing the physical interactions between the instrumental device and the observed system, as well as the intrinsic properties of the solution itself. Finally, it requires the design of robust, accurate and efficient inversion algorithms. Advanced sensor arrays and imaging devices provide high rate and high volume data; in this context, the efficient resolution of the inverse problem requires the joint development of new models and inversion methods, taking computational and implementation aspects into account. During this one-day workshop, researchers had the opportunity to bring to light and share new techniques and results in the field of inverse problems. The topics of the workshop were: algorithms and computational aspects of inversion, Bayesian estimation, kernel methods, learning methods, convex optimization, free discontinuity problems, metamodels, proper orthogonal decomposition
The Solution of Two-Phase Inverse Stefan Problem Based on a Hybrid Method with Optimization
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Yang Yu
2015-01-01
Full Text Available The two-phase Stefan problem is widely used in industrial field. This paper focuses on solving the two-phase inverse Stefan problem when the interface moving is unknown, which is more realistic from the practical point of view. With the help of optimization method, the paper presents a hybrid method which combines the homotopy perturbation method with the improved Adomian decomposition method to solve this problem. Simulation experiment demonstrates the validity of this method. Optimization method plays a very important role in this paper, so we propose a modified spectral DY conjugate gradient method. And the convergence of this method is given. Simulation experiment illustrates the effectiveness of this modified spectral DY conjugate gradient method.
Approximate Bayesian computation for machine learning, inverse problems and big data
Mohammad-Djafari, Ali
2017-06-01
This paper summarizes my tutorial talk in MaxEnt 2016 workshop. Starting from the basics of the Bayesian approach and simple example of low dimensional parameter estimation where almost all the computations can be done easily, we go very fast to high dimensional case. In those real world cases, even for the sample case of linear model with Gaussian prior, where the posterior law is also Gaussian, the cost of the computation of the posterior covariance becomes important and needs approximate and fast algorithms. Different approximation methods for model comparison and model selection in machine learning problems are presented in summary. Among the existing methods, we mention Laplace approximation, Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and Variational Bayesian Approximation (VBA) Methods. Finally, through two examples of inverse problems in imaging systems: X ray and Diffraction wave Computed Tomography (CT), we show how to handle the real great dimensional problems.
Inverse coefficient problem for the semi-linear fractional telegraph equation
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Halyna Lopushanska
2015-06-01
Full Text Available We establish the unique solvability for an inverse problem for semi-linear fractional telegraph equation $$ D^\\alpha_t u+r(tD^\\beta_t u-\\Delta u=F_0(x,t,u,D^\\beta_t u, \\quad (x,t \\in \\Omega_0\\times (0,T] $$ with regularized fractional derivatives $D^\\alpha_t u, D^\\beta_t u$ of orders $\\alpha\\in (1,2$, $\\beta\\in (0,1$ with respect to time on bounded cylindrical domain. This problem consists in the determination of a pair of functions: a classical solution $u$ of the first boundary-value problem for such equation, and an unknown continuous coefficient $r(t$ under the over-determination condition $$ \\int_{\\Omega_0}u(x,t\\varphi(xdx=F(t, \\quad t\\in [0,T] $$ with given functions $\\varphi$ and $F$.
Fymat, A. L.
1976-01-01
The paper studies the inversion of the radiative transfer equation describing the interaction of electromagnetic radiation with atmospheric aerosols. The interaction can be considered as the propagation in the aerosol medium of two light beams: the direct beam in the line-of-sight attenuated by absorption and scattering, and the diffuse beam arising from scattering into the viewing direction, which propagates more or less in random fashion. The latter beam has single scattering and multiple scattering contributions. In the former case and for single scattering, the problem is reducible to first-kind Fredholm equations, while for multiple scattering it is necessary to invert partial integrodifferential equations. A nonlinear minimization search method, applicable to the solution of both types of problems has been developed, and is applied here to the problem of monitoring aerosol pollution, namely the complex refractive index and size distribution of aerosol particles.
Energy Technology Data Exchange (ETDEWEB)
Tupek, Michael R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2016-06-30
In recent years there has been a proliferation of modeling techniques for forward predictions of crack propagation in brittle materials, including: phase-field/gradient damage models, peridynamics, cohesive-zone models, and G/XFEM enrichment techniques. However, progress on the corresponding inverse problems has been relatively lacking. Taking advantage of key features of existing modeling approaches, we propose a parabolic regularization of Barenblatt cohesive models which borrows extensively from previous phase-field and gradient damage formulations. An efficient explicit time integration strategy for this type of nonlocal fracture model is then proposed and justified. In addition, we present a C++ computational framework for computing in- put parameter sensitivities efficiently for explicit dynamic problems using the adjoint method. This capability allows for solving inverse problems involving crack propagation to answer interesting engineering questions such as: 1) what is the optimal design topology and material placement for a heterogeneous structure to maximize fracture resistance, 2) what loads must have been applied to a structure for it to have failed in an observed way, 3) what are the existing cracks in a structure given various experimental observations, etc. In this work, we focus on the first of these engineering questions and demonstrate a capability to automatically and efficiently compute optimal designs intended to minimize crack propagation in structures.
On an inverse source problem for enhanced oil recovery by wave motion maximization in reservoirs
Karve, Pranav M.
2014-12-28
© 2014, Springer International Publishing Switzerland. We discuss an optimization methodology for focusing wave energy to subterranean formations using strong motion actuators placed on the ground surface. The motivation stems from the desire to increase the mobility of otherwise entrapped oil. The goal is to arrive at the spatial and temporal description of surface sources that are capable of maximizing mobility in the target reservoir. The focusing problem is posed as an inverse source problem. The underlying wave propagation problems are abstracted in two spatial dimensions, and the semi-infinite extent of the physical domain is negotiated by a buffer of perfectly-matched-layers (PMLs) placed at the domain’s truncation boundary. We discuss two possible numerical implementations: Their utility for deciding the tempo-spatial characteristics of optimal wave sources is shown via numerical experiments. Overall, the simulations demonstrate the inverse source method’s ability to simultaneously optimize load locations and time signals leading to the maximization of energy delivery to a target formation.
A Hybrid Optimization Method for Solving Bayesian Inverse Problems under Uncertainty.
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Kai Zhang
Full Text Available In this paper, we investigate the application of a new method, the Finite Difference and Stochastic Gradient (Hybrid method, for history matching in reservoir models. History matching is one of the processes of solving an inverse problem by calibrating reservoir models to dynamic behaviour of the reservoir in which an objective function is formulated based on a Bayesian approach for optimization. The goal of history matching is to identify the minimum value of an objective function that expresses the misfit between the predicted and measured data of a reservoir. To address the optimization problem, we present a novel application using a combination of the stochastic gradient and finite difference methods for solving inverse problems. The optimization is constrained by a linear equation that contains the reservoir parameters. We reformulate the reservoir model's parameters and dynamic data by operating the objective function, the approximate gradient of which can guarantee convergence. At each iteration step, we obtain the relatively 'important' elements of the gradient, which are subsequently substituted by the values from the Finite Difference method through comparing the magnitude of the components of the stochastic gradient, which forms a new gradient, and we subsequently iterate with the new gradient. Through the application of the Hybrid method, we efficiently and accurately optimize the objective function. We present a number numerical simulations in this paper that show that the method is accurate and computationally efficient.
Zhang, Yang; Liu, Guoqiang; Tao, Chunjing; Wang, Hao; He, Wenjing
2009-01-01
The analysis of electromagnetic forward and inverse problems is very important in the process of image reconstruction for magnetoacoustic tomography with magnetic induction (MAT-MI). A new analysis method was introduced in this paper. It breaks through some illogical supposes that the existing methods applied and can improve the spatial resolution of the image availably. Besides it can avoid rotating the static magnetic field which is very difficult to come true in application, therefore the development of MAT-MI technique can be promoted greatly. To test the validity of the new method, two test models were analyzed, and the availability of the method was demonstrated.
Vasil'ev, V. I.; Kardashevsky, A. M.; Popov, V. V.; Prokopev, G. A.
2017-10-01
This article presents results of computational experiment carried out using a finite-difference method for solving the inverse Cauchy problem for a two-dimensional elliptic equation. The computational algorithm involves an iterative determination of the missing boundary condition from the override condition using the conjugate gradient method. The results of calculations are carried out on the examples with exact solutions as well as at specifying an additional condition with random errors are presented. Results showed a high efficiency of the iterative method of conjugate gradients for numerical solution
An Adaptive Observer-Based Algorithm for Solving Inverse Source Problem for the Wave Equation
Asiri, Sharefa M.
2015-08-31
Observers are well known in control theory. Originally designed to estimate the hidden states of dynamical systems given some measurements, the observers scope has been recently extended to the estimation of some unknowns, for systems governed by partial differential equations. In this paper, observers are used to solve inverse source problem for a one-dimensional wave equation. An adaptive observer is designed to estimate the state and source components for a fully discretized system. The effectiveness of the algorithm is emphasized in noise-free and noisy cases and an insight on the impact of measurements’ size and location is provided.
A New Concept for Atmospheric Reentry Optimal Guidance: An Inverse Problem Inspired Approach
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Davood Abbasi
2013-01-01
Full Text Available This paper presents a new concept for atmospheric reentry online optimal guidance and control using a method called MARE G&C that exploits the different time scale featured by reentry dynamics. The new technique reaches a quasi-analytical solution and simplified computations, even considering both lift-to-drag ratio and aerodynamic roll as control variables; in addition, the paper offers a solution for the challenging path constraints issue, getting inspiration from the inverse problem methodology. The final resulting algorithm seems suitable for onboard predictive guidance, a new need for future space missions.
Inverse Problem In Optical Tomography Using Diffusion Approximation and Its Hopf-Cole Transformation
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Taufiquar R. Khan
2003-12-01
Full Text Available In this paper, we derive the Hopf-Cole transformation to the diffusion approximation. We find the analytic solution to the one dimensional diffusion approximation and its Hopf-Cole transformation for a homogenous constant background medium. We demonstrate that for a homogenous constant background medium in one dimension, the Hopf-Cole transformation improves the stability of the inverse problem. We also derive a Green's function scaling of the higher dimensional diffusion approximation for an inhomogeneous background medium and discuss a two step reconstruction algorithm.
Numerical Modeling of Inverse Problems under Uncertainty for Damage Detection in Aircraft Structures
2013-08-01
Filtro de Kalman para um Problema Inverso de AFOSR/SOARD Grant FA9550-10-1-0103. Report 2010-13. PI: Dr. Ariosto B Jorge. Numerical Modeling of...Inverse Problems under Uncertainty for Damage Detection in Aircraft Structures. 15 Localização e Detecção de Dano em Problema 2-D). Type of monograph...Parameter Identification and Global Optimization Techniques (in Portuguese) (Modelagem de Problema Inverso de Detecção de Danos por Técnicas de
Alessandrini, Giovanni; de Hoop, Maarten V.; Gaburro, Romina
2017-12-01
We discuss the inverse problem of determining the, possibly anisotropic, conductivity of a body Ω\\subset{R}n when the so-called Neumann-to-Dirichlet map is locally given on a non-empty curved portion Σ of the boundary \\partialΩ . We prove that anisotropic conductivities that are a priori known to be piecewise constant matrices on a given partition of Ω with curved interfaces can be uniquely determined in the interior from the knowledge of the local Neumann-to-Dirichlet map.
Remarks on a financial inverse problem by means of Monte Carlo Methods
Cuomo, Salvatore; Di Somma, Vittorio; Sica, Federica
2017-10-01
Estimating the price of a barrier option is a typical inverse problem. In this paper we present a numerical and statistical framework for a market with risk-free interest rate and a risk asset, described by a Geometric Brownian Motion (GBM). After approximating the risk asset with a numerical method, we find the final option price by following an approach based on sequential Monte Carlo methods. All theoretical results are applied to the case of an option whose underlying is a real stock.
Energy Technology Data Exchange (ETDEWEB)
Lisin, E. A.; Lisina, I. I.; Vaulina, O. S.; Petrov, O. F. [Joint Institute for High Temperatures of the Russian Academy of Sciences, 13 bd.2 Izhorskaya St., Moscow 125412, Russia and Moscow Institute of Physics and Technology, 9 Institutskiy Per., Dolgoprudny, Moscow Region 141700 (Russian Federation)
2015-03-15
Solution of the inverse Langevin problem is presented for open dissipative systems with anisotropic interparticle interaction. Possibility of applying this solution for experimental determining the anisotropic interaction forces between dust particles in complex plasmas with ion flow is considered. For this purpose, we have tested the method on the results of numerical simulation of chain structures of particles with quasidipole-dipole interaction, similar to the one occurring due to effects of ion focusing in gas discharges. Influence of charge spatial inhomogeneity and fluctuations on the results of recovery is also discussed.
Stability estimate for a hyperbolic inverse problem with time-dependent coefficient
Ben Aïcha, Ibtissem
2015-12-01
We study the stability issue in the inverse problem of determining the time-dependent coefficient q(t,x) of order zero appearing in the wave equation, from boundary observations. In dimension n≥slant 2, we derive a log-type stability estimate with respect to the Dirichlet-to-Neumann map for the restriction of q to a suitable subset of the domain. This is provided q is known outside the above subset. Moreover, by enlarging the set of data, we prove that q can be stably retrieved in larger subsets of the domain, including the whole domain itself.
Liu, Gao-Lian
1991-01-01
Advances in inverse design and optimization theory in engineering fields in China are presented. Two original approaches, the image-space approach and the variational approach, are discussed in terms of turbomachine aerodynamic inverse design. Other areas of research in turbomachine aerodynamic inverse design include the improved mean-streamline (stream surface) method and optimization theory based on optimal control. Among the additional engineering fields discussed are the following: the inverse problem of heat conduction, free-surface flow, variational cogeneration of optimal grid and flow field, and optimal meshing theory of gears.
Wang, Yongli; Benson, Robert F.
2011-01-01
Two software applications have been produced specifically for the analysis of some million digital topside ionograms produced by a recent analog-to-digital conversion effort of selected analog telemetry tapes from the Alouette-2, ISIS-1 and ISIS-2 satellites. One, TOPIST (TOPside Ionogram Scalar with True-height algorithm) from the University of Massachusetts Lowell, is designed for the automatic identification of the topside-ionogram ionospheric-reflection traces and their inversion into vertical electron-density profiles Ne(h). TOPIST also has the capability of manual intervention. The other application, from the Goddard Space Flight Center based on the FORTRAN code of John E. Jackson from the 1960s, is designed as an IDL-based interactive program for the scaling of selected digital topside-sounder ionograms. The Jackson code has also been modified, with some effort, so as to run on modern computers. This modification was motivated by the need to scale selected ionograms from the millions of Alouette/ISIS topside-sounder ionograms that only exist on 35-mm film. During this modification, it became evident that it would be more efficient to design a new code, based on the capabilities of present-day computers, than to continue to modify the old code. Such a new code has been produced and here we will describe its capabilities and compare Ne(h) profiles produced from it with those produced by the Jackson code. The concept of the new code is to assume an initial Ne(h) and derive a final Ne(h) through an iteration process that makes the resulting apparent-height profile fir the scaled values within a certain error range. The new code can be used on the X-, O-, and Z-mode traces. It does not assume any predefined profile shape between two contiguous points, like the exponential rule used in Jackson s program. Instead, Monotone Piecewise Cubic Interpolation is applied in the global profile to keep the monotone nature of the profile, which also ensures better smoothness
Mixed-norm estimates for the M/EEG inverse problem using accelerated gradient methods
Gramfort, Alexandre; Kowalski, Matthieu; Hämäläinen, Matti
2012-04-01
Magneto- and electroencephalography (M/EEG) measure the electromagnetic fields produced by the neural electrical currents. Given a conductor model for the head, and the distribution of source currents in the brain, Maxwell's equations allow one to compute the ensuing M/EEG signals. Given the actual M/EEG measurements and the solution of this forward problem, one can localize, in space and in time, the brain regions that have produced the recorded data. However, due to the physics of the problem, the limited number of sensors compared to the number of possible source locations, and measurement noise, this inverse problem is ill-posed. Consequently, additional constraints are needed. Classical inverse solvers, often called minimum norm estimates (MNE), promote source estimates with a small ℓ2 norm. Here, we consider a more general class of priors based on mixed norms. Such norms have the ability to structure the prior in order to incorporate some additional assumptions about the sources. We refer to such solvers as mixed-norm estimates (MxNE). In the context of M/EEG, MxNE can promote spatially focal sources with smooth temporal estimates with a two-level ℓ1/ℓ2 mixed-norm, while a three-level mixed-norm can be used to promote spatially non-overlapping sources between different experimental conditions. In order to efficiently solve the optimization problems of MxNE, we introduce fast first-order iterative schemes that for the ℓ1/ℓ2 norm give solutions in a few seconds making such a prior as convenient as the simple MNE. Furthermore, thanks to the convexity of the optimization problem, we can provide optimality conditions that guarantee global convergence. The utility of the methods is demonstrated both with simulations and experimental MEG data.
Directory of Open Access Journals (Sweden)
Виктор Семенович Корнилов
2017-12-01
Full Text Available In article attention that when training in the inverse problems for differential equations at students scientific and cognitive potential develops is paid. Students realize that mathematical models of the inverse problems for differential equations find the application in economy, the industries, ecology, sociology, biology, chemistry, mathematician, physics, in researches of the processes and the phenomena occurring in water and earth’s environment, air and space.Attention of the reader that in training activity to the inverse problems for differential equations at students the scientific outlook, logical, algorithmic, information thinking, creative activity, independence and ingenuity develop is focused. Students acquire skills to apply knowledge of many physical and mathematical disciplines, to carry out the analysis of the received decision of the reverse task and to formulate logical outputs of application-oriented character. Solving the inverse problems for differential equations, students acquire new knowledge in the field of applied and calculus mathematics, informatics, natural sciences and other knowledge.
Klibanov, M V
2006-01-01
The Lipschitz stability estimate for a coefficient inverse problem for the non-stationary single-speed transport equation with the lateral boundary data is obtained. The method of Carleman estimates is used. Uniqueness of the solution follows.
Lezina, Natalya; Agoshkov, Valery
2017-04-01
Domain decomposition method (DDM) allows one to present a domain with complex geometry as a set of essentially simpler subdomains. This method is particularly applied for the hydrodynamics of oceans and seas. In each subdomain the system of thermo-hydrodynamic equations in the Boussinesq and hydrostatic approximations is solved. The problem of obtaining solution in the whole domain is that it is necessary to combine solutions in subdomains. For this purposes iterative algorithm is created and numerical experiments are conducted to investigate an effectiveness of developed algorithm using DDM. For symmetric operators in DDM, Poincare-Steklov's operators [1] are used, but for the problems of the hydrodynamics, it is not suitable. In this case for the problem, adjoint equation method [2] and inverse problem theory are used. In addition, it is possible to create algorithms for the parallel calculations using DDM on multiprocessor computer system. DDM for the model of the Baltic Sea dynamics is numerically studied. The results of numerical experiments using DDM are compared with the solution of the system of hydrodynamic equations in the whole domain. The work was supported by the Russian Science Foundation (project 14-11-00609, the formulation of the iterative process and numerical experiments). [1] V.I. Agoshkov, Domain Decompositions Methods in the Mathematical Physics Problem // Numerical processes and systems, No 8, Moscow, 1991 (in Russian). [2] V.I. Agoshkov, Optimal Control Approaches and Adjoint Equations in the Mathematical Physics Problem, Institute of Numerical Mathematics, RAS, Moscow, 2003 (in Russian).
jInv: A Modular and Scalable Framework for Electromagnetic Inverse Problems
Belliveau, P. T.; Haber, E.
2016-12-01
Inversion is a key tool in the interpretation of geophysical electromagnetic (EM) data. Three-dimensional (3D) EM inversion is very computationally expensive and practical software for inverting large 3D EM surveys must be able to take advantage of high performance computing (HPC) resources. It has traditionally been difficult to achieve those goals in a high level dynamic programming environment that allows rapid development and testing of new algorithms, which is important in a research setting. With those goals in mind, we have developed jInv, a framework for PDE constrained parameter estimation problems. jInv provides optimization and regularization routines, a framework for user defined forward problems, and interfaces to several direct and iterative solvers for sparse linear systems. The forward modeling framework provides finite volume discretizations of differential operators on rectangular tensor product meshes and tetrahedral unstructured meshes that can be used to easily construct forward modeling and sensitivity routines for forward problems described by partial differential equations. jInv is written in the emerging programming language Julia. Julia is a dynamic language targeted at the computational science community with a focus on high performance and native support for parallel programming. We have developed frequency and time-domain EM forward modeling and sensitivity routines for jInv. We will illustrate its capabilities and performance with two synthetic time-domain EM inversion examples. First, in airborne surveys, which use many sources, we achieve distributed memory parallelism by decoupling the forward and inverse meshes and performing forward modeling for each source on small, locally refined meshes. Secondly, we invert grounded source time-domain data from a gradient array style induced polarization survey using a novel time-stepping technique that allows us to compute data from different time-steps in parallel. These examples both show
Generalized Uncertainty Quantification for Linear Inverse Problems in X-ray Imaging
Energy Technology Data Exchange (ETDEWEB)
Fowler, Michael James [Clarkson Univ., Potsdam, NY (United States)
2014-04-25
In industrial and engineering applications, X-ray radiography has attained wide use as a data collection protocol for the assessment of material properties in cases where direct observation is not possible. The direct measurement of nuclear materials, particularly when they are under explosive or implosive loading, is not feasible, and radiography can serve as a useful tool for obtaining indirect measurements. In such experiments, high energy X-rays are pulsed through a scene containing material of interest, and a detector records a radiograph by measuring the radiation that is not attenuated in the scene. One approach to the analysis of these radiographs is to model the imaging system as an operator that acts upon the object being imaged to produce a radiograph. In this model, the goal is to solve an inverse problem to reconstruct the values of interest in the object, which are typically material properties such as density or areal density. The primary objective in this work is to provide quantitative solutions with uncertainty estimates for three separate applications in X-ray radiography: deconvolution, Abel inversion, and radiation spot shape reconstruction. For each problem, we introduce a new hierarchical Bayesian model for determining a posterior distribution on the unknowns and develop efficient Markov chain Monte Carlo (MCMC) methods for sampling from the posterior. A Poisson likelihood, based on a noise model for photon counts at the detector, is combined with a prior tailored to each application: an edge-localizing prior for deconvolution; a smoothing prior with non-negativity constraints for spot reconstruction; and a full covariance sampling prior based on a Wishart hyperprior for Abel inversion. After developing our methods in a general setting, we demonstrate each model on both synthetically generated datasets, including those from a well known radiation transport code, and real high energy radiographs taken at two U. S. Department of Energy
An inverse problem to the generation of pseudo-nondiffracting beams: detection of Cerenkov radiation
Miler, Miroslav; Pala, Jan
2003-11-01
Nondiffracting beams have been in the center of interest for the last decade. These beams, however, can be realized in practice only approximately. The simplest scheme for generating such a beam is to use a sufficiently narrow annular source placed in the back focal plane of a lens. Behind the lens, the beam is pseudo-nondiffracting in some length. The inverse problem is detection of Cerenkov radiation. The trace of a charged particle traveling through a dielectric medium faster than light emits this radiation under a certain angle. Generated conical wave front creates in the back focal plane of a lens a diffraction pattern in form of a ring. The contribution analyses theoretically both mentioned problems.
An Inverse Source Problem for a One-dimensional Wave Equation: An Observer-Based Approach
Asiri, Sharefa M.
2013-05-25
Observers are well known in the theory of dynamical systems. They are used to estimate the states of a system from some measurements. However, recently observers have also been developed to estimate some unknowns for systems governed by Partial differential equations. Our aim is to design an observer to solve inverse source problem for a one dimensional wave equation. Firstly, the problem is discretized in both space and time and then an adaptive observer based on partial field measurements (i.e measurements taken form the solution of the wave equation) is applied to estimate both the states and the source. We see the effectiveness of this observer in both noise-free and noisy cases. In each case, numerical simulations are provided to illustrate the effectiveness of this approach. Finally, we compare the performance of the observer approach with Tikhonov regularization approach.
Lazri, Hacene; Ogam, Erick; Amar, Boudour; Fellah, Z E A; Oduor, Andrew O; Baki, Paul
2017-11-01
A method for the identification of the mechanical moduli and density of flexible, supple thermoplastic thin films placed on elastic substrates using ultrasonic waves has been developed. The composite medium immersed in a fluid host medium (water) was excited using a 50MHz transducer operating at normal incidence in reflection mode. Inverse problems involving experimental data pertaining to elastic wave propagation in the thin films on their substrates and theoretical fluid-solid interaction models for stratified media using elasticity theory were solved. Two configurations having different interface boundary conditions (BC) were modeled, transverse slip for the sliding contact interface in the case where the thin films were placed on the substrate without bonding; a bonded interface condition. The inverse problem for the recovery of the mechanical parameters were solved for the thin films under the bonded and slip BCs. Substrates made of different elastic materials having different geometries were also evaluated and their advantages discussed. Copyright © 2017 Elsevier B.V. All rights reserved.
Prediction of the thermal conductivity of metal hydrides - The inverse problem
Energy Technology Data Exchange (ETDEWEB)
Ghafir, Mohd Fahmi Abdul; Batcha, Mohd Faizal Mohideen [Faculty of Mechanical Engineering, University Tun Hussein Onn Malaysia, 86400 Parit Raja, Johor (Malaysia); Raghavan, Vijay R. [Department of Mechanical Engineering, University Technology Petronas, Bandar Seri Iskander, 31750 Tronoh, Perak (Malaysia)
2009-08-15
With sustainability as an important and driving theme, not merely of research, but that of our existence itself, the effort in developing sustainable systems takes many directions. One of these directions is in the transport sector, particularly personal transport using hydrogen as fuel, which logically leads on to the problem of hydrogen storage. This paper deals with the prediction of the effective conductivity of beds of metal hydride for hydrogen storage. To enable modeling of the effective thermal conductivity of these systems, it is necessary to arrive at the functional dependence of the thermal conductivity of the solid hydride on its hydrogen concentration or content. This is the inverse problem in thermal conductivity of multiphase materials. Inverse methods in general are those where we start from known consequences in order to find unknown causes. Using published and known data of the effective thermal conductivity of the hydride-hydrogen assemblage, we arrive at the unknown hydride conductivity by analysis. Among the models available in the literature for determination of the effective conductivity of the bed from the properties of the constituent phases, the model of Raghavan and Martin is chosen for the analysis as it combines simplicity and physical rigor. The result is expected to be useful for predicting the thermal conductivity of hydride particles and determining the optimum heat transfer rates governing the absorption and desorption rates of hydrogen in the storage system. (author)
Al-Ma'shumah, Fathimah; Permana, Dony; Sidarto, Kuntjoro Adji
2015-12-01
Customer Lifetime Value is an important and useful concept in marketing. One of its benefits is to help a company for budgeting marketing expenditure for customer acquisition and customer retention. Many mathematical models have been introduced to calculate CLV considering the customer retention/migration classification scheme. A fairly new class of these models which will be described in this paper uses Markov Chain Models (MCM). This class of models has the major advantage for its flexibility to be modified to several different cases/classification schemes. In this model, the probabilities of customer retention and acquisition play an important role. From Pfeifer and Carraway, 2000, the final formula of CLV obtained from MCM usually contains nonlinear form of the transition probability matrix. This nonlinearity makes the inverse problem of CLV difficult to solve. This paper aims to solve this inverse problem, yielding the approximate transition probabilities for the customers, by applying metaheuristic optimization algorithm developed by Yang, 2013, Flower Pollination Algorithm. The major interpretation of obtaining the transition probabilities are to set goals for marketing teams in keeping the relative frequencies of customer acquisition and customer retention.
Pontes, P. C.; Naveira-Cotta, C. P.
2016-09-01
The theoretical analysis for the design of microreactors in biodiesel production is a complicated task due to the complex liquid-liquid flow and mass transfer processes, and the transesterification reaction that takes place within these microsystems. Thus, computational simulation is an important tool that aids in understanding the physical-chemical phenomenon and, consequently, in determining the suitable conditions that maximize the conversion of triglycerides during the biodiesel synthesis. A diffusive-convective-reactive coupled nonlinear mathematical model, that governs the mass transfer process during the transesterification reaction in parallel plates microreactors, under isothermal conditions, is here described. A hybrid numerical-analytical solution via the Generalized Integral Transform Technique (GITT) for this partial differential system is developed and the eigenfunction expansions convergence rates are extensively analyzed and illustrated. The heuristic method of Particle Swarm Optimization (PSO) is applied in the inverse analysis of the proposed direct problem, to estimate the reaction kinetics constants, which is a critical step in the design of such microsystems. The results present a good agreement with the limited experimental data in the literature, but indicate that the GITT methodology combined with the PSO approach provide a reliable computational algorithm for direct-inverse analysis in such reactive mass transfer problems.
A limited memory BFGS method for a nonlinear inverse problem in digital breast tomosynthesis
Landi, G.; Loli Piccolomini, E.; Nagy, J. G.
2017-09-01
Digital breast tomosynthesis (DBT) is an imaging technique that allows the reconstruction of a pseudo three-dimensional image of the breast from a finite number of low-dose two-dimensional projections obtained by different x-ray tube angles. An issue that is often ignored in DBT is the fact that an x-ray beam is polyenergetic, i.e. it is composed of photons with different levels of energy. The polyenergetic model requires solving a large-scale, nonlinear inverse problem, which is more expensive than the typically used simplified, linear monoenergetic model. However, the polyenergetic model is much less susceptible to beam hardening artifacts, which show up as dark streaks and cupping (i.e. background nonuniformities) in the reconstructed image. In addition, it has been shown that the polyenergetic model can be exploited to obtain additional quantitative information about the material of the object being imaged. In this paper we consider the multimaterial polyenergetic DBT model, and solve the nonlinear inverse problem with a limited memory BFGS quasi-Newton method. Regularization is enforced at each iteration using a diagonally modified approximation of the Hessian matrix, and by truncating the iterations.
Indoor detection of passive targets recast as an inverse scattering problem
Gottardi, G.; Moriyama, T.
2017-10-01
The wireless local area networks represent an alternative to custom sensors and dedicated surveillance systems for target indoor detection. The availability of the channel state information has opened the exploitation of the spatial and frequency diversity given by the orthogonal frequency division multiplexing. Such a fine-grained information can be used to solve the detection problem as an inverse scattering problem. The goal of the detection is to reconstruct the properties of the investigation domain, namely to estimate if the domain is empty or occupied by targets, starting from the measurement of the electromagnetic perturbation of the wireless channel. An innovative inversion strategy exploiting both the frequency and the spatial diversity of the channel state information is proposed. The target-dependent features are identified combining the Kruskal-Wallis test and the principal component analysis. The experimental validation points out the detection performance of the proposed method when applied to an existing wireless link of a WiFi architecture deployed in a real indoor scenario. False detection rates lower than 2 [%] have been obtained.
Convergence analysis of surrogate-based methods for Bayesian inverse problems
Yan, Liang; Zhang, Yuan-Xiang
2017-12-01
The major challenges in the Bayesian inverse problems arise from the need for repeated evaluations of the forward model, as required by Markov chain Monte Carlo (MCMC) methods for posterior sampling. Many attempts at accelerating Bayesian inference have relied on surrogates for the forward model, typically constructed through repeated forward simulations that are performed in an offline phase. Although such approaches can be quite effective at reducing computation cost, there has been little analysis of the approximation on posterior inference. In this work, we prove error bounds on the Kullback–Leibler (KL) distance between the true posterior distribution and the approximation based on surrogate models. Our rigorous error analysis show that if the forward model approximation converges at certain rate in the prior-weighted L 2 norm, then the posterior distribution generated by the approximation converges to the true posterior at least two times faster in the KL sense. The error bound on the Hellinger distance is also provided. To provide concrete examples focusing on the use of the surrogate model based methods, we present an efficient technique for constructing stochastic surrogate models to accelerate the Bayesian inference approach. The Christoffel least squares algorithms, based on generalized polynomial chaos, are used to construct a polynomial approximation of the forward solution over the support of the prior distribution. The numerical strategy and the predicted convergence rates are then demonstrated on the nonlinear inverse problems, involving the inference of parameters appearing in partial differential equations.
Kuchment, Peter
2015-05-10
© 2015, Springer Basel. In the previous paper (Kuchment and Steinhauer in Inverse Probl 28(8):084007, 2012), the authors introduced a simple procedure that allows one to detect whether and explain why internal information arising in several novel coupled physics (hybrid) imaging modalities could turn extremely unstable techniques, such as optical tomography or electrical impedance tomography, into stable, good-resolution procedures. It was shown that in all cases of interest, the Fréchet derivative of the forward mapping is a pseudo-differential operator with an explicitly computable principal symbol. If one can set up the imaging procedure in such a way that the symbol is elliptic, this would indicate that the problem was stabilized. In the cases when the symbol is not elliptic, the technique suggests how to change the procedure (e.g., by adding extra measurements) to achieve ellipticity. In this article, we consider the situation arising in acousto-optical tomography (also called ultrasound modulated optical tomography), where the internal data available involves the Green’s function, and thus depends globally on the unknown parameter(s) of the equation and its solution. It is shown that the technique of (Kuchment and Steinhauer in Inverse Probl 28(8):084007, 2012) can be successfully adopted to this situation as well. A significant part of the article is devoted to results on generic uniqueness for the linearized problem in a variety of situations, including those arising in acousto-electric and quantitative photoacoustic tomography.
Sparse deconvolution for the large-scale ill-posed inverse problem of impact force reconstruction
Qiao, Baijie; Zhang, Xingwu; Gao, Jiawei; Liu, Ruonan; Chen, Xuefeng
2017-01-01
Most previous regularization methods for solving the inverse problem of force reconstruction are to minimize the l2-norm of the desired force. However, these traditional regularization methods such as Tikhonov regularization and truncated singular value decomposition, commonly fail to solve the large-scale ill-posed inverse problem in moderate computational cost. In this paper, taking into account the sparse characteristic of impact force, the idea of sparse deconvolution is first introduced to the field of impact force reconstruction and a general sparse deconvolution model of impact force is constructed. Second, a novel impact force reconstruction method based on the primal-dual interior point method (PDIPM) is proposed to solve such a large-scale sparse deconvolution model, where minimizing the l2-norm is replaced by minimizing the l1-norm. Meanwhile, the preconditioned conjugate gradient algorithm is used to compute the search direction of PDIPM with high computational efficiency. Finally, two experiments including the small-scale or medium-scale single impact force reconstruction and the relatively large-scale consecutive impact force reconstruction are conducted on a composite wind turbine blade and a shell structure to illustrate the advantage of PDIPM. Compared with Tikhonov regularization, PDIPM is more efficient, accurate and robust whether in the single impact force reconstruction or in the consecutive impact force reconstruction.
Energy Technology Data Exchange (ETDEWEB)
Lawrence, Chris C.; Flaska, Marek; Pozzi, Sara A. [Department of Nuclear Engineering and Radiological Sciences, University of Michigan, Ann Arbor, Michigan 48109 (United States); Febbraro, Michael; Becchetti, F. D. [Department of Physics, University of Michigan, Ann Arbor, Michigan 48109 (United States)
2016-08-14
Verification of future warhead-dismantlement treaties will require detection of certain warhead attributes without the disclosure of sensitive design information, and this presents an unusual measurement challenge. Neutron spectroscopy—commonly eschewed as an ill-posed inverse problem—may hold special advantages for warhead verification by virtue of its insensitivity to certain neutron-source parameters like plutonium isotopics. In this article, we investigate the usefulness of unfolded neutron spectra obtained from organic-scintillator data for verifying a particular treaty-relevant warhead attribute: the presence of high-explosive and neutron-reflecting materials. Toward this end, several improvements on current unfolding capabilities are demonstrated: deuterated detectors are shown to have superior response-matrix condition to that of standard hydrogen-base scintintillators; a novel data-discretization scheme is proposed which removes important detector nonlinearities; and a technique is described for re-parameterizing the unfolding problem in order to constrain the parameter space of solutions sought, sidestepping the inverse problem altogether. These improvements are demonstrated with trial measurements and verified using accelerator-based time-of-flight calculation of reference spectra. Then, a demonstration is presented in which the elemental compositions of low-Z neutron-attenuating materials are estimated to within 10%. These techniques could have direct application in verifying the presence of high-explosive materials in a neutron-emitting test item, as well as other for treaty verification challenges.
An Inverse Eigenvalue Problem for a Vibrating String with Two Dirichlet Spectra
Rundell, William
2013-04-23
A classical inverse problem is "can you hear the density of a string clamped at both ends?" The mathematical model gives rise to an inverse Sturm-Liouville problem for the unknown density ñ, and it is well known that the answer is negative: the Dirichlet spectrum from the clamped end-point conditions is insufficient. There are many known ways to add additional information to gain a positive answer, and these include changing one of the boundary conditions and recomputing the spectrum or giving the energy in each eigenmode-the so-called norming constants. We make the assumption that neither of these changes are possible. Instead we will add known mass-densities to the string in a way we can prescribe and remeasure the Dirichlet spectrum. We will not be able to answer the uniqueness question in its most general form, but will give some insight to what "added masses" should be chosen and how this can lead to a reconstruction of the original string density. © 2013 Society for Industrial and Applied Mathematics.
LINPRO: Linear inverse problem library for data contaminated by statistical noise
Magierski, Piotr; Wlazłowski, Gabriel
2012-10-01
The library LINPRO which provides the solution to the linear inverse problem for data contaminated by a statistical noise is presented. The library makes use of two methods: Maximum Entropy Method and Singular Value Decomposition. As an example it has been applied to perform an analytic continuation of the imaginary time propagator obtained within the Quantum Monte Carlo method. Program summary Program title: LINPRO v1.0. Catalogue identifier: AEMT_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEMT_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland. Licensing provisions: GNU Lesser General Public Licence. No. of lines in distributed program, including test data, etc.: 110620. No. of bytes in distributed program, including test data, etc.: 3208593. Distribution format: tar.gz. Programming language: C++. Computer: LINPRO library should compile on any computing system that has C++ compiler. Operating system: Linux or Unix. Classification: 4.9, 4.12, 4.13. External routines: OPT++: An Object-Oriented Nonlinear Optimization Library [1] (included in the distribution). Nature of problem: LINPRO library solves linear inverse problems with an arbitrary kernel and arbitrary external constraints imposed on the solution. Solution method: LINPRO library implements two complementary methods: Maximum Entropy Method and SVD method. Additional comments: Tested with compilers-GNU Compiler g++, Intel Compiler icpc. Running time: Problem dependent, ranging from seconds to hours. Each of the examples takes less than a minute to run. References: [1] OPT++: An Object-Oriented Nonlinear Optimization Library, https://software.sandia.gov/opt++/.
Quasisolutions of Inverse Boundary-Value Problem of Aerodynamics for Dense Airfoil Grids
Directory of Open Access Journals (Sweden)
A.M. Elizarov
2016-12-01
Full Text Available In the process of turbomachinery development, it is of great importance to accurately design impellers and select their blade shape. One of the promising approaches to solving this problem is based on the theory of inverse boundary-value problems in aerodynamics. It helps to develop methods for profiling airfoil grids with predetermined properties in the same way as it is done for isolated airfoils. In this paper, methods have been worked out to find quasisolutions of the inverse boundary-value problem in aerodynamics for a plane airfoil grid. Two methods of quasisolution have been described. The first “`formal” method is similar, in its essence, to the method used for construction of quasisolution for an isolated airfoil. It has been shown that such quasisolutions provide satisfactory results for grids having a sufficiently large relative airfoil pitch. If pitch values are low, this method is unacceptable, because “modified” velocity distribution in some areas is significantly different from the original one in this case. For this reason, areas with significant changes in the angle of the tangent line appear in the airfoil contour and the flow region becomes multivalent. To satisfy the conditions of solvability in the case of grids having a small airfoil pitch, a new quasisolution construction method taking into account the specifics of the problem has been suggested. The desired effect has been achieved due to changes in the weighting function of the minimized functional. The comparison of the results of construction of the new quasisolution with the results obtained by the “formal” method has demonstrated that the constructed airfoils are very similar when the pitch is large. In the case of dense grids, it is clear that preference should be given to the second method, as it brings less distortion to the initial velocity distribution and, thus, allows to physically find an actual airfoil contour.
Franck, I. M.; Koutsourelakis, P. S.
2017-01-01
This paper is concerned with the numerical solution of model-based, Bayesian inverse problems. We are particularly interested in cases where the cost of each likelihood evaluation (forward-model call) is expensive and the number of unknown (latent) variables is high. This is the setting in many problems in computational physics where forward models with nonlinear PDEs are used and the parameters to be calibrated involve spatio-temporarily varying coefficients, which upon discretization give rise to a high-dimensional vector of unknowns. One of the consequences of the well-documented ill-posedness of inverse problems is the possibility of multiple solutions. While such information is contained in the posterior density in Bayesian formulations, the discovery of a single mode, let alone multiple, poses a formidable computational task. The goal of the present paper is two-fold. On one hand, we propose approximate, adaptive inference strategies using mixture densities to capture multi-modal posteriors. On the other, we extend our work in [1] with regard to effective dimensionality reduction techniques that reveal low-dimensional subspaces where the posterior variance is mostly concentrated. We validate the proposed model by employing Importance Sampling which confirms that the bias introduced is small and can be efficiently corrected if the analyst wishes to do so. We demonstrate the performance of the proposed strategy in nonlinear elastography where the identification of the mechanical properties of biological materials can inform non-invasive, medical diagnosis. The discovery of multiple modes (solutions) in such problems is critical in achieving the diagnostic objectives.
Direct and inverse problems in dispersive time-of-flight photocurrent revisited
Sagues, Francesc; Sokolov, Igor M.
2017-10-01
Using the fact that the continuous time random walk (CTRW) scheme is a random process subordinated to a simple random walk under the operational time given by the number of steps taken by the walker up to a given time, we revisit the problem of strongly dispersive transport in disordered media, which first lead Scher and Montroll to introducing the power law waiting time distributions. Using a subordination approach permits to disentangle the complexity of the problem, separating the solution of the boundary value problem (which is solved on the level of normal diffusive transport) from the influence of the waiting times, which allows for the solution of the direct problem in the whole time domain (including short times, out of reach of the initial approach), and simplifying strongly the analysis of the inverse problem. This analysis shows that the current traces do not contain information sufficient for unique restoration of the waiting time probability densities, but define a single-parametric family of functions that can be restored, all leading to the same photocurrent forms. The members of the family have the power-law tails which differ only by a prefactor, but may look astonishingly different at their body. The same applies to the multiple trapping model, mathematically equivalent to a special limiting case of CTRW. Contribution to the Topical Issue "Continuous Time Random Walk Still Trendy: Fifty-year History, Current State and Outlook", edited by Ryszard Kutner and Jaume Masoliver.
Inverse problem of estimating some of the geothermal reservoir characteristics (Part 1)
Energy Technology Data Exchange (ETDEWEB)
Yoshimura, Yuzaburo; Nakagome, Osamu; Okazaki, Kaneo (Japan Petroleum Exploration Co., Ltd., Tokyo)
1988-11-10
To estimate the parameters of reservoir, its characteristics such as permeability and porosity, and past pressure, flow rate and other production data are simulated. Those properties are determined as those that give the best reasonable match between both the observed and calculated data. That process of parameter determination by match is widely known as a history matching, extensively studied in the petroleum engineering and hydrological field these two decades. The problem of history matching is basically a nonlinear optimum minimization problem, as a nonlinear operator equation Ka=u (where K:reservoir model-representing operator, a:reservoir parameter and u:observed reservoir data of model's output). Inversely, the history matching problem is precisely u/K=a. However, the obtainment of a is extremely difficult, because K is of spatially varying parameter reservoir models. The standard history matching approaches of spatially varying parameters often lead to an ill-posed problem, generally characterized by the nonuniqueness and instability of parameters to be estimated. To circumvent such an ill-posed problem, the minimax and linear programming, quasilinearization, optimum control approach, Kalman filtering method, maximum likelihood estimation, etc. were developed. More recently, a method based on a bicubic spline interpolation of permeability and porosity distribution, in a single-phase two-dimensional areal reservoir from pressure data, has been reported. 3 refs.
Gentili, Rodolphe J; Papaxanthis, Charalambos; Ebadzadeh, Mehdi; Eskiizmirliler, Selim; Ouanezar, Sofiane; Darlot, Christian
2009-01-01
Several authors suggested that gravitational forces are centrally represented in the brain for planning, control and sensorimotor predictions of movements. Furthermore, some studies proposed that the cerebellum computes the inverse dynamics (internal inverse model) whereas others suggested that it computes sensorimotor predictions (internal forward model). This study proposes a model of cerebellar pathways deduced from both biological and physical constraints. The model learns the dynamic inverse computation of the effect of gravitational torques from its sensorimotor predictions without calculating an explicit inverse computation. By using supervised learning, this model learns to control an anthropomorphic robot arm actuated by two antagonists McKibben artificial muscles. This was achieved by using internal parallel feedback loops containing neural networks which anticipate the sensorimotor consequences of the neural commands. The artificial neural networks architecture was similar to the large-scale connectivity of the cerebellar cortex. Movements in the sagittal plane were performed during three sessions combining different initial positions, amplitudes and directions of movements to vary the effects of the gravitational torques applied to the robotic arm. The results show that this model acquired an internal representation of the gravitational effects during vertical arm pointing movements. This is consistent with the proposal that the cerebellar cortex contains an internal representation of gravitational torques which is encoded through a learning process. Furthermore, this model suggests that the cerebellum performs the inverse dynamics computation based on sensorimotor predictions. This highlights the importance of sensorimotor predictions of gravitational torques acting on upper limb movements performed in the gravitational field.
Directory of Open Access Journals (Sweden)
Shoubin Wang
2017-01-01
Full Text Available The compound variable inverse problem which comprises boundary temperature distribution and surface convective heat conduction coefficient of two-dimensional steady heat transfer system with inner heat source is studied in this paper applying the conjugate gradient method. The introduction of complex variable to solve the gradient matrix of the objective function obtains more precise inversion results. This paper applies boundary element method to solve the temperature calculation of discrete points in forward problems. The factors of measuring error and the number of measuring points zero error which impact the measurement result are discussed and compared with L-MM method in inverse problems. Instance calculation and analysis prove that the method applied in this paper still has good effectiveness and accuracy even if measurement error exists and the boundary measurement points’ number is reduced. The comparison indicates that the influence of error on the inversion solution can be minimized effectively using this method.
DEFF Research Database (Denmark)
Karamehmedovic, Mirza; Sørensen, Mads Peter; Hansen, Poul Erik
2010-01-01
the proposed method, we apply it in a concrete quantitative characterisation of a non-periodic, nano-scale grating defect, with numerically simulated measurements. It is shown that the presented procedure can solve the inverse problem with an accuracy usually thought to require rigorous electromagnetic......We propose a method of numerical solution of a type of inverse scattering problem that arises in the optical characterisation/quality control of nanostructures. The underlying global, ill-posed, nonlinear optimisation problem is first localised by best-fit matching of library and measured...... diffraction efficiency patterns. The inverse problem is then solved using piecewise linear interpolation between the best far-field matches. Finally, the results are refined, on average, by solving an additional local optimisation problem formulated in terms of the method of auxiliary sources. To illustrate...
An inverse-source problem for maximization of pore-fluid oscillation within poroelastic formations
Jeong, C.
2016-07-04
This paper discusses a mathematical and numerical modeling approach for identification of an unknown optimal loading time signal of a wave source, atop the ground surface, that can maximize the relative wave motion of a single-phase pore fluid within fluid-saturated porous permeable (poroelastic) rock formations, surrounded by non-permeable semi-infinite elastic solid rock formations, in a one-dimensional setting. The motivation stems from a set of field observations, following seismic events and vibrational tests, suggesting that shaking an oil reservoir is likely to improve oil production rates. This maximization problem is cast into an inverse-source problem, seeking an optimal loading signal that minimizes an objective functional – the reciprocal of kinetic energy in terms of relative pore-fluid wave motion within target poroelastic layers. We use the finite element method to obtain the solution of the governing wave physics of a multi-layered system, where the wave equations for the target poroelastic layers and the elastic wave equation for the surrounding non-permeable layers are coupled with each other. We use a partial-differential-equation-constrained-optimization framework (a state-adjoint-control problem approach) to tackle the minimization problem. The numerical results show that the numerical optimizer recovers optimal loading signals, whose dominant frequencies correspond to amplification frequencies, which can also be obtained by a frequency sweep, leading to larger amplitudes of relative pore-fluid wave motion within the target hydrocarbon formation than other signals.
Ravishankar, Saiprasad; Nadakuditi, Raj Rao; Fessler, Jeffrey A
2017-12-01
The sparsity of signals in a transform domain or dictionary has been exploited in applications such as compression, denoising and inverse problems. More recently, data-driven adaptation of synthesis dictionaries has shown promise compared to analytical dictionary models. However, dictionary learning problems are typically non-convex and NP-hard, and the usual alternating minimization approaches for these problems are often computationally expensive, with the computations dominated by the NP-hard synthesis sparse coding step. This paper exploits the ideas that drive algorithms such as K-SVD, and investigates in detail efficient methods for aggregate sparsity penalized dictionary learning by first approximating the data with a sum of sparse rank-one matrices (outer products) and then using a block coordinate descent approach to estimate the unknowns. The resulting block coordinate descent algorithms involve efficient closed-form solutions. Furthermore, we consider the problem of dictionary-blind image reconstruction, and propose novel and efficient algorithms for adaptive image reconstruction using block coordinate descent and sum of outer products methodologies. We provide a convergence study of the algorithms for dictionary learning and dictionary-blind image reconstruction. Our numerical experiments show the promising performance and speedups provided by the proposed methods over previous schemes in sparse data representation and compressed sensing-based image reconstruction.
Iterative Solutions to the Inverse Geometric Problem for Manipulators with no Closed Form Solution
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Pål Johan From
2008-07-01
Full Text Available A set of new iterative solutions to the inverse geometric problem is presented. The approach is general and does not depend on intersecting axes or calculation of the Jacobian. The solution can be applied to any manipulator and is well suited for manipulators for which convergence is poor for conventional Jacobian-based iterative algorithms. For kinematically redundant manipulators, weights can be applied to each joint to introduce stiffness and for collision avoidance. The algorithm uses the unit quaternion to represent the position of each joint and calculates analytically the optimal position of the joint when only the respective joint is considered. This sub-problem is computationally very efficient due to the analytical solution. Several algorithms based on the solution of this sub-problem are presented. For difficult problems, for which the initial condition is far from a solution or the geometry of the manipulator makes the solution hard to reach, it is shown that the algorithm finds a solution fairly close to the solution in only a few iterations.
The inverse problem for definition of the shape of a molten contact bridge
Kharin, Stanislav N.; Sarsengeldin, Merey M.
2017-09-01
The paper presents the results of investigation of bridging phenomenon occurring at opening of electrical contacts. The mathematical model describing the dynamics of metal molten bridge takes into account the Thomson effect. It is based on the system of partial differential equations for temperature and electrical fields of the bridge in the domain containing two moving unknown boundaries. One of them is an interface between liquid and solid zones of the bridge and should be found by the solution of the corresponding Stefan problem. The second free boundary corresponds to the shape of the visible part of a bridge. Its definition is an inverse problem, for which solution it is necessary to find minimum of the energy consuming for the formation of the shape of a quasi-stationary bridge. Three components of this energy, namely surface tension, pinch effect and gravitation, are defined by the functional which minimum gives the required shape of the bridge. The solution of corresponding variation problem is found by the reduction of the problem to the solution of the system of ordinary differential equations. Calculated values of the voltage of the bridge rupture for various metals are in a good agreement with the experimental data. The criteria responsible for the mechanism of molten bridge rupture are introduced in the paper.
SU-E-J-161: Inverse Problems for Optical Parameters in Laser Induced Thermal Therapy
Energy Technology Data Exchange (ETDEWEB)
Fahrenholtz, SJ; Stafford, RJ; Fuentes, DT [UT MD Anderson Cancer Center, Houston, TX (United States); UT Graduate School of Biomedical Sciences, Houston, TX (United States)
2014-06-01
Purpose: Magnetic resonance-guided laser-induced thermal therapy (MRgLITT) is investigated as a neurosurgical intervention for oncological applications throughout the body by active post market studies. Real-time MR temperature imaging is used to monitor ablative thermal delivery in the clinic. Additionally, brain MRgLITT could improve through effective planning for laser fiber's placement. Mathematical bioheat models have been extensively investigated but require reliable patient specific physical parameter data, e.g. optical parameters. This abstract applies an inverse problem algorithm to characterize optical parameter data obtained from previous MRgLITT interventions. Methods: The implemented inverse problem has three primary components: a parameter-space search algorithm, a physics model, and training data. First, the parameter-space search algorithm uses a gradient-based quasi-Newton method to optimize the effective optical attenuation coefficient, μ-eff. A parameter reduction reduces the amount of optical parameter-space the algorithm must search. Second, the physics model is a simplified bioheat model for homogeneous tissue where closed-form Green's functions represent the exact solution. Third, the training data was temperature imaging data from 23 MRgLITT oncological brain ablations (980 nm wavelength) from seven different patients. Results: To three significant figures, the descriptive statistics for μ-eff were 1470 m{sup −1} mean, 1360 m{sup −1} median, 369 m{sup −1} standard deviation, 933 m{sup −1} minimum and 2260 m{sup −1} maximum. The standard deviation normalized by the mean was 25.0%. The inverse problem took <30 minutes to optimize all 23 datasets. Conclusion: As expected, the inferred average is biased by underlying physics model. However, the standard deviation normalized by the mean is smaller than literature values and indicates an increased precision in the characterization of the optical parameters needed to plan MRg
Solving the inverse heat conduction problem using NVLink capable Power architecture
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Sándor Szénási
2017-11-01
Full Text Available The accurate knowledge of Heat Transfer Coefficients is essential for the design of precise heat transfer operations. The determination of these values requires Inverse Heat Transfer Calculations, which are usually based on heuristic optimisation techniques, like Genetic Algorithms or Particle Swarm Optimisation. The main bottleneck of these heuristics is the high computational demand of the cost function calculation, which is usually based on heat transfer simulations producing the thermal history of the workpiece at given locations. This Direct Heat Transfer Calculation is a well parallelisable process, making it feasible to implement an efficient GPU kernel for this purpose. This paper presents a novel step forward: based on the special requirements of the heuristics solving the inverse problem (executing hundreds of simulations in a parallel fashion at the end of each iteration, it is possible to gain a higher level of parallelism using multiple graphics accelerators. The results show that this implementation (running on 4 GPUs is about 120 times faster than a traditional CPU implementation using 20 cores. The latest developments of the GPU-based High Power Computations area were also analysed, like the new NVLink connection between the host and the devices, which tries to solve the long time existing data transfer handicap of GPU programming.
Inverse problem for tripotential measures in the study of buried cavities
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D. Luzio
1996-06-01
Full Text Available This paper presents a solution to the inverse electrical problem for the interpretation of apparent resistivity anomalies due to empty buried cavities of quasi-spherical shape when tripotential measures are carried out. The anomalies of the apparent resistivities ra,rb andrg,and the composed resistivitiesrmand rt were previously calculated for a sufficient class of spherical models of resistivity anomalies. Then, for the whole class of models, some functionals of spatial distribution of the apparent and composed resistivity were identified and analyzed. They represent the average characteristics of the anomalies and, depending in a simple way on the fundamental parameters of the sources of the anomalies (average diameter and depth, they allow reliable estimates to be determined. Among the studied functionals, those allowing the most stable and less biased estimates of the anomaly source parameters are identified by numerical simulations with random noise perturbed data. Finally the trend of standard deviation and bias of the estimates of the unknown parameters were analyzed by varying the source models and the set of functionals used for the inversion.
An Improved Genetic Algorithm for Single-Machine Inverse Scheduling Problem
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Jianhui Mou
2014-01-01
Full Text Available The goal of the scheduling is to arrange operations on suitable machines with optimal sequence for corresponding objectives. In order to meet market requirements, scheduling systems must own enough flexibility against uncertain events. These events can change production status or processing parameters, even causing the original schedule to no longer be optimal or even to be infeasible. Traditional scheduling strategies, however, cannot cope with these cases. Therefore, a new idea of scheduling called inverse scheduling has been proposed. In this paper, the inverse scheduling with weighted completion time (SMISP is considered in a single-machine shop environment. In this paper, an improved genetic algorithm (IGA with a local searching strategy is proposed. To improve the performance of IGA, efficient encoding scheme, fitness evaluation mechanism, feasible initialization methods, and a local search procedure have been employed in the paper. Because of the local improving method, the proposed IGA can balance its exploration ability and exploitation ability. We adopt 27 instances to verify the effectiveness of the proposed algorithm. The experimental results illustrated that the proposed algorithm can generate satisfactory solutions. This approach also has been applied to solve the scheduling problem in the real Chinese shipyard and can bring some benefits.
Derkachov, G.; Jakubczyk, T.; Jakubczyk, D.; Archer, J.; Woźniak, M.
2017-07-01
Utilising Compute Unified Device Architecture (CUDA) platform for Graphics Processing Units (GPUs) enables significant reduction of computation time at a moderate cost, by means of parallel computing. In the paper [Jakubczyk et al., Opto-Electron. Rev., 2016] we reported using GPU for Mie scattering inverse problem solving (up to 800-fold speed-up). Here we report the development of two subroutines utilising GPU at data preprocessing stages for the inversion procedure: (i) A subroutine, based on ray tracing, for finding spherical aberration correction function. (ii) A subroutine performing the conversion of an image to a 1D distribution of light intensity versus azimuth angle (i.e. scattering diagram), fed from a movie-reading CPU subroutine running in parallel. All subroutines are incorporated in PikeReader application, which we make available on GitHub repository. PikeReader returns a sequence of intensity distributions versus a common azimuth angle vector, corresponding to the recorded movie. We obtained an overall ∼ 400 -fold speed-up of calculations at data preprocessing stages using CUDA codes running on GPU in comparison to single thread MATLAB-only code running on CPU.
Improving landscape inference by integrating heterogeneous data in the inverse Ising problem.
Barrat-Charlaix, Pierre; Figliuzzi, Matteo; Weigt, Martin
2016-11-25
The inverse Ising problem and its generalizations to Potts and continuous spin models have recently attracted much attention thanks to their successful applications in the statistical modeling of biological data. In the standard setting, the parameters of an Ising model (couplings and fields) are inferred using a sample of equilibrium configurations drawn from the Boltzmann distribution. However, in the context of biological applications, quantitative information for a limited number of microscopic spins configurations has recently become available. In this paper, we extend the usual setting of the inverse Ising model by developing an integrative approach combining the equilibrium sample with (possibly noisy) measurements of the energy performed for a number of arbitrary configurations. Using simulated data, we show that our integrative approach outperforms standard inference based only on the equilibrium sample or the energy measurements, including error correction of noisy energy measurements. As a biological proof-of-concept application, we show that mutational fitness landscapes in proteins can be better described when combining evolutionary sequence data with complementary structural information about mutant sequences.
Desmal, Abdulla
2014-07-01
A numerical framework that incorporates recently developed iterative shrinkage thresholding (IST) algorithms within the Born iterative method (BIM) is proposed for solving the two-dimensional inverse electromagnetic scattering problem. IST algorithms minimize a cost function weighted between measurement-data misfit and a zeroth/first-norm penalty term and therefore promote "sharpness" in the solution. Consequently, when applied to domains with sharp variations, discontinuities, or sparse content, the proposed framework is more efficient and accurate than the "classical" BIM that minimizes a cost function with a second-norm penalty term. Indeed, numerical results demonstrate the superiority of the IST-BIM over the classical BIM when they are applied to sparse domains: Permittivity and conductivity profiles recovered using the IST-BIM are sharper and more accurate and converge faster. © 1963-2012 IEEE.
Spectral approach to the inverse problem for the field of arbitrary changing electric dipole
Epp, V
2013-01-01
The inverse problem for electromagnetic field produced by arbitrary altered charge distribution in dipole approximation is solved. The charge distribution is represented by its dipole moment. It is assumed that the spectral properties of magnetic field of the dipole are known. The position of the dipole and its Fourier components are considered as the unknown quantities. It is assumed that relative increments of amplitude and phase of magnetic field in the vicinity of the observation point are known. The derived results can be used for study of phenomena concerned with occurrence and variation of localized electric charge distribution, when the position and the dynamics of a localized source of electromagnetic field are to be defined.
The inverse problem of brain energetics: ketone bodies as alternative substrates
Calvetti, D.; Occhipinti, R.; Somersalo, E.
2008-07-01
Little is known about brain energy metabolism under ketosis, although there is evidence that ketone bodies have a neuroprotective role in several neurological disorders. We investigate the inverse problem of estimating reaction fluxes and transport rates in the different cellular compartments of the brain, when the data amounts to a few measured arterial venous concentration differences. By using a recently developed methodology to perform Bayesian Flux Balance Analysis and a new five compartment model of the astrocyte-glutamatergic neuron cellular complex, we are able to identify the preferred biochemical pathways during shortage of glucose and in the presence of ketone bodies in the arterial blood. The analysis is performed in a minimally biased way, therefore revealing the potential of this methodology for hypothesis testing.
Padois, Thomas; Berry, Alain
2015-12-01
Microphone arrays and beamforming have become a standard method to localize aeroacoustic sources. Deconvolution techniques have been developed to improve spatial resolution of beamforming maps. The deconvolution approach for the mapping of acoustic sources (DAMAS) is a standard deconvolution technique, which has been enhanced via a sparsity approach called sparsity constrained deconvolution approach for the mapping of acoustic sources (SC-DAMAS). In this paper, the DAMAS inverse problem is solved using the orthogonal matching pursuit (OMP) and compared with beamforming and SC-DAMAS. The resulting noise source maps show that OMP-DAMAS is an efficient source localization technique in the case of uncorrelated or correlated acoustic sources. Moreover, the computation time is clearly reduced as compared to SC-DAMAS.
Karkhin, V. A.; Pittner, A.; Schwenk, C.; Rethmeier, M.
2011-06-01
The paper presents bounded volume heat sources and the corresponding functional-analytical expressions for the temperature field. The power density distributions considered here are normal, exponential and parabolic. The sources model real heat sources like the welding arc, laser beam, electron beam, etc., the convection in the weld pool as well as the latent heat due to fusion and solidification. The parameters of the heat source models are unknown a priori and have to be evaluated by solving an inverse heat conduction problem. The functional-analytical technique for calculating 3D temperature fields in butt welding is developed. The proposed technique makes it possible to reduce considerably the total time for data input and solution. It is demonstrated with an example of laser beam welding of steel plates.
Beck, J. V.; Murio, D. A.
1984-01-01
The inverse heat conduction problem involves the calculation of surface heat flux and/or temperature histories from transient, measured temperatures inside solids. This paper proposes and investigates a new combined procedure that is based on two different methods. One of these methods is the sequential function specification method which was originally proposed by Beck. The other method is the regularization method which has been used by Tikhonov and others. The combined method uses the sequential feature of the function specification method and the special function that is minimized in the regularization method. A test case is investigated of a semi-infinite body exposed to a heat flux that is initially zero, has a step increase and then drops to zero. A wide range of parameters is investigated. The combined procedure is much more computationally efficient than the usual regularization procedure when all the flux components are found simultaneously and yet the calculated values found by combined method are little different.
The inverse problem of brain energetics: ketone bodies as alternative substrates
Energy Technology Data Exchange (ETDEWEB)
Calvetti, D; Occhipinti, R [Case Western Reserve University, Department of Mathematics, 10900 Euclid Avenue, Cleveland, OH 44106 (United States); Somersalo, E [Helsinki University of Technology, Institute of Mathematics, P. O. Box 1100, FIN-02015 HUT (Finland)], E-mail: daniela.calvetti@case.edu, E-mail: rossana.occhipinti@case.edu, E-mail: erkki.somersalo@tkk.fi
2008-07-15
Little is known about brain energy metabolism under ketosis, although there is evidence that ketone bodies have a neuroprotective role in several neurological disorders. We investigate the inverse problem of estimating reaction fluxes and transport rates in the different cellular compartments of the brain, when the data amounts to a few measured arterial venous concentration differences. By using a recently developed methodology to perform Bayesian Flux Balance Analysis and a new five compartment model of the astrocyte-glutamatergic neuron cellular complex, we are able to identify the preferred biochemical pathways during shortage of glucose and in the presence of ketone bodies in the arterial blood. The analysis is performed in a minimally biased way, therefore revealing the potential of this methodology for hypothesis testing.
Control of plasma profile in microwave discharges via inverse-problem approach
Directory of Open Access Journals (Sweden)
Yasuyoshi Yasaka
2013-12-01
Full Text Available In the manufacturing process of semiconductors, plasma processing is an essential technology, and the plasma used in the process is required to be of high density, low temperature, large diameter, and high uniformity. This research focuses on the microwave-excited plasma that meets these needs, and the research target is a spatial profile control. Two novel techniques are introduced to control the uniformity; one is a segmented slot antenna that can change radial distribution of the radiated field during operation, and the other is a hyper simulator that can predict microwave power distribution necessary for a desired radial density profile. The control system including these techniques provides a method of controlling radial profiles of the microwave plasma via inverse-problem approach, and is investigated numerically and experimentally.
Inverse acoustooptic problem: Coherent summing of optical beams into a single optical channel
Antonov, S. N.; Vainer, A. V.; Proklov, V. V.; Rezvov, Yu. G.
2007-05-01
A highly efficient summing of mutually coherent beams (channels) into a single beam with the same divergence and aperture (an inverse acoustooptic problem) is realized via diffraction in a Bragg cell. The multibeam field to be converged is formed as a result of the diffraction (splitting) of a single laser beam. Theoretical and experimental evidence is obtained for the fact that the repeated diffraction can provide a highly efficient (up to 100%) reconstruction of beam with initial parameters. The experiments are performed with a single-mode laser radiation at 0.63 μm and multimode radiation at 0.96 μm. The virtually attained summing efficiency is on the order of 70%. The factors that act to diminish the experimental efficiency below the predicted value, the ways to raise the efficiency, and possible applications of the results of this study are discussed.
Loreti, Paola; Sforza, Daniela; Yamamoto, Masahiro
2017-12-01
We consider an anisotropic hyperbolic equation with memory term: ∂t2u(x,t)=∑i,j=1n∂i(aij(x)∂ju)+∫0t∑|α|⩽2bα(x,t,η)∂xαu(x,η)dη+R(x,t)f(x) for x \\in Ω and t\\in (0, T) , which is a simplified model equation for viscoelasticity. The main result is a both-sided Lipschitz stability estimate for an inverse source problem of determining a spatial varying factor f(x) of the force term R(x, t) f(x) . The proof is based on a Carleman estimate and due to the anisotropy, the existing transformation technique does not work and we introduce a new transformation of u in order to treat the integral terms.
Real-time solution of the finite element inverse problem of viscoelasticity
Eskandari, Hani; Salcudean, Septimiu E.; Rohling, Robert; Bell, Ian
2011-08-01
The linear dynamic finite element model can be formulated such that the elasticity and viscosity of the elements appear as the parameters in a linear system of equations. The resulting system of equations can be solved directly using singular value decomposition or a similar technique or through defining a quadratic functional. A priori knowledge and regularity measures can be added as equality or inequality constraints. The sensitivity of the inverse problem solution to the displacement noise and model imperfections are tested in simulations, where the parameters were successfully reconstructed with a displacement signal-to-noise ratio as low as 20 dB. Also, the viscoelastic parameters have been successfully estimated for a breast phantom with an embedded hard inclusion. The study of the computation speed demonstrates the potential of the new method for real-time implementations.
Directory of Open Access Journals (Sweden)
Виктор Семенович Корнилов
2015-12-01
Full Text Available In article the problem of training of specialists in the field of applied mathematics is discussed. The attention on the content of training of students of physical and mathematical specialties of higher educational institutions to the inverse problems for differential equations is paid. The statement of the inverse problem for system of the equations of Maxwell which entered the content of training, the scheme of its decision with the formulation of the corresponding final theorems is given. Conclusions about formation of competence of students in the field of applied mathematics in the course of such training are drawn.
Cerebellum-inspired neural network solution of the inverse kinematics problem.
Asadi-Eydivand, Mitra; Ebadzadeh, Mohammad Mehdi; Solati-Hashjin, Mehran; Darlot, Christian; Abu Osman, Noor Azuan
2015-12-01
The demand today for more complex robots that have manipulators with higher degrees of freedom is increasing because of technological advances. Obtaining the precise movement for a desired trajectory or a sequence of arm and positions requires the computation of the inverse kinematic (IK) function, which is a major problem in robotics. The solution of the IK problem leads robots to the precise position and orientation of their end-effector. We developed a bioinspired solution comparable with the cerebellar anatomy and function to solve the said problem. The proposed model is stable under all conditions merely by parameter determination, in contrast to recursive model-based solutions, which remain stable only under certain conditions. We modified the proposed model for the simple two-segmented arm to prove the feasibility of the model under a basic condition. A fuzzy neural network through its learning method was used to compute the parameters of the system. Simulation results show the practical feasibility and efficiency of the proposed model in robotics. The main advantage of the proposed model is its generalizability and potential use in any robot.
Space-Dependent Sobolev Gradients as a Regularization for Inverse Radiative Transfer Problems
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Y. Favennec
2016-01-01
Full Text Available Diffuse optical tomography problems rely on the solution of an optimization problem for which the dimension of the parameter space is usually large. Thus, gradient-type optimizers are likely to be used, such as the Broyden-Fletcher-Goldfarb-Shanno (BFGS algorithm, along with the adjoint-state method to compute the cost function gradient. Usually, the L2-inner product is chosen within the extraction procedure (i.e., in the definition of the relationship between the cost function gradient and the directional derivative of the cost function while alternative inner products that act as regularization can be used. This paper presents some results based on space-dependent Sobolev inner products and shows that this method acts as an efficient low-pass filter on the cost function gradient. Numerical results indicate that the use of Sobolev gradients can be particularly attractive in the context of inverse problems, particularly because of the simplicity of this regularization, since a single additional diffusion equation is to be solved, and also because the quality of the solution is smoothly varying with respect to the regularization parameter.
Inverse Problem for Two-Dimensional Discrete Schr`dinger Equation
Serdyukova, S I
2000-01-01
For two-dimensional discrete Schroedinger equation the boundary-value problem in rectangle M times N with zero boundary conditions is solved. It's stated in this work, that inverse problem reduces to reconstruction of C symmetric five-diagonal matrix with given spectrum and given first k(M,N), 1<-k
Sini, Mourad
2003-08-01
In this paper, we deal with the inverse spectral problem for the equation -(pu')' + qu = lambdaru on a finite interval (0,h). The above equation subjected to appropriate boundary conditions on zero and h gives the vibrations of a string of length h. Using the Dirichlet-to-Neumann map type approach known in the multidimensional Calderón problem, we prove some uniqueness results of one or two discontinuous coefficients among p,q and r, and the length h from the vibrations of the end point zero. We also consider Sturm-Liouville systems of the form -(Pu')' + Qu = lambdaRu where P and R are diagonal n × n matrices and Q a symmetric n × n matrix with Linfty(Omega) entries. In the case n = 2, this problem models the small vibrations of two connected beams. We prove the uniqueness of the matrix of rigidity P or matrix density R when its entries are piecewise constant functions.
Energy Technology Data Exchange (ETDEWEB)
Thomas, Edward V. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Stork, Christopher L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Mattingly, John K. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2015-07-01
Inverse radiation transport focuses on identifying the configuration of an unknown radiation source given its observed radiation signatures. The inverse problem is traditionally solved by finding the set of transport model parameter values that minimizes a weighted sum of the squared differences by channel between the observed signature and the signature pre dicted by the hypothesized model parameters. The weights are inversely proportional to the sum of the variances of the measurement and model errors at a given channel. The traditional implicit (often inaccurate) assumption is that the errors (differences between the modeled and observed radiation signatures) are independent across channels. Here, an alternative method that accounts for correlated errors between channels is described and illustrated using an inverse problem based on the combination of gam ma and neutron multiplicity counting measurements.
Stankova, K.
2009-01-01
This thesis studies the so-called inverse Stackelberg games, that are new in the world of game theory, their properties, and their applications in the optimal toll design problem, the energy markets liberalization problem, and in the theory of incentives.
Cao, Jianping; Du, Zhengjian; Mo, Jinhan; Li, Xinxiao; Xu, Qiujian; Zhang, Yinping
2016-12-20
Passive sampling is an alternative to active sampling for measuring concentrations of gas-phase volatile organic compounds (VOCs). However, the uncertainty or relative error of the measurements have not been minimized due to the limitations of existing design methods. In this paper, we have developed a novel method, the inverse problem optimization method, to address the problems associated with designing accurate passive samplers. The principle is to determine the most appropriate physical properties of the materials, and the optimal geometry of a passive sampler, by minimizing the relative sampling error based on the mass transfer model of VOCs for a passive sampler. As an example application, we used our proposed method to optimize radial passive samplers for the sampling of benzene and formaldehyde in a normal indoor environment. A new passive sampler, which we have called the Tsinghua Passive Diffusive Sampler (THPDS), for indoor benzene measurement was developed according to the optimized results. Silica zeolite was selected as the sorbent for the THPDS. The measured overall uncertainty of THPDS (22% for benzene) is lower than that of most commercially available passive samplers but is quite a bit larger than the modeled uncertainty (4.8% for benzene, the optimized result), suggesting that further research is required.
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В С Корнилов
2016-12-01
Full Text Available In article the attention that when training in the inverse problems for the differential equations at bachelors and undergraduates fundamental knowledge in the field of methods of mathematical physics whom allows to investigate various educational mathematical tasks successfully is formed is paid. Statements of educational inverse problems for the differential equations to which research methods of mathematical physics, and also the short scheme of their research with the formulation of the received results are applied are given. Such methods of mathematical physics as a method of characteristics, Fourier’s method, a convolution method, Kirchhoff’s formula which bachelors and undergraduates apply at the solution of the inverse problems on studies are shown.
Charyyar Ashyralyyev; Gulzipa Akyuz; Mutlu Dedeturk
2017-01-01
In this work, we consider an inverse elliptic problem with Bitsadze-Samarskii type multipoint nonlocal and Neumann boundary conditions. We construct the first and second order of accuracy difference schemes (ADSs) for problem considered. We stablish stability and coercive stability estimates for solutions of these difference schemes. Also, we give numerical results for overdetermined elliptic problem with multipoint Bitsadze-Samarskii type nonlocal and Neumann boundary...
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Rodolphe J Gentili
Full Text Available BACKGROUND: Several authors suggested that gravitational forces are centrally represented in the brain for planning, control and sensorimotor predictions of movements. Furthermore, some studies proposed that the cerebellum computes the inverse dynamics (internal inverse model whereas others suggested that it computes sensorimotor predictions (internal forward model. METHODOLOGY/PRINCIPAL FINDINGS: This study proposes a model of cerebellar pathways deduced from both biological and physical constraints. The model learns the dynamic inverse computation of the effect of gravitational torques from its sensorimotor predictions without calculating an explicit inverse computation. By using supervised learning, this model learns to control an anthropomorphic robot arm actuated by two antagonists McKibben artificial muscles. This was achieved by using internal parallel feedback loops containing neural networks which anticipate the sensorimotor consequences of the neural commands. The artificial neural networks architecture was similar to the large-scale connectivity of the cerebellar cortex. Movements in the sagittal plane were performed during three sessions combining different initial positions, amplitudes and directions of movements to vary the effects of the gravitational torques applied to the robotic arm. The results show that this model acquired an internal representation of the gravitational effects during vertical arm pointing movements. CONCLUSIONS/SIGNIFICANCE: This is consistent with the proposal that the cerebellar cortex contains an internal representation of gravitational torques which is encoded through a learning process. Furthermore, this model suggests that the cerebellum performs the inverse dynamics computation based on sensorimotor predictions. This highlights the importance of sensorimotor predictions of gravitational torques acting on upper limb movements performed in the gravitational field.
Problem in the surgical correction of long-face with vertical open bite
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Coen Pramono D
2005-12-01
Full Text Available Long-face cases usually need both treatment of orthodontic and surgery. The problem appearing in the correction of long-face might be able to be related with some difficult factors such as the crowded teeth and excessive vertical height. A class III malocclusion and excessive open bite can be also followed in long face. This situation might worsen the facial aesthetic condition and increase the difficulty in orthodontic treatment. The orthodontic approach is oriented toward positioning the teeth pre-surgically to facilitate the surgical plan. The form of mandible which has grown in the downward direction in the area of mandible angle makes an extreme vertical open bite. The maxilla is usually presented with a maxillary hypolasia. Double-jaw surgery was done as the correction of the lower jaw alone would produce a flattened face appearance and difficulty in repositioning the mandible to achieve a good facial performance. Several cephalometric points were measured to observe the facial situation progress after surgery. Two cases of longface are reported, and the same surgical treatments were performed and showed different results.
Circulation of the Carribean Sea: a well-resolved inverse problem
Energy Technology Data Exchange (ETDEWEB)
Roemmich, D.
1981-09-20
The Caribbean Sea is selected as a region where the large-scale circulation is well determined by historical hydrographic measurements through application of the inverse method. A simple example is used to illustrate the technique and to demonstrate how some physically relevant quantities may be well determined in the formally underdetermined inverse problem. The geostrophic flow field in the Caribbean is found by imposing mass and salt conservation constraints in seven layers separated by surfaces of constant potential density. An unsmoothed solution is displayed that has weak dependence on an initial choice of reference level. In addition, a unique smoothed solution is shown. Above sigma/sub theta/ = 27.4, the total flow leaving the western Caribbean is estimated to be 29 x 10/sup 6/ m/sup 3/ s/sup -1/, in agreement with direct measurements. This flow is made up of 22 x 10/sup 6/ m/sup 3/s /sup -1/ entering the Caribbean from the east and flowing across the southern half of the basin as the Caribbean Current, and 7 x 10/sup 6/ m/sup 3/ s/sup -1/, in agreement with direct measurements. This flow is made up of 22 x 10/sup 6/ m/sup 3/ s/sup -1/ entering the Caribbean from the east and flowing across the southern half of the basin as the Caribbean Current, and 7 x 10/sup 7/ m/sup 3/ s/sup -1/ entering from the north through Windward Passage. Both of these currents show small-scale variability that diminishes with distance from the respective passages. The deep flow has no net transport, as required by the shallow exit, but a well organized clockwise recirculation is found in the deep eastern Caribbean.
Kawashita, Mishio
2017-01-01
In this paper, an inverse initial-boundary value problem for the heat equation in three dimensions is studied. Assume that a three-dimensional heat conductive body contains several cavities of strictly convex. In the outside boundary of this body, a single pair of the temperature and heat flux is given as an observation datum for the inverse problem. It is found the minimum length of broken paths connecting arbitrary fixed point in the outside, a point on the boundary of the cavities and a po...
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Ramazan Tinaztepe
2014-01-01
Full Text Available This study is devoted to the numerical solution of an inverse coefficient problem for a density dependent nonlinear reaction-diffusion equation. The method is based on approximating the unknown coefficient by polynomials. An optimal idea for solving the inverse problem is to minimize an error functional between the output data and the additional data. For this purpose, we find a polynomial of degree n that minimizes the error functional; i.e, n-th degree polynomial approximation of the unknown coefficient for the desired n.
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Gülcan Özkum
2013-01-01
Full Text Available The study in this paper mainly concerns the inverse problem of determining an unknown source function in the linear fractional differential equation with variable coefficient using Adomian decomposition method (ADM. We apply ADM to determine the continuous right hand side functions fx and ft in the heat-like diffusion equations Dtαux,t=hxuxxx,t+fx and Dtαux,t=hxuxxx,t+ft, respectively. The results reveal that ADM is very effective and simple for the inverse problem of determining the source function.
Agoshkov, Valery
2017-04-01
There are different approaches for modeling boundary conditions describing hydrophysical fields in water areas with "liquid" boundaries. Variational data assimilation may also be considered as one of such approaches. Development of computer equipment, together with an increase in the quantity and quality of data from the satellites and other monitoring tools proves that the development of this particular approach is perspective. The range of connected the problems is wide - different recording forms of boundary conditions, observational data assimilation procedures and used models of hydrodynamics are possible. In this work some inverse problems and corresponding variational data assimilation ones, connected with mathematical modeling of hydrophysical fields in water areas (seas and oceans) with "liquid" ("open") boundaries, are formulated and studied. Note that the surface of water area (which can also be considered as a "liquid" boundary) is not included in the set of "liquid" boundaries, in this case "liquid" boundaries are borders between the areas "water-water". In the work, mathematical model of hydrothermodynamics in the water areas with "liquid" ("open") part of the boundary, a generalized statement of the problem and the splitting method for time approximation are formulated. Also the problem of variational data assimilation and iterative algorithm for solving inverse problems mentioned above are formulated. The work is based on [1]. The work was partly supported by the Russian Science Foundation (project 14-11-00609, the general formulation of the inverse problems) and by the Russian Foundation for Basic Research (project 16-01-00548, the formulation of the problem and its study). [1] V.I. Agoshkov, Methods for solving inverse problems and variational data assimilation problems of observations in the problems of the large-scale dynamics of the oceans and seas, Institute of Numerical Mathematics, RAS, Moscow, 2016 (in Russian).
Hampel, Uwe; Freyer, Richard
1996-12-01
We present a reconstruction scheme which solves the inverse linear problem in optical absorption tomography for radially symmetric objects. This is a relevant geometry for optical diagnosis in soft tissues, e.g. breast, testis and even head. The algorithm utilizes an invariance property of the linear imaging operator in homogeneously scattering media. The inverse problem is solved in the Fourier space of the angular component leading to a considerable dimension reduction which allows to compute the inverse in a direct way using singular value decomposition. There are two major advantages of this approach. First the inverse operator can be stored in computer memory and the computation of the inverse problem comprises only a few matrix multiplications. This makes the algorithm very fast and suitable for parallel execution. On the other hand we obtain the spectrum of the imaging operator that allows conclusions about reconstruction limits in the presence of noise and gives a termination criterion for image synthesis. To demonstrate the capabilities of this scheme reconstruction results from synthetic and phantom data are presented.
Model Reduction of a 2-Dimenional Sedimentary Texture Groundwater-Flow Model for Inverse Problems
Boyce, S. E.; Yeh, W.
2013-12-01
pattern by defining the 57,888 elements with a fraction of coarse- and fine-grained sediment. This highly-heterogeneous model is reduced by selecting combinations of the global coarse and fine hydraulic conductivity at a set power of the power mean. The dimensionality of the Texture Oristano model for power-mean powers of 0, 0.8, and 1 are reduced from a system of 29,197 ordinary differential equations to 60, 42, and 45 equations, respectively. The application of the parameter-independent model reduction reduces the CPU time by 90% for a single model run. The robustness of the three reduced models, which differ in the power-mean power, are evaluated by solving a synthetic inverse problem with the BFGS algorithm. The three reduced models produced the same optimal coarse and fine hydraulic conductivity as the full model's result from BFGS. This study demonstrates that parameter-independent model reduction is possible for a highly, heterogeneous groundwater model and the inverse problem can be solved with the reduced model at a fraction of the time required by the full model.
Goel, N.; Strebel, D. E.
1983-01-01
An important but relatively uninvestigated problem in remote sensing is the inversion of vegetative canopy reflectance models to obtain agrophysical parameters, given measured reflectances. The problem is here formally defined and its solution outlined. Numerical nonlinear optimization techniques are used to implement this inversion to obtain the leaf area index using Suits' canopy reflectance model. The results for a variety of cases indicate that this can be done successfully using infrared reflectances at different views or azimuth angles or a combination thereof. The other parameters of the model must be known, although reasonable measurement errors can be tolerated without seriously degrading the accuracy of the inversion. The application of the technique to ground based remote-sensing experiments is potentially useful, but is limited to the degree to which the canopy reflectance model can accurately predict observed reflectances.
Inverse and direct problems of optics: usage of artificial neural networks
Abrukov, Victor S.; Pavlov, Roman I.; Malinin, Gennadiy I.
2004-08-01
We describe an application of artificial neural networks (ANN) for solving of inverse and direct problems of optics. Using the ANN we calculate local and integral characteristics of object by means of incomplete set of data that characterize optical images. Possibilities of usage the only one value of a function of signal intensity distributionn in a plane of a registration for full determination of distribution of local characteristics in an object are shown. It is very important for optical fiber sensors, smart sensors and MEMS. Examples of ANN usage for a case of object with a cylindrical symmetry in a field of interferometry are presented. Results obtained show that determination of object local and integral characteristics can be perform very much simpler than by means of standard procedures and numerical approaches for signal processing, reduction and analysis. The ANN can allow also to solve number of tasks that could not be solved by means of usual approaches. In prospects, this method can be used for creation of automated systems for diagnostics, testing and control in various fields of scientific and applied research as well as in industry.
Inverse Problem of Air Filtration of Nanoparticles: Optimal Quality Factors of Fibrous Filters
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Dahua Shou
2015-01-01
Full Text Available Application of nanofibers has become an emerging approach to enhance filtration efficiency, but questions arise about the decrease in Quality factor (QF for certain particles due to the rapidly increasing pressure drop. In this paper, we theoretically investigate the QF of dual-layer filters for filtration of monodisperse and polydisperse nanoparticles. The inverse problem of air filtration, as defined in this work, consists in determining the optimal construction of the two-layer fibrous filter with the maximum QF. In comparison to a single-layer substrate, improved QF values for dual-layer filters are found when a second layer with proper structural parameters is added. The influences of solidity, fiber diameter, filter thickness, face velocity, and particle size on the optimization of QF are studied. The maximum QF values for realistic polydisperse particles with a lognormal size distribution are also found. Furthermore, we propose a modified QF (MQF accounting for the effects of energy cost and flow velocity, which are significant in certain operations. The optimal MQF of the dual-layer filter is found to be over twice that of the first layer. This work provides a quick tool for designing and optimizing fibrous structures with better performance for the air filtration of specific nanoparticles.
Liu, Sha; Liu, Shi; Tong, Guowei
2017-11-01
In industrial areas, temperature distribution information provides a powerful data support for improving system efficiency, reducing pollutant emission, ensuring safety operation, etc. As a noninvasive measurement technology, acoustic tomography (AT) has been widely used to measure temperature distribution where the efficiency of the reconstruction algorithm is crucial for the reliability of the measurement results. Different from traditional reconstruction techniques, in this paper a two-phase reconstruction method is proposed to ameliorate the reconstruction accuracy (RA). In the first phase, the measurement domain is discretized by a coarse square grid to reduce the number of unknown variables to mitigate the ill-posed nature of the AT inverse problem. By taking into consideration the inaccuracy of the measured time-of-flight data, a new cost function is constructed to improve the robustness of the estimation, and a grey wolf optimizer is used to solve the proposed cost function to obtain the temperature distribution on the coarse grid. In the second phase, the Adaboost.RT based BP neural network algorithm is developed for predicting the temperature distribution on the refined grid in accordance with the temperature distribution data estimated in the first phase. Numerical simulations and experiment measurement results validate the superiority of the proposed reconstruction algorithm in improving the robustness and RA.
Inverse Problem for Color Doppler Ultrasound-Assisted Intracardiac Blood Flow Imaging
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Jaeseong Jang
2016-01-01
Full Text Available For the assessment of the left ventricle (LV, echocardiography has been widely used to visualize and quantify geometrical variations of LV. However, echocardiographic image itself is not sufficient to describe a swirling pattern which is a characteristic blood flow pattern inside LV without any treatment on the image. We propose a mathematical framework based on an inverse problem for three-dimensional (3D LV blood flow reconstruction. The reconstruction model combines the incompressible Navier-Stokes equations with one-direction velocity component of the synthetic flow data (or color Doppler data from the forward simulation (or measurement. Moreover, time-varying LV boundaries are extracted from the intensity data to determine boundary conditions of the reconstruction model. Forward simulations of intracardiac blood flow are performed using a fluid-structure interaction model in order to obtain synthetic flow data. The proposed model significantly reduces the local and global errors of the reconstructed flow fields. We demonstrate the feasibility and potential usefulness of the proposed reconstruction model in predicting dynamic swirling patterns inside the LV over a cardiac cycle.
General Features of Supersymmetric Signals at the ILC: Solving the LHC Inverse Problem
Energy Technology Data Exchange (ETDEWEB)
Berger, Carola F.; Gainer, James S.; Hewett, JoAnne L.; Lillie, Ben; Rizzo, Thomas G.
2007-12-19
We examine whether the {radical}s = 500 GeV International Linear Collider with 80% electron beam polarization can be used to solve the LHC Inverse Problem within the framework of the MSSM. We investigate 242 points in the MSSM parameter space, which we term models, that correspond to the 162 pairs of models found by Arkani-Hamed et al. to give indistinguishable signatures at the LHC. We first determine whether the production of the various SUSY particles is visible above the Standard Model background for each of these parameter space points, and then make a detailed comparison of their various signatures. Assuming an integrated luminosity of 500 fb{sup -1}, we find that only 82 out of 242 models lead to visible signatures of some kind with a significance {ge} 5 and that only 57(63) out of the 162 model pairs are distinguishable at 5(3){sigma}. Our analysis includes PYTHIA and CompHEP SUSY signal generation, full matrix element SM backgrounds for all 2 {yields} 2, 2 {yields} 4, and 2 {yields} 6 processes, ISR and beamstrahlung generated via WHIZARD/GuineaPig, and employs the fast SiD detector simulation org.lcsim.
Zhang, Yin; Wei, Zhiyuan; Zhang, Yinping; Wang, Xin
2017-12-01
Urban heating in northern China accounts for 40% of total building energy usage. In central heating systems, heat is often transferred from heat source to users by the heat network where several heat exchangers are installed at heat source, substations and terminals respectively. For given overall heating capacity and heat source temperature, increasing the terminal fluid temperature is an effective way to improve the thermal performance of such cascade heat exchange network for energy saving. In this paper, the mathematical optimization model of the cascade heat exchange network with three-stage heat exchangers in series is established. Aim at maximizing the cold fluid temperature for given hot fluid temperature and overall heating capacity, the optimal heat exchange area distribution and the medium fluids' flow rates are determined through inverse problem and variation method. The preliminary results show that the heat exchange areas should be distributed equally for each heat exchanger. It also indicates that in order to improve the thermal performance of the whole system, more heat exchange areas should be allocated to the heat exchanger where flow rate difference between two fluids is relatively small. This work is important for guiding the optimization design of practical cascade heating systems.
An algorithmic framework for Mumford-Shah regularization of inverse problems in imaging
Hohm, Kilian; Storath, Martin; Weinmann, Andreas
2015-11-01
The Mumford-Shah model is a very powerful variational approach for edge preserving regularization of image reconstruction processes. However, it is algorithmically challenging because one has to deal with a non-smooth and non-convex functional. In this paper, we propose a new efficient algorithmic framework for Mumford-Shah regularization of inverse problems in imaging. It is based on a splitting into specific subproblems that can be solved exactly. We derive fast solvers for the subproblems which are key for an efficient overall algorithm. Our method neither requires a priori knowledge of the gray or color levels nor of the shape of the discontinuity set. We demonstrate the wide applicability of the method for different modalities. In particular, we consider the reconstruction from Radon data, inpainting, and deconvolution. Our method can be easily adapted to many further imaging setups. The relevant condition is that the proximal mapping of the data fidelity can be evaluated a within reasonable time. In other words, it can be used whenever classical Tikhonov regularization is possible.
Bao, Xingxian; Cao, Aixia; Zhang, Jing
2016-07-01
Modal parameters estimation plays an important role for structural health monitoring. Accurately estimating the modal parameters of structures is more challenging as the measured vibration response signals are contaminated with noise. This study develops a mathematical algorithm of solving the partially described inverse singular value problem (PDISVP) combined with the complex exponential (CE) method to estimate the modal parameters. The PDISVP solving method is to reconstruct an L2-norm optimized (filtered) data matrix from the measured (noisy) data matrix, when the prescribed data constraints are one or several sets of singular triplets of the matrix. The measured data matrix is Hankel structured, which is constructed based on the measured impulse response function (IRF). The reconstructed matrix must maintain the Hankel structure, and be lowered in rank as well. Once the filtered IRF is obtained, the CE method can be applied to extract the modal parameters. Two physical experiments, including a steel cantilever beam with 10 accelerometers mounted, and a steel plate with 30 accelerometers mounted, excited by an impulsive load, respectively, are investigated to test the applicability of the proposed scheme. In addition, the consistency diagram is proposed to exam the agreement among the modal parameters estimated from those different accelerometers. Results indicate that the PDISVP-CE method can significantly remove noise from measured signals and accurately estimate the modal frequencies and damping ratios.
Llibre, Jaume; Ramírez, Rafael; Ramírez, Valentín
2017-09-01
We consider polynomial vector fields X with a linear type and with homogenous nonlinearities. It is well-known that X has a center at the origin if and only if X has an analytic first integral of the form H =1/2 (x2 +y2) + ∑ j = 3 ∞Hj, where Hj =Hj (x , y) is a homogenous polynomial of degree j. The classical center-focus problem already studied by H. Poincaré consists in distinguishing when the origin of X is either a center or a focus. In this paper we study the inverse center-focus problem. In particular for a given analytic function H defined in a neighborhood of the origin we want to determine the homogenous polynomials in such a way that H is a first integral of X and consequently the origin of X will be a center. We study the particular case of centers which have a local analytic first integral of the form H =1/2 (x2 +y2) (1 + ∑ j = 1 ∞ϒj) , in a neighborhood of the origin, where ϒj is a convenient homogenous polynomial of degree j, for j ≥ 1. These centers are called weak centers, they contain the class of center studied by Alwash and Lloyd, the uniform isochronous centers and the isochronous holomorphic centers, but they do not coincide with the class of isochronous centers. We give a classification of the weak centers for quadratic and cubic vector fields with homogenous nonlinearities.
Czech Academy of Sciences Publication Activity Database
Domesová, Simona; Beres, Michal
2017-01-01
Roč. 15, č. 2 (2017), s. 258-266 ISSN 1336-1376 R&D Projects: GA MŠk LQ1602 Institutional support: RVO:68145535 Keywords : Bayesian statistics * Cross-Entropy method * Darcy flow * Gaussian random field * inverse problem Subject RIV: BA - General Mathematics http://advances.utc.sk/index.php/AEEE/article/view/2236
Savenkov, S M
2002-01-01
Using the Mueller matrix representation in the basis of the matrices of amplitude and phase anisotropies, a generalized solution of the inverse problem of polarimetry for deterministic objects on the base of incomplete Mueller matrices, which have been measured by method of three input polarization, is obtained.
Klibanov, M V
2006-01-01
A coefficient inverse problem for the non-stationary single-speed transport equation for t in (0,T) with the lateral boundary data and initial condition at t=0 is considered. Global uniqueness result is obtained via the method of Carleman estimates.
Music algorithm for imaging of a sound-hard arc in limited-view inverse scattering problem
Park, Won-Kwang
2017-07-01
MUltiple SIgnal Classification (MUSIC) algorithm for a non-iterative imaging of sound-hard arc in limited-view inverse scattering problem is considered. In order to discover mathematical structure of MUSIC, we derive a relationship between MUSIC and an infinite series of Bessel functions of integer order. This structure enables us to examine some properties of MUSIC in limited-view problem. Numerical simulations are performed to support the identified structure of MUSIC.
Dolenko, T. A.; Burikov, S. A.; Vervald, E. N.; Efitorov, A. O.; Laptinskiy, K. A.; Sarmanova, O. E.; Dolenko, S. A.
2017-02-01
Elaboration of methods for the control of biochemical reactions with deoxyribonucleic acid (DNA) strands is necessary for the solution of one of the basic problems in the creation of biocomputers—improvement in the reliability of molecular DNA computing. In this paper, the results of the solution of the four-parameter inverse problem of laser Raman spectroscopy—the determination of the type and concentration of each of the DNA nitrogenous bases in multi-component solutions—are presented.
DEFF Research Database (Denmark)
Montoya-Martinez, Jair; Artes-Rodriguez, Antonio; Pontil, Massimiliano
2014-01-01
We consider the estimation of the Brain Electrical Sources (BES) matrix from noisy electroencephalographic (EEG) measurements, commonly named as the EEG inverse problem. We propose a new method to induce neurophysiological meaningful solutions, which takes into account the smoothness, structured...... matrix and the squared Frobenius norm of the latent source matrix. We develop an alternating optimization algorithm to solve the resulting nonsmooth-nonconvex minimization problem. We analyze the convergence of the optimization procedure, and we compare, under different synthetic scenarios...
Terekhov, Alexander V; Pesin, Yakov B; Niu, Xun; Latash, Mark L; Zatsiorsky, Vladimir M
2010-09-01
We consider the problem of what is being optimized in human actions with respect to various aspects of human movements and different motor tasks. From the mathematical point of view this problem consists of finding an unknown objective function given the values at which it reaches its minimum. This problem is called the inverse optimization problem. Until now the main approach to this problems has been the cut-and-try method, which consists of introducing an objective function and checking how it reflects the experimental data. Using this approach, different objective functions have been proposed for the same motor action. In the current paper we focus on inverse optimization problems with additive objective functions and linear constraints. Such problems are typical in human movement science. The problem of muscle (or finger) force sharing is an example. For such problems we obtain sufficient conditions for uniqueness and propose a method for determining the objective functions. To illustrate our method we analyze the problem of force sharing among the fingers in a grasping task. We estimate the objective function from the experimental data and show that it can predict the force-sharing pattern for a vast range of external forces and torques applied to the grasped object. The resulting objective function is quadratic with essentially non-zero linear terms.
Directory of Open Access Journals (Sweden)
Marc H. V. Van Regenmortel
2018-01-01
Full Text Available Hypotheses and theories are essential constituents of the scientific method. Many vaccinologists are unaware that the problems they try to solve are mostly inverse problems that consist in imagining what could bring about a desired outcome. An inverse problem starts with the result and tries to guess what are the multiple causes that could have produced it. Compared to the usual direct scientific problems that start with the causes and derive or calculate the results using deductive reasoning and known mechanisms, solving an inverse problem uses a less reliable inductive approach and requires the development of a theoretical model that may have different solutions or none at all. Unsuccessful attempts to solve inverse problems in HIV vaccinology by reductionist methods, systems biology and structure-based reverse vaccinology are described. The popular strategy known as rational vaccine design is unable to solve the multiple inverse problems faced by HIV vaccine developers. The term “rational” is derived from “rational drug design” which uses the 3D structure of a biological target for designing molecules that will selectively bind to it and inhibit its biological activity. In vaccine design, however, the word “rational” simply means that the investigator is concentrating on parts of the system for which molecular information is available. The economist and Nobel laureate Herbert Simon introduced the concept of “bounded rationality” to explain why the complexity of the world economic system makes it impossible, for instance, to predict an event like the financial crash of 2007–2008. Humans always operate under unavoidable constraints such as insufficient information, a limited capacity to process huge amounts of data and a limited amount of time available to reach a decision. Such limitations always prevent us from achieving the complete understanding and optimization of a complex system that would be needed to achieve a truly
Directory of Open Access Journals (Sweden)
Rita C. O. Sebastião
2011-01-01
Full Text Available A neural network procedure to solve inverse chemical kinetic problems is discussed in this work. Rate constants are calculated from the product concentration of an irreversible consecutive reaction: the hydrogenation of Citral molecule, a process with industrial interest. Simulated and experimental data are considered. Errors in the simulated data, up to 7% in the concentrations, were assumed to investigate the robustness of the inverse procedure. Also, the proposed method is compared with two common methods in nonlinear analysis; the Simplex and Levenberg-Marquardt approaches. In all situations investigated, the neural network approach was numerically stable and robust with respect to deviations in the initial conditions or experimental noises.
Energy Technology Data Exchange (ETDEWEB)
Chen, Wen-Lih; Yang, Yu-Ching; Chang, Win-Jin; Lee, Haw-Long [Clean Energy Center, Department of Mechanical Engineering, Kun Shan University, Yung-Kang City, Tainan 710-03 (China)
2008-08-15
In this study, a conjugate gradient method based inverse algorithm is applied to estimate the unknown space and time dependent heat transfer rate on the external wall of a pipe system using temperature measurements. It is assumed that no prior information is available on the functional form of the unknown heat transfer rate; hence, the procedure is classified as function estimation in the inverse calculation. The accuracy of the inverse analysis is examined by using simulated exact and inexact temperature measurements. Results show that an excellent estimation of the space and time dependent heat transfer rate can be obtained for the test case considered in this study. (author)
I Think I See the Light Curve: The Good (and Bad) of Exoplanetary Inverse Problems
Schwartz, Joel Colin
Planets and planetary systems change in brightness as a function of time. These "light curves" can have several features, including transits where a planet blocks some starlight, eclipses where a star obscures a planet's flux, and rotational variations where a planet reflects light differently as it spins. One can measure these brightness changes--which encode radii, temperatures, and more of planets--using current and planned telescopes. But interpreting light curves is an inverse problem: one has to extract astrophysical signals from the effects of imperfect instruments. In this thesis, I first present a meta study of planetary eclipses taken with the Spitzer Space Telescope. We find that eclipse depth uncertainties may be overly precise, especially those in early Spitzer papers. I then offer the first rigorous test of BiLinearly-Interpolated Subpixel Sensitivity (BLISS) mapping, which is widely used to model detector systematics of Spitzer. We show that this ad hoc method is not statistically sound, but it performs adequately in many real-life scenarios. Next, I present the most comprehensive empirical analysis to date on the energy budgets and bulk atmospherics of hot Jupiters. We find that dayside and nightside measurements suggest many hot Jupiters have reflective clouds in the infrared, and that day-night heat transport decreases as these planets are irradiated more. I lastly describe a semi-analytical model for how a planet's surfaces, clouds, and orbital geometry imprint on a light curve. We show that one can strongly constrain a planet's spin axis--and even spin direction--from modest high-precision data. Importantly, these methods will be useful for temperate, terrestrial planets with the launch of the James Webb Space Telescope and beyond.
Chaikovsky, A.; Dubovik, O.; Holben, Brent N.; Bril, A.; Goloub, P.; Tanre, D.; Pappalardo, G.; Wandinger, U.; Chaikovskaya, L.; Denisov, S.;
2015-01-01
This paper presents a detailed description of LIRIC (LIdar-Radiometer Inversion Code)algorithm for simultaneous processing of coincident lidar and radiometric (sun photometric) observations for the retrieval of the aerosol concentration vertical profiles. As the lidar radiometric input data we use measurements from European Aerosol Re-search Lidar Network (EARLINET) lidars and collocated sun-photometers of Aerosol Robotic Network (AERONET). The LIRIC data processing provides sequential inversion of the combined lidar and radiometric data by the estimations of column-integrated aerosol parameters from radiometric measurements followed by the retrieval of height-dependent concentrations of fine and coarse aerosols from lidar signals using integrated column characteristics of aerosol layer as a priori constraints. The use of polarized lidar observations allows us to discriminate between spherical and non-spherical particles of the coarse aerosol mode. The LIRIC software package was implemented and tested at a number of EARLINET stations. Inter-comparison of the LIRIC-based aerosol retrievals was performed for the observations by seven EARLNET lidars in Leipzig, Germany on 25 May 2009. We found close agreement between the aerosol parameters derived from different lidars that supports high robustness of the LIRIC algorithm. The sensitivity of the retrieval results to the possible reduction of the available observation data is also discussed.
An inverse problem in simultaneous estimating the Biot numbers of heat and moisture transfer for a porous material
Energy Technology Data Exchange (ETDEWEB)
Cheng-Hung Huang; Chun-Ying Yeh [National Cheng Kung University, Tainan, Taiwan (China). Department of Naval Architecture and Marine Engineering
2002-11-01
A conjugate gradient method based inverse algorithm is applied in the present study in simultaneous determining the unknown time-dependent Biot numbers of heat and moisture transfer for a porous material based on interior measurements of temperature and moisture. It is assumed that no prior information is available on the functional form of the unknown Biot numbers in the present study, thus, it is classified as the function estimation in inverse calculation. The accuracy of this inverse heat and moisture transfer problem is examined by using the simulated exact and inexact temperature and moisture measurements in the numerical experiments. Results show that the estimation on the time-dependent Biot numbers can be obtained with any arbitrary initial guesses on a Pentium IV 1.4 GHz personal computer. (author)
Directory of Open Access Journals (Sweden)
Charyyar Ashyralyyev
2017-08-01
Full Text Available In this work, we consider an inverse elliptic problem with Bitsadze-Samarskii type multipoint nonlocal and Neumann boundary conditions. We construct the first and second order of accuracy difference schemes (ADSs for problem considered. We stablish stability and coercive stability estimates for solutions of these difference schemes. Also, we give numerical results for overdetermined elliptic problem with multipoint Bitsadze-Samarskii type nonlocal and Neumann boundary conditions in two and three dimensional test examples. Numerical results are carried out by MATLAB program and brief explanation on the realization of algorithm is given.
S.-C. Fang; J. Han; Z. Huang (Zhen); S.I. Birbil (Ilker)
2002-01-01
textabstractBy using a smooth entropy function to approximate the non-smooth max-type function, a vertical linear complementarity problem (VLCP) can be treated as a family of parameterized smooth equations. A Newton-type method with a testing procedure is proposed to solve such a system. We show
S.I. Birbil (Ilker); S-C. Fang (Shu-Cherng); J. Han
2002-01-01
textabstractBy using a smooth entropy function to approximate the non-smooth max-type function, a vertical linear complementarity problem (VLCP) can be treated as a family of parameterized smooth equations. A Newton-type method with a testing procedure is proposed to solve such a system. We show
Eichardt, Roland; Baumgarten, Daniel; Petković, Bojana; Wiekhorst, Frank; Trahms, Lutz; Haueisen, Jens
2012-10-01
The problem of estimating magnetic nanoparticle distributions from magnetorelaxometric measurements is addressed here. The objective of this work was to identify source grid parameters that provide a good condition for the related linear inverse problem. The parameters investigated here were the number of sources, the extension of the source grid, and the source direction. A new measure of the condition, the ratio between the largest and mean singular value of the lead field matrix, is proposed. Our results indicated that the source grids should be larger than the sensor area. The sources and, consequently, the magnetic excitation field, should be directed toward the Z-direction. For underdetermined linear inverse problems, such as in our application, the number of sources affects the condition to a relatively small degree. Overdetermined magnetostatic linear inverse problems, however, benefit from a reduction in the number of sources, which considerably improves the condition. The adapted source grids proposed here were used to estimate the magnetostatic dipole from simulated data; the L2-norm, residual, and distances between the estimated and simulated sources were significantly reduced.
Assimaki, D.; Tsuda, K.; Oakes, J.; Steidl, J.
2004-12-01
A seismic waveform inversion algorithm is demonstrated for the estimation of elastic soil properties from one-dimensional downhole array recordings. For a given bedrock motion, scarcity of near-surface geotechnical information, error propagation and limited resolution of the continuum usually result in predictions of surface ground motion that poorly compare with low amplitude observations. This discrepancy is further aggravated for strong ground motion, associated with hysteretic, nonlinear, and potentially irreversible material deformations. Seismogram inversion is a nonlinear multi-parameter optimization problem. Traditional search techniques that use characteristics of the problem to determine the next sampling point (e.g. gradients, Hessians, linearity and continuity) are computationally efficient, yet limited to convex regular functions. As a result, they fail to identify the best fit solution in seismogram inversion problems, when the starting model is too far from the global optimal solution. On the other hand, stochastic search techniques (e.g. genetic algorithms, simulated annealing) have been shown to efficiently identify promising regions in the search space, but perform very poorly in a localized search. The proposed inversion technique is a two-step process, namely a genetic algorithm in the wavelet domain in series with a nonlinear least-square fit in the frequency domain; we thus improve the computational efficiency of the former, while avoiding the pitfalls of using local linearization techniques such as the latter for the optimization of multi-modal, discontinuous and non-differentiable functions. The parameters to be estimated are stepwise variations of the shear modulus, attenuation and density with depth, for horizontally layered media with refined near-surface discretization. Equality constrains are imposed on the vector of unknowns to bound the search space, based on the available soil investigation. For the genetic algorithm, the objective
Dorn, Oliver; Lionheart, Bill
2010-11-01
any successful inversion, whereas the other three papers discuss novel inversion techniques for specific applications. In the first contribution, with the title A Novel Simplified Mathematical Model for Antennas used in Medical Imaging Applications, the authors M J Fernando, M Elsdon, K Busawon and D Smith discuss a new technique for modelling the current across a monopole antenna from which the radiation fields of the antenna can be calculated very efficiently in specific medical imaging applications. This new technique is then tested on two examples, a quarter wavelength and a three quarter wavelength monopole antenna. The next contribution, with the title An investigation into the use of a mixture model for simulating the electrical properties of soil with varying effective saturation levels for sub-soil imaging using ECT by R R Hayes, P A Newill, F J W Podd, T A York, B D Grieve and O Dorn, considers the development of a new visualization tool for monitoring soil moisture content surrounding certain seed breeder plants. An electrical capacitance tomography technique is employed for verifying how efficiently each plant utilises the water and nutrients available in the surrounding soil. The goal of this study is to help in developing and identifying new drought tolerant food crops. In the third contribution Combination of Maximin and Kriging Prediction Methods for Eddy-Current Testing Database Generation by S Bilicz, M Lambert, E Vazquez and S Gyimóthy, a novel database generation technique is proposed for its use in solving inverse eddy-current testing problems. For avoiding expensive repeated forward simulations during the creation of this database, a kriging interpolation technique is employed for filling uniformly the data output space with sample points. Mathematically this is achieved by using a maximin formalism. The paper 2.5D inversion of CSEM data in a vertically anisotropic earth by C Ramananjaona and L MacGregor considers controlled
DEFF Research Database (Denmark)
Fukshansky-Kazarinova, N.; Fukshansky, L.; Kuhl, M.
1998-01-01
A method for the solution of the inverse problem of radiative transfer is presented which utilizes the internal fluxes measured at different depths and in different directions with optical radiance microprobes in dense multiple scattering media. The method yields optical cross-sections and the ph......A method for the solution of the inverse problem of radiative transfer is presented which utilizes the internal fluxes measured at different depths and in different directions with optical radiance microprobes in dense multiple scattering media. The method yields optical cross......-sections and the phase function for the sample even when these parameters are depth dependent. The sensitivity analysis shows that the theoretical errors caused by the finite number of measurements as well as by the non-uniform directional sensitivity of the microprobes can be held on a low level; even the fourth...
Solving the inverse Ising problem by mean-field methods in a clustered phase space with many states.
Decelle, Aurélien; Ricci-Tersenghi, Federico
2016-07-01
In this work we explain how to properly use mean-field methods to solve the inverse Ising problem when the phase space is clustered, that is, many states are present. The clustering of the phase space can occur for many reasons, e.g., when a system undergoes a phase transition, but also when data are collected in different regimes (e.g., quiescent and spiking regimes in neural networks). Mean-field methods for the inverse Ising problem are typically used without taking into account the eventual clustered structure of the input configurations and may lead to very poor inference (e.g., in the low-temperature phase of the Curie-Weiss model). In this work we explain how to modify mean-field approaches when the phase space is clustered and we illustrate the effectiveness of our method on different clustered structures (low-temperature phases of Curie-Weiss and Hopfield models).
Energy Technology Data Exchange (ETDEWEB)
Barenboim, Gabriela, E-mail: Gabriela.Barenboim@uv.es; Park, Wan-Il, E-mail: Wanil.Park@uv.es
2016-08-10
We investigate the gravitational wave background from a first order phase transition in a matter-dominated universe, and show that it has a unique feature from which important information about the properties of the phase transition and thermal history of the universe can be easily extracted. Also, we discuss the inverse problem of such a gravitational wave background in view of the degeneracy among macroscopic parameters governing the signal.
Vatankhah, Saeed; Renaut, Rosemary A.; Ardestani, Vahid E.
2018-01-01
We present a fast algorithm for the total variation regularization of the 3-D gravity inverse problem. Through imposition of the total variation regularization, subsurface structures presenting with sharp discontinuities are preserved better than when using a conventional minimum-structure inversion. The associated problem formulation for the regularization is non linear but can be solved using an iteratively reweighted least squares algorithm. For small scale problems the regularized least squares problem at each iteration can be solved using the generalized singular value decomposition. This is not feasible for large, or even moderate, scale problems. Instead we introduce the use of a randomized generalized singular value decomposition in order to reduce the dimensions of the problem and provide an effective and efficient solution technique. For further efficiency an alternating direction algorithm is used to implement the total variation weighting operator within the iteratively reweighted least squares algorithm. Presented results for synthetic examples demonstrate that the novel randomized decomposition provides good accuracy for reduced computational and memory demands as compared to use of classical approaches.
Directory of Open Access Journals (Sweden)
Ali Mohammad-Djafari
2015-06-01
Full Text Available The main content of this review article is first to review the main inference tools using Bayes rule, the maximum entropy principle (MEP, information theory, relative entropy and the Kullback–Leibler (KL divergence, Fisher information and its corresponding geometries. For each of these tools, the precise context of their use is described. The second part of the paper is focused on the ways these tools have been used in data, signal and image processing and in the inverse problems, which arise in different physical sciences and engineering applications. A few examples of the applications are described: entropy in independent components analysis (ICA and in blind source separation, Fisher information in data model selection, different maximum entropy-based methods in time series spectral estimation and in linear inverse problems and, finally, the Bayesian inference for general inverse problems. Some original materials concerning the approximate Bayesian computation (ABC and, in particular, the variational Bayesian approximation (VBA methods are also presented. VBA is used for proposing an alternative Bayesian computational tool to the classical Markov chain Monte Carlo (MCMC methods. We will also see that VBA englobes joint maximum a posteriori (MAP, as well as the different expectation-maximization (EM algorithms as particular cases.
Derevtsov, E. Yu; Louis, A. K.; Maltseva, S. V.; Polyakova, A. P.; Svetov, I. E.
2017-12-01
A problem of reconstruction of 2D vector or symmetric 2-tensor fields by their known ray transforms is considered. Two numerical approaches based on the method of approximate inverse are suggested for solving the problem. The first method allows to recover components of a vector or tensor field, and the second reconstructs its potentials in the sense of feature reconstruction, where the observation operator assigns to a field its potential. Numerical simulations show good results of reconstruction of the sought-for fields or their solenoidal or potential parts from its ray transforms.
Directory of Open Access Journals (Sweden)
Hetmaniok Edyta
2015-01-01
Full Text Available The paper proposes a procedure for solving the inverse Stefan problem consisted in reconstruction of the function describing the heat transfer coefficient on the basis of temperature measurements. Elaborated method is based on two procedures: solution of the appropriate direct Stefan problem by using the finite difference method combined with the alternating phase truncation method and minimization of some functional with the aid of invasive weed optimization algorithm. For verifying the effectiveness of investigated algorithm the experimental data obtained in the solidification of aluminum are used.
Energy Technology Data Exchange (ETDEWEB)
Huang, Cheng-Hung; Lo, Hung-Chi [Department of Systems and Naval Mechatronic Engineering, National Cheng Kung University, 1 Ta-Hsueh Road, Tainan 701, (Taiwan)
2006-10-15
The time-dependent heat flux generated in rotor and stator for the high speed electric motor is determined in this three-dimensional inverse heat conduction problem. The inverse algorithm utilizing the Steepest Descent Method (SDM) and a general purpose commercial code CFX4.4 is applied successfully in the present study in accordance with the simulated measured temperature distributions on some proper exterior surfaces. No cooling systems can be designed before the heat fluxes are estimated and identified. Two different functional forms for heat fluxes with different temperature measurement errors are used in the numerical experiments to illustrate the validity of the inverse algorithm. Results of the numerical simulation show that due to the structure of the cooling passages for motor housing, the estimated heat flux lying under the cooling passages is not accurate. However, when the concept of effective heat flux is applied, a reliable time-dependent heat flux can be obtained by using the present inverse algorithm. (author)
Directory of Open Access Journals (Sweden)
Maciejewska Beata
2012-04-01
Full Text Available The aim of this paper is to determine the boiling heat transfer coefficient for the cooling liquid flow in a rectangular minichannel with asymmetric heating. The main part of the test section is made up of a vertical minichannel of 1.0 mm depth. The heating foil on the side of the fluid flowing in the minichannel is singlesided enhanced on the selected area. The experiment is carried out with FC-72. The investigations focus on the transition from single-phase forced convection to nucleate boiling, that is, from the zone of boiling incipience further to developed boiling. Owing to the liquid crystal layer located on the heating surface contacting the glass, it is possible to measure the heating wall temperature distribution while increasing the heat flux transferred to the liquid flowing in the minichannel. The objective of the calculations is to evaluate a heat transfer model and numerical approach to solving the inverse boundary problem, and to calculate the heat transfer coefficient. This problem has been solved by means the finite element method in combination with Trefftz functions (FEMT. Trefftz functions are used to construct base functions in Hermite space of the finite element.
Directory of Open Access Journals (Sweden)
В. А. Куликов
2017-03-01
Full Text Available Electrical methods of exploration are widely applied in prospecting and estimation of ore mineral resources. It is not always that geoelectrical models obtained in the course of interpretation of different types of electric and electromagnetic sounding are in line with each other. This leads to difficulties in geological interpretation of electrical exploration results. In single cases a geological model can be built that with great precision satisfies data from different electrical explorations, for instance, results of geometric and inductive electromagnetic soundings. For this purpose an algorithm of combined inversion of electrotomographic and audio-megnetotellurgic sounding data has been developed and implemented by A.E.Kaminskii in software ZondRes2D. Advantage of combined inversion has been shown for investigation of sections up till 400-500 m deep on synthetic models and actual field data.
Energy Technology Data Exchange (ETDEWEB)
Lopez, C.; Koski, J.A.; Razani, A.
2000-01-06
A study of the errors introduced when one-dimensional inverse heat conduction techniques are applied to problems involving two-dimensional heat transfer effects was performed. The geometry used for the study was a cylinder with similar dimensions as a typical container used for the transportation of radioactive materials. The finite element analysis code MSC P/Thermal was used to generate synthetic test data that was then used as input for an inverse heat conduction code. Four different problems were considered including one with uniform flux around the outer surface of the cylinder and three with non-uniform flux applied over 360{degree}, 180{degree}, and 90{degree} sections of the outer surface of the cylinder. The Sandia One-Dimensional Direct and Inverse Thermal (SODDIT) code was used to estimate the surface heat flux of all four cases. The error analysis was performed by comparing the results from SODDIT and the heat flux calculated based on the temperature results obtained from P/Thermal. Results showed an increase in error of the surface heat flux estimates as the applied heat became more localized. For the uniform case, SODDIT provided heat flux estimates with a maximum error of 0.5% whereas for the non-uniform cases, the maximum errors were found to be about 3%, 7%, and 18% for the 360{degree}, 180{degree}, and 90{degree} cases, respectively.
Nguyen, Dinh-Liem; Klibanov, Michael V.; Nguyen, Loc H.; Kolesov, Aleksandr E.; Fiddy, Michael A.; Liu, Hui
2017-09-01
We analyze in this paper the performance of a newly developed globally convergent numerical method for a coefficient inverse problem for the case of multi-frequency experimental backscatter data associated to a single incident wave. These data were collected using a microwave scattering facility at the University of North Carolina at Charlotte. The challenges for the inverse problem under the consideration are not only from its high nonlinearity and severe ill-posedness but also from the facts that the amount of the measured data is minimal and that these raw data are contaminated by a significant amount of noise, due to a non-ideal experimental setup. This setup is motivated by our target application in detecting and identifying explosives. We show in this paper how the raw data can be preprocessed and successfully inverted using our inversion method. More precisely, we are able to reconstruct the dielectric constants and the locations of the scattering objects with a good accuracy, without using any advanced a priori knowledge of their physical and geometrical properties.
PREFACE: 6th International Conference on Inverse Problems in Engineering: Theory and Practice
Bonnet, Marc
2008-07-01
The 6th International Conference on Inverse Problems in Engineering: Theory and Practice (ICIPE 2008) belongs to a successful series of conferences held up to now following a three-year cycle. Previous conferences took place in Palm Coast, Florida, USA (1993), Le Croisic, France (1996), Port Ludlow, Washington, USA (1999), Angra dos Reis, Brazil (2002), and Cambridge, UK (2005). The conference has its roots on the informal seminars organized by Professor J V Beck at Michigan State University, which were initiated in 1987. The organization of this Conference, which took place in Dourdan (Paris) France, 15-19 June 2008, was made possible through a joint effort by four research departments from four different universities: LEMTA (Laboratoire de Mécanique Théorique et Appliquée, Nancy-Université) LMS (Laboratoire de Mécanique des Solides, Ecole Polytechnique, Paris) LMAC (Laboratoire de Mathématiques Appliquées, UTC Compiègne) LTN (Laboratoire de Thermocinétique, Université de Nantes) It received support from three organizations: SFT (Société Française de Thermique: French Heat Transfer Association) ACSM (Association Calcul de Structures et Simulation : Computational Structural Mechanics Association) GdR Ondes - CNRS (`Waves' Network, French National Center for Scientific Research) The objective of the conference was to provide the opportunity for interaction and cross-fertilization between designers of inverse methods and practitioners. The delegates came from very different fields, such as applied mathematics, heat transfer, solid mechanics, tomography.... Consequently the sessions were organised along mostly methodological topics in order to facilitate interaction among participants who might not meet otherwise. The present proceedings, published in the Journal of Physics: Conference Series, gathers the four plenary invited lectures and the full-length versions of 103 presentations. The latter have been reviewed by the scientific committee (see
Djebbi, Ramzi
2014-08-05
Multi-parameter inversion in anisotropic media suffers from the inherent trade-off between the anisotropic parameters, even under the acoustic assumption. Multi-component data, often acquired nowadays in ocean bottom acquisition and land data, provide additional information capable of resolving anisotropic parameters under the acoustic approximation assumption. Based on Born scattering approximation, we develop formulas capable of characterizing the radiation patterns for the acoustic pseudo-pure mode P-waves. Though commonly reserved for the elastic fields, we use displacement fields to constrain the acoustic vertical transverse isotropic (VTI) representation of the medium. Using the asymptotic Green\\'s functions and a horizontal reflector we derive the radiation patterns for perturbations in the anisotropic media. The radiation pattern for the anellipticity parameter η is identically zero for the horizontal displacement. This allows us to dedicate this component to invert for velocity and δ. Computing the traveltime sensitivity kernels based on the unwrapped phase confirms the radiation patterns observations, and provide the model wavenumber behavior of the update.
Finite Difference Study of MHD Stokes Problem for a Vertical Infinite ...
African Journals Online (AJOL)
The explicit finite difference method is employed to study the effects of both the Hall and ionslip currents on a free convective flow of a viscous heat generating rotating fluid past an impulsively started infinite vertical plate, to which a strong magnetic field is applied perpendicularly. The velocity (both primary and secondary) ...
Liao, Ke; Zhu, Min; Ding, Lei
2013-08-01
The present study investigated the use of transform sparseness of cortical current density on human brain surface to improve electroencephalography/magnetoencephalography (EEG/MEG) inverse solutions. Transform sparseness was assessed by evaluating compressibility of cortical current densities in transform domains. To do that, a structure compression method from computer graphics was first adopted to compress cortical surface structure, either regular or irregular, into hierarchical multi-resolution meshes. Then, a new face-based wavelet method based on generated multi-resolution meshes was proposed to compress current density functions defined on cortical surfaces. Twelve cortical surface models were built by three EEG/MEG softwares and their structural compressibility was evaluated and compared by the proposed method. Monte Carlo simulations were implemented to evaluate the performance of the proposed wavelet method in compressing various cortical current density distributions as compared to other two available vertex-based wavelet methods. The present results indicate that the face-based wavelet method can achieve higher transform sparseness than vertex-based wavelet methods. Furthermore, basis functions from the face-based wavelet method have lower coherence against typical EEG and MEG measurement systems than vertex-based wavelet methods. Both high transform sparseness and low coherent measurements suggest that the proposed face-based wavelet method can improve the performance of L1-norm regularized EEG/MEG inverse solutions, which was further demonstrated in simulations and experimental setups using MEG data. Thus, this new transform on complicated cortical structure is promising to significantly advance EEG/MEG inverse source imaging technologies. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Akcelik, Volkan [ORNL; Flath, Pearl [University of Texas, Austin; Ghattas, Omar [University of Texas, Austin; Hill, Judith C [ORNL; Van Bloemen Waanders, Bart [Sandia National Laboratories (SNL); Wilcox, Lucas [University of Texas, Austin
2011-01-01
We consider the problem of estimating the uncertainty in large-scale linear statistical inverse problems with high-dimensional parameter spaces within the framework of Bayesian inference. When the noise and prior probability densities are Gaussian, the solution to the inverse problem is also Gaussian, and is thus characterized by the mean and covariance matrix of the posterior probability density. Unfortunately, explicitly computing the posterior covariance matrix requires as many forward solutions as there are parameters, and is thus prohibitive when the forward problem is expensive and the parameter dimension is large. However, for many ill-posed inverse problems, the Hessian matrix of the data misfit term has a spectrum that collapses rapidly to zero. We present a fast method for computation of an approximation to the posterior covariance that exploits the lowrank structure of the preconditioned (by the prior covariance) Hessian of the data misfit. Analysis of an infinite-dimensional model convection-diffusion problem, and numerical experiments on large-scale 3D convection-diffusion inverse problems with up to 1.5 million parameters, demonstrate that the number of forward PDE solves required for an accurate low-rank approximation is independent of the problem dimension. This permits scalable estimation of the uncertainty in large-scale ill-posed linear inverse problems at a small multiple (independent of the problem dimension) of the cost of solving the forward problem.
ORINC: a one-dimensional implicit approach to the inverse heat conduction problem. [PWR
Energy Technology Data Exchange (ETDEWEB)
Ott, L.J.; Hedrick, R.A.
1977-10-18
The report develops an implicit solution technique to determine both the transient surface temperature and the transient surface heat flux of electrically heated rods given the power input and an ''indicated'' internal temperature during a simulated loss-of-coolant accident. A digital computer program ORINC (ORNL Inverse Code) is developed which solves a one-dimensional, transient, lumped parameter, implicit formulation of the conduction equation at each bundle thermocouple position in the Thermal-Hydraulic Test Facility (THTF).
Structural-change localization and monitoring through a perturbation-based inverse problem.
Roux, Philippe; Guéguen, Philippe; Baillet, Laurent; Hamze, Alaa
2014-11-01
Structural-change detection and characterization, or structural-health monitoring, is generally based on modal analysis, for detection, localization, and quantification of changes in structure. Classical methods combine both variations in frequencies and mode shapes, which require accurate and spatially distributed measurements. In this study, the detection and localization of a local perturbation are assessed by analysis of frequency changes (in the fundamental mode and overtones) that are combined with a perturbation-based linear inverse method and a deconvolution process. This perturbation method is applied first to a bending beam with the change considered as a local perturbation of the Young's modulus, using a one-dimensional finite-element model for modal analysis. Localization is successful, even for extended and multiple changes. In a second step, the method is numerically tested under ambient-noise vibration from the beam support with local changes that are shifted step by step along the beam. The frequency values are revealed using the random decrement technique that is applied to the time-evolving vibrations recorded by one sensor at the free extremity of the beam. Finally, the inversion method is experimentally demonstrated at the laboratory scale with data recorded at the free end of a Plexiglas beam attached to a metallic support.
Energy Technology Data Exchange (ETDEWEB)
Otero, F A; Frontini, G L; Elicabe, G E [Institute of Materials Science and Technology (INTEMA), University of Mar del Plata and National Research Council (CONICET), J B Justo 4302, 7600 Mar del Plata (Argentina)
2011-01-01
An analytic model for the scattering of a spherical particle with spherical inclusions has been proposed under the RG approximation. The model can be used without limitations to describe an X-ray scattering experiment. However, for light scattering several conditions must be fulfilled. Based on this model an inverse methodology is proposed to estimate the radii of host particle and inclusions, the number of inclusions and the Distance Distribution Functions (DDF's) of the distances between inclusions and the distances between inclusions and the origin of coordinates. The methodology is numerically tested in a light scattering example in which the host particle is eliminated by matching the refractive indices of host particle and medium. The results obtained for this cluster particle are very satisfactory.
Nazarova, L. A.; Nazarov, L. A.; Vandamme, M.; Pereira, J.-M.
2017-06-01
A geomechanical 2D model of the experiment on constrained adsorption deformation of cylindrical rock samples and a numerical-analytical method of solving the corresponding boundary-value problem based on coordinatewise averaging of the system of poroelasticity equations for the orthotropic model of the medium have been developed. It has been shown that the axial and radial deformations measured in the experiment are proportional to the volume-averaged adsorption stresses. Using the results of laboratory testing of coal samples, the coefficient inverse problem of determining the deformation characteristics and permeability of the matrix has been stated and solved. It has been revealed that Young's moduli of the latter are greater by two or three times and the permeability is at least two orders of magnitude lower than the corresponding effective values for the sample, which is caused by the natural fracturing of coals.
Directory of Open Access Journals (Sweden)
Tursun K. Yuldashev
2015-12-01
Full Text Available We consider the questions of one value solvability of the inverse problem for a nonlinear partial Fredholm type integro-differential equation of the fourth order with degenerate kernel. The method of degenerate kernel is developed for the case of inverse problem for the considering partial Fredholm type integro-differential equation of the fourth order. After denoting the Fredholm type integro-differential equation is reduced to a system of integral equations. By the aid of differentiating the system of integral equations reduced to the system of differential equations. When a certain imposed condition is fulfilled, the system of differential equations is changed to the system of algebraic equations. For the regular values of spectral parameterthe system of algebraic equations is solved by the Kramer metod. Using the given additional condition the nonlinear Volterra type integral equation of second kind with respect to main unknowing function and the nonlinear Volterra special type integral equation of first kind with respect to restore function are obtained. We use the method of successive approximations combined with the method of compressing maps. Further the restore function is defined. This paper developes the theory of Fredholm integro-differential equations with degenerate kernel.
"Pit Craters", lava tubes, and open vertical volcanic conduits in Hawaii: a problem in terminology
Directory of Open Access Journals (Sweden)
William R. Halliday
1998-01-01
Full Text Available Almost from the 1849 publication of the term pit crater, volcanologists have disagreed about the parameters differentiating these features from other vertical volcanic structures. Kaluaiki is a jameo giving entry to Thurston Lava Tube in Hawaii Volcanoes National Park. Long-standing misidentification of it as a pit crater is an example of misunderstandings arising from the lack of a clear definition of pit crater. In general, pit craters are unrelated to lava tube caves genetically, but two special cases are discussed. One probably is genetically related to a rift tube deep below the surface; the other is a complex of a small pit crater with a partial rim of accreted plates plus an ordinary-seeming lava tube cave. The term pit crater should be redefined in such a way that it excludes collapses or subsidences related to ordinary superficial lava tubes and open vertical volcanic conduits. Otherwise, a non-definition like that currently listed for agglomerate may be appropriate.
Sakhnovich, Lev A; Roitberg, Inna Ya
2013-01-01
This monograph fits theclearlyneed for books with a rigorous treatment of theinverse problems for non-classical systems and that of initial-boundary-value problems for integrable nonlinear equations. The authorsdevelop a unified treatment of explicit and global solutions via the transfer matrix function in a form due to Lev A. Sakhnovich. The book primarily addresses specialists in the field. However, it is self-contained andstarts with preliminaries and examples, and hencealso serves as an introduction for advanced graduate students in the field.
A GTA Welding Cooling Rate Analysis on Stainless Steel and Aluminum Using Inverse Problems
Directory of Open Access Journals (Sweden)
Elisan dos Santos Magalhaes
2017-01-01
Full Text Available This work presents an analysis of the thermal influence of the heat transfer by convection and radiation during GTA (gas tungsten arc welding process. The authors’ in-house C++ previously-developed code was modified to calculate the amount of heat transfer by convection and radiation. In this software, an iterative Broydon-Fletcher-Goldfarb-Shanno (BFGS inverse method was applied to estimate the amount of heat delivered to the plate when the appropriate sensitivity criteria were defined. The methodology was validated by accomplishing lab-controlled experiments on stainless steel AISI 304L and aluminum 6065 T5 plates. Due to some experimental singularities, the forced thermal convection induced by the electromagnetic field and thermal-capillary force were disregarded. Significant examples of these singularities are the relatively small weld bead when compared to the sample size and the reduced time of the welding process. In order to evaluate the local Nusselt number, empirical correlations for flat plates were used. The thermal emission was a dominant cooling effect on the aluminum cooling. However, it did not present the same behavior as the stainless steel samples. The study found that the heat losses by convection and radiation of the weld pool do not affect the cooling process significantly.
Samani, Abbas; Plewes, Donald
2007-03-07
Soft tissue elasticity has been a subject of interest in biomedical applications as an aid to medical diagnosis since the dawn of medicine. More recently, this has led to the concept of elastography with the aim of imaging the spatial distribution of tissue elasticity. Interpreting elastography images requires reliable information pertaining to elastic properties of normal and pathological tissues. Such information is either very limited or not available in the literature. Elastic modulus measurement techniques developed for soft tissues generally require tissue excision to prepare samples for testing. While this may be done with normal tissues, tumour tissue excision is generally not permissible because tumour pathological assessment requires that the tumour be kept intact. To address this limitation, we developed a system to measure the Young's modulus of tumour specimens. The technique consists of indenting the tumour specimen while measuring indentation force and displacements. To obtain the Young's modulus from the measured force-displacement slope, we developed an iterative inversion technique that uses a finite element model of the piecewise homogeneous tissue slice in each iteration. Preliminary elasticity measurement results of various breast tumours are presented and discussed. These results indicate that the proposed method is robust and highly accurate. Furthermore, they indicate that a benign lesion and malignant tumours are roughly five times and ten times stiffer than normal breast tissues respectively.
Energy Technology Data Exchange (ETDEWEB)
Samani, Abbas [Department of Medical Biophysics/Electrical and Computer Engineering, University of Western Ontario, London, Ontario, N6A 5C1 (Canada); Plewes, Donald [Department of Medical Biophysics, University of Toronto, 2075 Bayview Avenue, Toronto, Ontario, M4N 3M5 (Canada)
2007-03-07
Soft tissue elasticity has been a subject of interest in biomedical applications as an aid to medical diagnosis since the dawn of medicine. More recently, this has led to the concept of elastography with the aim of imaging the spatial distribution of tissue elasticity. Interpreting elastography images requires reliable information pertaining to elastic properties of normal and pathological tissues. Such information is either very limited or not available in the literature. Elastic modulus measurement techniques developed for soft tissues generally require tissue excision to prepare samples for testing. While this may be done with normal tissues, tumour tissue excision is generally not permissible because tumour pathological assessment requires that the tumour be kept intact. To address this limitation, we developed a system to measure the Young's modulus of tumour specimens. The technique consists of indenting the tumour specimen while measuring indentation force and displacements. To obtain the Young's modulus from the measured force-displacement slope, we developed an iterative inversion technique that uses a finite element model of the piecewise homogeneous tissue slice in each iteration. Preliminary elasticity measurement results of various breast tumours are presented and discussed. These results indicate that the proposed method is robust and highly accurate. Furthermore, they indicate that a benign lesion and malignant tumours are roughly five times and ten times stiffer than normal breast tissues respectively.
On the Inverse Problem of Finding Cosmic Strings and Other Topological Defects
Lassas, Matti; Oksanen, Lauri; Stefanov, Plamen; Uhlmann, Gunther
2017-11-01
We consider how microlocal methods developed for tomographic problems can be used to detect singularities of the Lorentzian metric of the Universe using measurements of the Cosmic Microwave Background radiation. The physical model we study is mathematically rigorous but highly idealized.
Adaptive finite element methods for the solution of inverse problems in optical tomography
Bangerth, Wolfgang; Joshi, Amit
2008-06-01
Optical tomography attempts to determine a spatially variable coefficient in the interior of a body from measurements of light fluxes at the boundary. Like in many other applications in biomedical imaging, computing solutions in optical tomography is complicated by the fact that one wants to identify an unknown number of relatively small irregularities in this coefficient at unknown locations, for example corresponding to the presence of tumors. To recover them at the resolution needed in clinical practice, one has to use meshes that, if uniformly fine, would lead to intractably large problems with hundreds of millions of unknowns. Adaptive meshes are therefore an indispensable tool. In this paper, we will describe a framework for the adaptive finite element solution of optical tomography problems. It takes into account all steps starting from the formulation of the problem including constraints on the coefficient, outer Newton-type nonlinear and inner linear iterations, regularization, and in particular the interplay of these algorithms with discretizing the problem on a sequence of adaptively refined meshes. We will demonstrate the efficiency and accuracy of these algorithms on a set of numerical examples of clinical relevance related to locating lymph nodes in tumor diagnosis.
Energy Technology Data Exchange (ETDEWEB)
Fraguela Collar, Andres; Oliveros Oliveros, Jose J.; Ivanovich Grebennikov, Alexandre [Benemerita Universidad Autonoma de Puebla, Puebla (Mexico)
2001-04-01
Techniques of the potential theory have been used to analyze the properties of the operator where the sources of current produced by electric activity in the cerebral cortex is associated with the measurements on the scalp of the electric potential generated by these sources. A medium conductor model which take in account the circle convolution of the brain has been used to prove the uniqueness of solution of the inverse problem of recuperation of activity cortical sources from electroencephalographic measurement on the scalp. This result of uniqueness is very important because we can to use algorithms of regularization. An other state the problem is presented to elaborate numerical solutions of the inverse problem using a set of discrete measurement. The stability of algorithms is showed in some examples. [Spanish] Tecnicas de la teoria de potencial han sido utilizadas para analizar las propiedades del operador que a las fuentes de corriente asociadas a la actividad electrica de las neuronas en la corteza cerebral, le hace corresponder la medicion de potencial electrico generado por dichas fuentes sobre el cuero cabelludo. Un modelo de medio conductor que toma en consideracion las circonvoluciones del cerebro ha sido utilizado para probar la unidad de solucion del problema inverso de recuperacion de las fuentes de actividad cortical a partir de las mediciones electroencefalograficas. Este resultado de unidad es fundamental ya que nos permite aplicar los metodos de regularizacion. Es presentado otro planteamiento del problema que nos permite construir soluciones numericas del problema inverso usando los datos de entrada discretos. La estabilidad de los algoritmos es ilustrada en algunos ejemplos numericos.
Semenov, Alexander; Zaikin, Oleg
2016-01-01
In this paper we propose an approach for constructing partitionings of hard variants of the Boolean satisfiability problem (SAT). Such partitionings can be used for solving corresponding SAT instances in parallel. For the same SAT instance one can construct different partitionings, each of them is a set of simplified versions of the original SAT instance. The effectiveness of an arbitrary partitioning is determined by the total time of solving of all SAT instances from it. We suggest the approach, based on the Monte Carlo method, for estimating time of processing of an arbitrary partitioning. With each partitioning we associate a point in the special finite search space. The estimation of effectiveness of the particular partitioning is the value of predictive function in the corresponding point of this space. The problem of search for an effective partitioning can be formulated as a problem of optimization of the predictive function. We use metaheuristic algorithms (simulated annealing and tabu search) to move from point to point in the search space. In our computational experiments we found partitionings for SAT instances encoding problems of inversion of some cryptographic functions. Several of these SAT instances with realistic predicted solving time were successfully solved on a computing cluster and in the volunteer computing project SAT@home. The solving time agrees well with estimations obtained by the proposed method.
Sang, Nguyen Anh; Thu Thuy, Do Thi; Loan, Nguyen Thi Ha; Lan, Nguyen Tri; Viet, Nguyen Ai
2017-06-01
Using the simple deformed three-level model (D3L model) proposed in our early work, we study the entanglement problem of composite bosons. Consider three first energy levels are known, we can get two energy separations, and can define the level deformation parameter δ. Using connection between q-deformed harmonic oscillator and Morse-like anharmonic potential, the deform parameter q also can be derived explicitly. Like the Einstein’s theory of special relativity, we introduce the observer e˙ects: out side observer (looking from outside the studying system) and inside observer (looking inside the studying system). Corresponding to those observers, the outside entanglement entropy and inside entanglement entropy will be defined.. Like the case of Foucault pendulum in the problem of Earth rotation, our deformation energy level investigation might be useful in prediction the environment e˙ect outside a confined box.
DEFF Research Database (Denmark)
Hansen, Lars Kristian
niveau med den overordnede autoritet over hele organisationen, (2) direktør niveauet med autoriteten over den administrative organisation, (3) IT-leder niveauet med den største viden om IT PPM, og (4) IT projekt niveauet som besidder de fleste resurser i IT PPM. Den horisontale deling af IT PPM er...... sammenfattet i en model bestående af 14 relaterede problemer, hvoraf de seks er rod-problemer med afgørende indvirkning på de øvrige problemer. Disse rod-problemer er: (1) svage kontrolprocesser mellem den politiske og den administrative organisation, (2) svage kontrolprocesser mellem direktør niveauet og IT...
DEFF Research Database (Denmark)
Hansen, Lars Kristian
2013-01-01
overordnede autoritet over hele organisationen, (2) direktør niveauet med autoriteten over den administrative organisation, (3) IT-leder niveauet med den største viden om IT PPM, og (4) IT projekt niveauet som besidder de fleste resurser i IT PPM. Den horisontale deling af IT PPM er beskrevet i tre faser: pre...... relaterede problemer, hvoraf de seks er rod-problemer med afgørende indvirkning på de øvrige problemer. Disse rod-problemer er: (1) svage kontrolprocesser mellem den politiske og den administrative organisation, (2) svage kontrolprocesser mellem direktør niveauet og IT-chef niveauet, (3) mangel på...
Directory of Open Access Journals (Sweden)
Jonathan E. Leightner
2012-01-01
Full Text Available The omitted variables problem is one of regression analysis’ most serious problems. The standard approach to the omitted variables problem is to find instruments, or proxies, for the omitted variables, but this approach makes strong assumptions that are rarely met in practice. This paper introduces best projection reiterative truncated projected least squares (BP-RTPLS, the third generation of a technique that solves the omitted variables problem without using proxies or instruments. This paper presents a theoretical argument that BP-RTPLS produces unbiased reduced form estimates when there are omitted variables. This paper also provides simulation evidence that shows OLS produces between 250% and 2450% more errors than BP-RTPLS when there are omitted variables and when measurement and round-off error is 1 percent or less. In an example, the government spending multiplier, , is estimated using annual data for the USA between 1929 and 2010.
Binary optimization for source localization in the inverse problem of ECG.
Potyagaylo, Danila; Cortés, Elisenda Gil; Schulze, Walther H W; Dössel, Olaf
2014-09-01
The goal of ECG-imaging (ECGI) is to reconstruct heart electrical activity from body surface potential maps. The problem is ill-posed, which means that it is extremely sensitive to measurement and modeling errors. The most commonly used method to tackle this obstacle is Tikhonov regularization, which consists in converting the original problem into a well-posed one by adding a penalty term. The method, despite all its practical advantages, has however a serious drawback: The obtained solution is often over-smoothed, which can hinder precise clinical diagnosis and treatment planning. In this paper, we apply a binary optimization approach to the transmembrane voltage (TMV)-based problem. For this, we assume the TMV to take two possible values according to a heart abnormality under consideration. In this work, we investigate the localization of simulated ischemic areas and ectopic foci and one clinical infarction case. This affects only the choice of the binary values, while the core of the algorithms remains the same, making the approximation easily adjustable to the application needs. Two methods, a hybrid metaheuristic approach and the difference of convex functions (DC), algorithm were tested. For this purpose, we performed realistic heart simulations for a complex thorax model and applied the proposed techniques to the obtained ECG signals. Both methods enabled localization of the areas of interest, hence showing their potential for application in ECGI. For the metaheuristic algorithm, it was necessary to subdivide the heart into regions in order to obtain a stable solution unsusceptible to the errors, while the analytical DC scheme can be efficiently applied for higher dimensional problems. With the DC method, we also successfully reconstructed the activation pattern and origin of a simulated extrasystole. In addition, the DC algorithm enables iterative adjustment of binary values ensuring robust performance.
Long, Christopher J; Purdon, Patrick L; Temereanca, Simona; Desai, Neil U; Hämäläinen, Matti S; Brown, Emery N
2011-06-01
Determining the magnitude and location of neural sources within the brain that are responsible for generating magnetoencephalography (MEG) signals measured on the surface of the head is a challenging problem in functional neuroimaging. The number of potential sources within the brain exceeds by an order of magnitude the number of recording sites. As a consequence, the estimates for the magnitude and location of the neural sources will be ill-conditioned because of the underdetermined nature of the problem. One well-known technique designed to address this imbalance is the minimum norm estimator (MNE). This approach imposes an L(2) regularization constraint that serves to stabilize and condition the source parameter estimates. However, these classes of regularizer are static in time and do not consider the temporal constraints inherent to the biophysics of the MEG experiment. In this paper we propose a dynamic state-space model that accounts for both spatial and temporal correlations within and across candidate intra-cortical sources. In our model, the observation model is derived from the steady-state solution to Maxwell's equations while the latent model representing neural dynamics is given by a random walk process. We show that the Kalman filter (KF) and the Kalman smoother [also known as the fixed-interval smoother (FIS)] may be used to solve the ensuing high-dimensional state-estimation problem. Using a well-known relationship between Bayesian estimation and Kalman filtering, we show that the MNE estimates carry a significant zero bias. Calculating these high-dimensional state estimates is a computationally challenging task that requires High Performance Computing (HPC) resources. To this end, we employ the NSF Teragrid Supercomputing Network to compute the source estimates. We demonstrate improvement in performance of the state-space algorithm relative to MNE in analyses of simulated and actual somatosensory MEG experiments. Our findings establish the
Cheng, J.; Liu, J. J.; Nakamura, G.
2005-06-01
In this paper, we present some results on the numerical realization of the probe method for the inverse scattering problem of determining an obstacle with impedance boundary condition from the near-field data. The keys are how to construct the Runge approximate function for the fundamental solutions and compute the indicator function for the boundary of an obstacle. We test the performance of the probe method for a 2D obstacle by taking the simulated Dirichlet-to-Neumann map as inversion input data. This work was partly supported by the China State Major Basic Research Project 2001CB309400). The first author is partially supported by NSF of China (nos. 10 271 032, 10 431 030), Shuguang Project and E-Institute of Shanghai Municipal Education Commission (N.E03004). The second author is partly supported by NSF of China (no. 10 371 018) and the third author is partially supported by Grant-in-Aid for Scientific Research (B) (2) (no. 14 340 038) of Japan Society of Promotion of Science.
The Adjoint Method Formulation for an Inverse Problem in the Generalized Black-Scholes Model
Directory of Open Access Journals (Sweden)
PIERRE NGNEPIEBA
2006-08-01
Full Text Available A general framework is developed to treat optimal control problems for a generalized Black-Scholes model, which is used for option pricing. The volatility function is retrieved from a set of market observations. The optimal volatility function is found by minimizing the cost functional measuring the discrepancy between the model solution (pricing and the observed market price, via the unconstrained minimization algorithm of the quasi-Newton limited memory type. The gradient is computed via the adjoint method. The effectiveness of the method is demonstrated on an European call option.
Ruggeri, Fabrizio
2016-05-12
In this work we develop a Bayesian setting to infer unknown parameters in initial-boundary value problems related to linear parabolic partial differential equations. We realistically assume that the boundary data are noisy, for a given prescribed initial condition. We show how to derive the joint likelihood function for the forward problem, given some measurements of the solution field subject to Gaussian noise. Given Gaussian priors for the time-dependent Dirichlet boundary values, we analytically marginalize the joint likelihood using the linearity of the equation. Our hierarchical Bayesian approach is fully implemented in an example that involves the heat equation. In this example, the thermal diffusivity is the unknown parameter. We assume that the thermal diffusivity parameter can be modeled a priori through a lognormal random variable or by means of a space-dependent stationary lognormal random field. Synthetic data are used to test the inference. We exploit the behavior of the non-normalized log posterior distribution of the thermal diffusivity. Then, we use the Laplace method to obtain an approximated Gaussian posterior and therefore avoid costly Markov Chain Monte Carlo computations. Expected information gains and predictive posterior densities for observable quantities are numerically estimated using Laplace approximation for different experimental setups.
Kawase, Hiroshi; Mori, Yuta; Nagashima, Fumiaki
2018-01-01
We have been discussing the validity of using the horizontal-to-vertical spectral ratios (HVRs) as a substitute for S-wave amplifications after Nakamura first proposed the idea in 1989. So far a formula for HVRs had not been derived that fully utilized their physical characteristics until a recent proposal based on the diffuse field concept. There is another source of confusion that comes from the mixed use of HVRs from earthquake and microtremors, although their wave fields are hardly the same. In this study, we compared HVRs from observed microtremors (MHVR) and those from observed earthquake motions (EHVR) at one hundred K-NET and KiK-net stations. We found that MHVR and EHVR share similarities, especially until their first peak frequency, but have significant differences in the higher frequency range. This is because microtremors mainly consist of surface waves so that peaks associated with higher modes would not be prominent, while seismic motions mainly consist of upwardly propagating plain body waves so that higher mode resonances can be seen in high frequency. We defined here the spectral amplitude ratio between them as EMR and calculated their average. We categorize all the sites into five bins by their fundamental peak frequencies in MHVR. Once we obtained EMRs for five categories, we back-calculated EHVRs from MHVRs, which we call pseudo-EHVRs (pEHVR). We found that pEHVR is much closer to EHVR than MHVR. Then we use our inversion code to invert the one-dimensional S-wave velocity structures from EHVRs based on the diffuse field concept. We also applied the same code to pEHVRs and MHVRs for comparison. We found that pEHVRs yield velocity structures much closer to those by EHVRs than those by MHVRs. This is natural since what we have done up to here is circular except for the average operation in EMRs. Finally, we showed independent examples of data not used in the EMR calculation, where better ground structures were successfully identified from p
Ion Cârstea, Cătălin; Wang, Jenn-Nan
2017-12-01
In the inverse boundary value problems of isotropic elasticity and complex conductivity, we derive estimates for the volume fraction of an inclusion whose physical parameters satisfy suitable gap conditions. For both the inclusion and the background medium we assume that the material coefficients are constant. In the elasticity case we require one measurement for the lower bound and another for the upper one. In the complex conductivity case we need three measurements for the lower bound and three for the upper. We accomplish this with the help of the ‘translation method’ which consists of perturbing the minimum principle associated with the equation by either a null-Lagrangian or a quasi-convex quadratic form.
Pollicott, Mark; Wang, Hao; Weiss, Howard Howie
2012-01-01
The transmission rate of many acute infectious diseases varies significantly in time, but the underlying mechanisms are usually uncertain. They may include seasonal changes in the environment, contact rate, immune system response, etc. The transmission rate has been thought difficult to measure directly. We present a new algorithm to compute the time-dependent transmission rate directly from prevalence data, which makes no assumptions about the number of susceptible or vital rates. The algorithm follows our complete and explicit solution of a mathematical inverse problem for SIR-type transmission models. We prove that almost any infection profile can be perfectly fitted by an SIR model with variable transmission rate. This clearly shows a serious danger of overfitting such transmission models. We illustrate the algorithm with historic UK measles data and our observations support the common belief that measles transmission was predominantly driven by school contacts.
Amano, Ken-ich
2013-01-01
Recent frequency-modulated atomic force microscopy (FM-AFM) can measure three-dimensional force distribution between a probe and a sample surface in liquid. The force distribution is, in the present circumstances, assumed to be solvation structure on the sample surface, because the force distribution and solvation structure have somewhat similar shape. However, the force distribution is exactly not the solvation structure. If we would like to obtain the solvation structure by using the liquid AFM, a method for transforming the force distribution into the solvation structure is necessary. Therefore, in this letter, we present the transforming method in a brief style. We call this method as a solution for an inverse problem, because the solvation structure is obtained at first and the force distribution is obtained next in general calculation processes. The method is formulated (mainly) by statistical mechanics of liquid.
DEFF Research Database (Denmark)
Cordua, Knud Skou; Hansen, Thomas Mejer; Lange, Katrine
.e. marginals) of the training image and a subsurface model are matched in order to obtain a solution with the same multiple-point statistics as the training image. Sequential Gibbs sampling is a simulation strategy that provides an efficient way of applying sequential simulation based algorithms as a priori...... proven to be an efficient way of obtaining multiple realizations that honor the same multiple-point statistics as the training image. The frequency matching method provides an alternative way of formulating multiple-point-based a priori models. In this strategy the pattern frequency distributions (i...... information in probabilistic inverse problems. Unfortunately, when this strategy is applied with the multiple-point-based simulation algorithm SNESIM the reproducibility of training image patterns is violated. In this study we suggest to combine sequential simulation with the frequency matching method...
Ueda, Kento; Kondoh, Jun
2017-07-01
A shear horizontal surface acoustic wave (SH-SAW) sensor can detect liquid properties, such as viscosity, density, permittivity, and conductivity. The advantage of using the SH-SAW sensors is the simultaneous detection of the mechanical and electrical properties of liquids. In this paper, we proposed a method of estimating the density and viscosity of liquids based on the inverse problem analysis. Glycerol or ethanol aqueous solutions were measured. The estimated and literature values were compared. For glycerol aqueous solutions, when the concentration is low, those values agree well. However, when the concentration is high, those values did not agree because the bulk modulus of glycerin solutions cannot be assumed as constant. On the other hand, as the bulk modulus of ethanol aqueous solutions can be assumed to be the same as that of water, the deviations between those values were small. Therefore, the proposed method is effective when the bulk modulus is assumed as constant.
Developing Academic Talent: A Problem of Vertical Integration and Discussant Reactions.
Trivelpiece, Alvin W.
The keynote address from the proceedings of the 1988 Conference on Academic Talent is presented here. The address criticizes the current educational system for its concentration on college preparatory courses that have little or no hands-on experience. It argues that the existing system does not encourage curiosity, a problem seen as so pervasive…
Mohebbi, Akbar; Dehghan, Mehdi
2010-12-01
The problem of finding the solution of partial differential equations with source control parameter has appeared increasingly in physical phenomena, for example, in the study of heat conduction process, thermo-elasticity, chemical diffusion and control theory. In this paper we present a high order scheme for determining unknown control parameter and unknown solution of parabolic inverse problem with both integral overspecialization and overspecialization at a point in the spatial domain. In these equations, we first approximate the spatial derivative with a fourth order compact scheme and reduce the problem to a system of ordinary differential equations (ODEs). Then we apply a fourth order boundary value method for the solution of resulting system of ODEs. So the proposed method has fourth order accuracy in both space and time components and is unconditionally stable due to the favorable stability property of boundary value methods. Several numerical examples and also some comparisons with other methods in the literature will be investigated to confirm the efficiency of the new procedure.
Ahn, Chi Young; Jeon, Kiwan; Park, Won-Kwang
2015-06-01
This study analyzes the well-known MUltiple SIgnal Classification (MUSIC) algorithm to identify unknown support of thin penetrable electromagnetic inhomogeneity from scattered field data collected within the so-called multi-static response matrix in limited-view inverse scattering problems. The mathematical theories of MUSIC are partially discovered, e.g., in the full-view problem, for an unknown target of dielectric contrast or a perfectly conducting crack with the Dirichlet boundary condition (Transverse Magnetic-TM polarization) and so on. Hence, we perform further research to analyze the MUSIC-type imaging functional and to certify some well-known but theoretically unexplained phenomena. For this purpose, we establish a relationship between the MUSIC imaging functional and an infinite series of Bessel functions of integer order of the first kind. This relationship is based on the rigorous asymptotic expansion formula in the existence of a thin inhomogeneity with a smooth supporting curve. Various results of numerical simulation are presented in order to support the identified structure of MUSIC. Although a priori information of the target is needed, we suggest a least condition of range of incident and observation directions to apply MUSIC in the limited-view problem.
Inverse Problems in Geosciences: Modelling the Rock Properties of an Oil Reservoir
DEFF Research Database (Denmark)
Lange, Katrine
to handle the large scale problems of the petroleum industry. But for now most of the study is based on simplified and idealised models. We have proposed a method for efficient and accurate interpolation of rock properties from seismic data. It is based on a recently published paper on interpolation of rock...... the method can be further improved by an orthogonal transformation of the attribute space. We have formulated a closed form expression of an a priori probability density function that quantifies the statistical probability of models describing the rock properties of a reservoir. This can be used to evaluate...... the probability that a model adhere to prior knowledge by having specific multiple-point statistics, for instance, learned from a training image. Existing methods efficiently sample an a priori probability density function to create a set of acceptable models; but they cannot evaluate the probability of a model...
Elsheikh, Ahmed H.
2014-02-01
A Hybrid Nested Sampling (HNS) algorithm is proposed for efficient Bayesian model calibration and prior model selection. The proposed algorithm combines, Nested Sampling (NS) algorithm, Hybrid Monte Carlo (HMC) sampling and gradient estimation using Stochastic Ensemble Method (SEM). NS is an efficient sampling algorithm that can be used for Bayesian calibration and estimating the Bayesian evidence for prior model selection. Nested sampling has the advantage of computational feasibility. Within the nested sampling algorithm, a constrained sampling step is performed. For this step, we utilize HMC to reduce the correlation between successive sampled states. HMC relies on the gradient of the logarithm of the posterior distribution, which we estimate using a stochastic ensemble method based on an ensemble of directional derivatives. SEM only requires forward model runs and the simulator is then used as a black box and no adjoint code is needed. The developed HNS algorithm is successfully applied for Bayesian calibration and prior model selection of several nonlinear subsurface flow problems. © 2013 Elsevier Inc.
Mushkin, I.; Solomon, S.
2017-10-01
We study the inverse contagion problem (ICP). As opposed to the direct contagion problem, in which the network structure is known and the question is when each node will be contaminated, in the inverse problem the links of the network are unknown but a sequence of contagion histories (the times when each node was contaminated) is observed. We consider two versions of the ICP: The strong problem (SICP), which is the reconstruction of the network and has been studied before, and the weak problem (WICP), which requires "only" the prediction (at each time step) of the nodes that will be contaminated at the next time step (this is often the real life situation in which a contagion is observed and predictions are made in real time). Moreover, our focus is on analyzing the increasing accuracy of the solution, as a function of the number of contagion histories already observed. For simplicity, we discuss the simplest (deterministic and synchronous) contagion dynamics and the simplest solution algorithm, which we have applied to different network types. The main result of this paper is that the complex problem of the convergence of the ICP for a network can be reduced to an individual property of pairs of nodes: the "false link difficulty". By definition, given a pair of unlinked nodes i and j, the difficulty of the false link (i,j) is the probability that in a random contagion history, the nodes i and j are not contaminated at the same time step (or at consecutive time steps). In other words, the "false link difficulty" of a non-existing network link is the probability that the observations during a random contagion history would not rule out that link. This probability is relatively straightforward to calculate, and in most instances relies only on the relative positions of the two nodes (i,j) and not on the entire network structure. We have observed the distribution of false link difficulty for various network types, estimated it theoretically and confronted it
Dubois, Kitsou
"Moderne dance" (as opposed to a more academic or classical dance form) uses techniques from kinesiology, anatomy and improvization which are adapted to a cultural, technological and political environment. The function of a choreographic system is to take and give a measure of the world. This includes, with the present tendency of the evolution of culture, a new "naturalism" which seeks the secrets of the body. Dance movements express in terms of space the dimension fo the infinite. It gives somehow the measure of a world within which everything is relative. Except for the speed of light, time and space are bound together by the same principle. The qualities of body awareness and specific motricity in dancers imply—besides a strict discipline—balance, coordination, muscular performance and perfect orientation, problems that astronauts also encounter in microgravity. Could chosen exercises used in modern dance technique be applied to the training of astronauts? Dancer-choreographer Kitsou Dubois has been working in this direction since 1988. She was granted a "Villa Medicis Hors Les Murs" by the French Ministry of Foreign Affairs, to carry on with her research at NASA, Houston, Tex. in April 1989. It allowed her to investigate the reality of this analogy. She intends to evaluate the dancers' subjective vertical refering to Mittelstaedt's observations on the proportional relationship between "space sickness" and some astronauts poor evaluation of the subjective vertical. This study should create a relationship between a choreographer's empirical intuition and a scientific reality.
Lan, Bo; Lowe, Michael J. S.; Dunne, Fionn P. E.
2015-10-01
A new spherical convolution approach has been presented which couples HCP single crystal wave speed (the kernel function) with polycrystal c-axis pole distribution function to give the resultant polycrystal wave speed response. The three functions have been expressed as spherical harmonic expansions thus enabling application of the de-convolution technique to enable any one of the three to be determined from knowledge of the other two. Hence, the forward problem of determination of polycrystal wave speed from knowledge of single crystal wave speed response and the polycrystal pole distribution has been solved for a broad range of experimentally representative HCP polycrystal textures. The technique provides near-perfect representation of the sensitivity of wave speed to polycrystal texture as well as quantitative prediction of polycrystal wave speed. More importantly, a solution to the inverse problem is presented in which texture, as a c-axis distribution function, is determined from knowledge of the kernel function and the polycrystal wave speed response. It has also been explained why it has been widely reported in the literature that only texture coefficients up to 4th degree may be obtained from ultrasonic measurements. Finally, the de-convolution approach presented provides the potential for the measurement of polycrystal texture from ultrasonic wave speed measurements.
Directory of Open Access Journals (Sweden)
Djamalov
2016-12-01
Full Text Available In the present work the problems of correctness of a linear inverse problem for the mixed type equation of the second kind of the second order in three-dimensional space are considered. For this problem, the theorems on existence and uniqueness of the solution are proved in certain class by «ε-regularization», Galerkin’s and of successive approximations methods.
Xue, Haile; Shen, Xueshun; Chou, Jifan
2015-10-01
Errors inevitably exist in numerical weather prediction (NWP) due to imperfect numeric and physical parameterizations. To eliminate these errors, by considering NWP as an inverse problem, an unknown term in the prediction equations can be estimated inversely by using the past data, which are presumed to represent the imperfection of the NWP model (model error, denoted as ME). In this first paper of a two-part series, an iteration method for obtaining the MEs in past intervals is presented, and the results from testing its convergence in idealized experiments are reported. Moreover, two batches of iteration tests were applied in the global forecast system of the Global and Regional Assimilation and Prediction System (GRAPES-GFS) for July-August 2009 and January-February 2010. The datasets associated with the initial conditions and sea surface temperature (SST) were both based on NCEP (National Centers for Environmental Prediction) FNL (final) data. The results showed that 6th h forecast errors were reduced to 10% of their original value after a 20-step iteration. Then, off-line forecast error corrections were estimated linearly based on the 2-month mean MEs and compared with forecast errors. The estimated error corrections agreed well with the forecast errors, but the linear growth rate of the estimation was steeper than the forecast error. The advantage of this iteration method is that the MEs can provide the foundation for online correction. A larger proportion of the forecast errors can be expected to be canceled out by properly introducing the model error correction into GRAPES-GFS.
Directory of Open Access Journals (Sweden)
Pieczyńska-Kozłowska Joanna M.
2015-12-01
Full Text Available The design process in geotechnical engineering requires the most accurate mapping of soil. The difficulty lies in the spatial variability of soil parameters, which has been a site of investigation of many researches for many years. This study analyses the soil-modeling problem by suggesting two effective methods of acquiring information for modeling that consists of variability from cone penetration test (CPT. The first method has been used in geotechnical engineering, but the second one has not been associated with geotechnics so far. Both methods are applied to a case study in which the parameters of changes are estimated. The knowledge of the variability of parameters allows in a long term more effective estimation, for example, bearing capacity probability of failure.
Pieczyńska-Kozłowska, Joanna M.
2015-12-01
The design process in geotechnical engineering requires the most accurate mapping of soil. The difficulty lies in the spatial variability of soil parameters, which has been a site of investigation of many researches for many years. This study analyses the soil-modeling problem by suggesting two effective methods of acquiring information for modeling that consists of variability from cone penetration test (CPT). The first method has been used in geotechnical engineering, but the second one has not been associated with geotechnics so far. Both methods are applied to a case study in which the parameters of changes are estimated. The knowledge of the variability of parameters allows in a long term more effective estimation, for example, bearing capacity probability of failure.
Directory of Open Access Journals (Sweden)
Richard N Henson
2011-08-01
Full Text Available We review recent methodological developments within a Parametric Empirical Bayesian (PEB framework for reconstructing intracranial sources of extracranial electroencephalographic (EEG and magnetoencephalographic (MEG data under linear Gaussian assumptions. The PEB framework offers a natural way to integrate multiple constraints (spatial priors on this inverse problem, such as those derived from different modalities (e.g., from functional magnetic resonance imaging, fMRI or from multiple replications (e.g., subjects. Using variations of the same basic generative model, we illustrate the application of PEB to three cases: 1 symmetric integration (fusion of MEG and EEG; 2 asymmetric integration of MEG or EEG with fMRI, and 3 group-optimisation of spatial priors across subjects. We evaluate these applications on multimodal data acquired from 18 subjects, focusing on energy induced by face perception within a time-frequency window of 100-220ms, 8-18Hz. We show the benefits of multi-modal, multi-subject integration in terms of the model evidence and the reproducibility (over subjects of cortical responses to faces.
Padois, Thomas; Gauthier, Philippe-Aubert; Berry, Alain
2014-12-01
Microphone arrays have become a standard technique to localize and quantify source in aeroacoustics. The simplest approach is the beamforming that provides noise source maps with large main lobe and strong side lobes at low frequency. Since a decade, the focus is set on deconvolution techniques such as DAMAS or Clean-SC. While the source map is clearly improved, these methods require a large computation time. In this paper, we propose a sound source localization technique based on an inverse problem with beamforming regularization matrix called Hybrid Method. With synthetic data, we show that the side lobes are removed and the main lobe is narrower. Moreover, if the sound noise source map provided by this method is used as input in the DAMAS process, the number of DAMAS iterations is highly reduced. The Hybrid Method is applied to experimental data obtained in a closed wind-tunnel. In both cases of acoustic or aeroacoustic data, the source is correctly detected. The proposed Hybrid Method is found simple to implement and the computation time is low if the number of scan points is reasonable.
Rakotomanga, Prisca; Soussen, Charles; Blondel, Walter C. P. M.
2017-03-01
Diffuse reflectance spectroscopy (DRS) has been acknowledged as a valuable optical biopsy tool for in vivo characterizing pathological modifications in epithelial tissues such as cancer. In spatially resolved DRS, accurate and robust estimation of the optical parameters (OP) of biological tissues is a major challenge due to the complexity of the physical models. Solving this inverse problem requires to consider 3 components: the forward model, the cost function, and the optimization algorithm. This paper presents a comparative numerical study of the performances in estimating OP depending on the choice made for each of the latter components. Mono- and bi-layer tissue models are considered. Monowavelength (scalar) absorption and scattering coefficients are estimated. As a forward model, diffusion approximation analytical solutions with and without noise are implemented. Several cost functions are evaluated possibly including normalized data terms. Two local optimization methods, Levenberg-Marquardt and TrustRegion-Reflective, are considered. Because they may be sensitive to the initial setting, a global optimization approach is proposed to improve the estimation accuracy. This algorithm is based on repeated calls to the above-mentioned local methods, with initial parameters randomly sampled. Two global optimization methods, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), are also implemented. Estimation performances are evaluated in terms of relative errors between the ground truth and the estimated values for each set of unknown OP. The combination between the number of variables to be estimated, the nature of the forward model, the cost function to be minimized and the optimization method are discussed.
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Huang Can
2014-08-01
Full Text Available In the present paper, a numerical model combining radiation and conduction for porous materials is developed based on the finite volume method. The model can be used to investigate high-temperature thermal insulations which are widely used in metallic thermal protection systems on reusable launch vehicles and high-temperature fuel cells. The effective thermal conductivities (ECTs which are measured experimentally can hardly be used separately to analyze the heat transfer behaviors of conduction and radiation for high-temperature insulation. By fitting the effective thermal conductivities with experimental data, the equivalent radiation transmittance, absorptivity and reflectivity, as well as a linear function to describe the relationship between temperature and conductivity can be estimated by an inverse problems method. The deviation between the calculated and measured effective thermal conductivities is less than 4%. Using the material parameters so obtained for conduction and radiation, the heat transfer process in multilayer thermal insulation (MTI is calculated and the deviation between the calculated and the measured transient temperatures at a certain depth in the multilayer thermal insulation is less than 6.5%.
Urmanov, Aleksey Mikhaylovich
Engineering problems are often ill-posed, i.e. cannot be solved by conventional data-driven methods such as parametric linear and nonlinear regression or neural networks. A method of regularization that is used for the solution of ill-posed problems requires an a priori choice of the regularization parameter. Several regularization parameter selection methods have been proposed in the literature, yet, none is resistant to model misspecification. Since almost all models are incorrectly or approximately specified, misspecification resistance is a valuable option for engineering applications. Each data-driven method is based on a statistical procedure which can perform well on one data set and can fail on other. Therefore, another useful feature of a data-driven method is robustness. This dissertation proposes a methodology of developing misspecification-resistant and robust regularization parameter selection methods through the use of the information complexity approach. The original contribution of the dissertation to the field of ill-posed inverse problems in engineering is a new robust regularization parameter selection method. This method is misspecification-resistant, i.e. it works consistently when the model is misspecified. The method also improves upon the information-based regularization parameter selection methods by correcting inadequate penalization of estimation inaccuracy through the use of the information complexity framework. Such an improvement makes the proposed regularization parameter selection method robust and reduces the risk of obtaining grossly underregularized solutions. A method of misspecification detection is proposed based on the discrepancy between the proposed regularization parameter selection method and its correctly specified version. A detected misspecification indicates that the model may be inadequate for the particular problem and should be revised. The superior performance of the proposed regularization parameter selection
Ben Aïcha, Ibtissem
2017-07-01
We study the stability issue in the inverse problem of determining the magnetic field and the time-dependent electric potential appearing in the Schrödinger equation, from boundary observations. We prove in dimension 3 or greater that the knowledge of the Dirichlet-to-Neumann map stably determines the magnetic field and the electric potential.
Li, Zhenhai; Nie, Chenwei; Yang, Guijun; Xu, Xingang; Jin, Xiuliang; Gu, Xiaohe
2014-10-01
Leaf area index (LAI) and LCC, as the two most important crop growth variables, are major considerations in management decisions, agricultural planning and policy making. Estimation of canopy biophysical variables from remote sensing data was investigated using a radiative transfer model. However, the ill-posed problem is unavoidable for the unique solution of the inverse problem and the uncertainty of measurements and model assumptions. This study focused on the use of agronomy mechanism knowledge to restrict and remove the ill-posed inversion results. For this purpose, the inversion results obtained using the PROSAIL model alone (NAMK) and linked with agronomic mechanism knowledge (AMK) were compared. The results showed that AMK did not significantly improve the accuracy of LAI inversion. LAI was estimated with high accuracy, and there was no significant improvement after considering AMK. The validation results of the determination coefficient (R2) and the corresponding root mean square error (RMSE) between measured LAI and estimated LAI were 0.635 and 1.022 for NAMK, and 0.637 and 0.999 for AMK, respectively. LCC estimation was significantly improved with agronomy mechanism knowledge; the R2 and RMSE values were 0.377 and 14.495 μg cm-2 for NAMK, and 0.503 and 10.661 μg cm-2 for AMK, respectively. Results of the comparison demonstrated the need for agronomy mechanism knowledge in radiative transfer model inversion.
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Britta Graewe
Full Text Available Many studies have linked the processing of different object categories to specific event-related potentials (ERPs such as the face-specific N170. Despite reports showing that object-related ERPs are influenced by visual stimulus features, there is consensus that these components primarily reflect categorical aspects of the stimuli. Here, we re-investigated this idea by systematically measuring the effects of visual feature manipulations on ERP responses elicited by both structure-from-motion (SFM-defined and luminance-defined object stimuli. SFM objects elicited a novel component at 200-250 ms (N250 over parietal and posterior temporal sites. We found, however, that the N250 amplitude was unaffected by restructuring SFM stimuli into meaningless objects based on identical visual cues. This suggests that this N250 peak was not uniquely linked to categorical aspects of the objects, but is strongly determined by visual stimulus features. We provide strong support for this hypothesis by parametrically manipulating the depth range of both SFM- and luminance-defined object stimuli and showing that the N250 evoked by SFM stimuli as well as the well-known N170 to static faces were sensitive to this manipulation. Importantly, this effect could not be attributed to compromised object categorization in low depth stimuli, confirming a strong impact of visual stimulus features on object-related ERP signals. As ERP components linked with visual categorical object perception are likely determined by multiple stimulus features, this creates an interesting inverse problem when deriving specific perceptual processes from variations in ERP components.
Wood, Nathan; Jones, Jeanne; Schelling, John; Schmidtlein, Mathew
2014-01-01
Tsunami vertical-evacuation (TVE) refuges can be effective risk-reduction options for coastal communities with local tsunami threats but no accessible high ground for evacuations. Deciding where to locate TVE refuges is a complex risk-management question, given the potential for conflicting stakeholder priorities and multiple, suitable sites. We use the coastal community of Ocean Shores (Washington, USA) and the local tsunami threat posed by Cascadia subduction zone earthquakes as a case study to explore the use of geospatial, multi-criteria decision analysis for framing the locational problem of TVE siting. We demonstrate a mixed-methods approach that uses potential TVE sites identified at community workshops, geospatial analysis to model changes in pedestrian evacuation times for TVE options, and statistical analysis to develop metrics for comparing population tradeoffs and to examine influences in decision making. Results demonstrate that no one TVE site can save all at-risk individuals in the community and each site provides varying benefits to residents, employees, customers at local stores, tourists at public venues, children at schools, and other vulnerable populations. The benefit of some proposed sites varies depending on whether or not nearby bridges will be functioning after the preceding earthquake. Relative rankings of the TVE sites are fairly stable under various criteria-weighting scenarios but do vary considerably when comparing strategies to exclusively protect tourists or residents. The proposed geospatial framework can serve as an analytical foundation for future TVE siting discussions.
Sanz, E.; Voss, C.I.
2006-01-01
Inverse modeling studies employing data collected from the classic Henry seawater intrusion problem give insight into several important aspects of inverse modeling of seawater intrusion problems and effective measurement strategies for estimation of parameters for seawater intrusion. Despite the simplicity of the Henry problem, it embodies the behavior of a typical seawater intrusion situation in a single aquifer. Data collected from the numerical problem solution are employed without added noise in order to focus on the aspects of inverse modeling strategies dictated by the physics of variable-density flow and solute transport during seawater intrusion. Covariances of model parameters that can be estimated are strongly dependent on the physics. The insights gained from this type of analysis may be directly applied to field problems in the presence of data errors, using standard inverse modeling approaches to deal with uncertainty in data. Covariance analysis of the Henry problem indicates that in order to generally reduce variance of parameter estimates, the ideal places to measure pressure are as far away from the coast as possible, at any depth, and the ideal places to measure concentration are near the bottom of the aquifer between the center of the transition zone and its inland fringe. These observations are located in and near high-sensitivity regions of system parameters, which may be identified in a sensitivity analysis with respect to several parameters. However, both the form of error distribution in the observations and the observation weights impact the spatial sensitivity distributions, and different choices for error distributions or weights can result in significantly different regions of high sensitivity. Thus, in order to design effective sampling networks, the error form and weights must be carefully considered. For the Henry problem, permeability and freshwater inflow can be estimated with low estimation variance from only pressure or only
Formalev, V. F.; Kolesnik, S. A.
2017-11-01
The authors are the first to present a closed procedure for numerical solution of inverse coefficient problems of heat conduction in anisotropic materials used as heat-shielding ones in rocket and space equipment. The reconstructed components of the thermal-conductivity tensor depend on temperature (are nonlinear). The procedure includes the formation of experimental data, the implicit gradient-descent method, the economical absolutely stable method of numerical solution of parabolic problems containing mixed derivatives, the parametric identification, construction, and numerical solution of the problem for elements of sensitivity matrices, the development of a quadratic residual functional and regularizing functionals, and also the development of algorithms and software systems. The implicit gradient-descent method permits expanding the quadratic functional in a Taylor series with retention of the linear terms for the increments of the sought functions. This substantially improves the exactness and stability of solution of the inverse problems. Software systems are developed with account taken of the errors in experimental data and disregarding them. On the basis of a priori assumptions of the qualitative behavior of the functional dependences of the components of the thermal-conductivity tensor on temperature, regularizing functionals are constructed by means of which one can reconstruct the components of the thermal-conductivity tensor with an error no higher than the error of the experimental data. Results of the numerical solution of the inverse coefficient problems on reconstruction of nonlinear components of the thermal-conductivity tensor have been obtained and are discussed.
Sakurai, Gen; Yonemura, Seiichiro; Kishimoto-Mo, Ayaka W; Murayama, Shohei; Ohtsuka, Toshiyuki; Yokozawa, Masayuki
2015-01-01
Carbon dioxide (CO2) efflux from the soil surface, which is a major source of CO2 from terrestrial ecosystems, represents the total CO2 production at all soil depths. Although many studies have estimated the vertical profile of the CO2 production rate, one of the difficulties in estimating the vertical profile is measuring diffusion coefficients of CO2 at all soil depths in a nondestructive manner. In this study, we estimated the temporal variation in the vertical profile of the CO2 production rate using a data assimilation method, the particle filtering method, in which the diffusion coefficients of CO2 were simultaneously estimated. The CO2 concentrations at several soil depths and CO2 efflux from the soil surface (only during the snow-free period) were measured at two points in a broadleaf forest in Japan, and the data were assimilated into a simple model including a diffusion equation. We found that there were large variations in the pattern of the vertical profile of the CO2 production rate between experiment sites: the peak CO2 production rate was at soil depths around 10 cm during the snow-free period at one site, but the peak was at the soil surface at the other site. Using this method to estimate the CO2 production rate during snow-cover periods allowed us to estimate CO2 efflux during that period as well. We estimated that the CO2 efflux during the snow-cover period (about half the year) accounted for around 13% of the annual CO2 efflux at this site. Although the method proposed in this study does not ensure the validity of the estimated diffusion coefficients and CO2 production rates, the method enables us to more closely approach the "actual" values by decreasing the variance of the posterior distribution of the values.
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K. Ioannidi
2014-01-01
Full Text Available We consider the problem of radiation from a vertical short (Hertzian dipole above flat lossy ground, which represents the well-known “Sommerfeld radiation problem” in the literature. The problem is formulated in a novel spectral domain approach, and by inverse three-dimensional Fourier transformation the expressions for the received electric and magnetic (EM field in the physical space are derived as one-dimensional integrals over the radial component of wavevector, in cylindrical coordinates. This formulation appears to have inherent advantages over the classical formulation by Sommerfeld, performed in the spatial domain, since it avoids the use of the so-called Hertz potential and its subsequent differentiation for the calculation of the received EM field. Subsequent use of the stationary phase method in the high frequency regime yields closed-form analytical solutions for the received EM field vectors, which coincide with the corresponding reflected EM field originating from the image point. In this way, we conclude that the so-called “space wave” in the literature represents the total solution of the Sommerfeld problem in the high frequency regime, in which case the surface wave can be ignored. Finally, numerical results are presented, in comparison with corresponding numerical results based on Norton’s solution of the problem.
The possibilities of linearized inversion of internally scattered seismic data
Aldawood, Ali
2014-08-05
Least-square migration is an iterative linearized inversion scheme that tends to suppress the migration artifacts and enhance the spatial resolution of the migrated image. However, standard least-square migration, based on imaging single scattering energy, may not be able to enhance events that are mainly illuminated by internal multiples such as vertical and nearly vertical faults. To alleviate this problem, we propose a linearized inversion framework to migrate internally multiply scattered energy. We applied this least-square migration of internal multiples to image a vertical fault. Tests on synthetic data demonstrate the ability of the proposed method to resolve a vertical fault plane that is poorly resolved by least-square imaging using primaries only. We, also, demonstrate the robustness of the proposed scheme in the presence of white Gaussian random observational noise and in the case of imaging the fault plane using inaccurate migration velocities.
Lee, Haw-Long; Chang, Win-Jin; Chen, Wen-Lih; Yang, Yu-Ching
2007-08-01
A conjugate gradient method based on inverse algorithm is applied in this study to estimate the unknown space- and time-dependent heat source in aluminum-coated tapered optical fibers for scanning near-field optical microscopy, by reading the transient temperature data at the measurement positions. No prior information is available on the functional form of the unknown heat source in the present study; thus, it is classified as the function estimation in inverse calculation. The accuracy of the inverse analysis is examined by using the simulated exact and inexact temperature measurements. Results show that an excellent estimation on the heat source and temperature distributions in the tapered optical fiber can be obtained for all the test cases considered in this study.
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Zhang Biao
2016-01-01
Full Text Available In this study, a continuous ant colony optimization algorithm on the basis of probability density function was applied to the inverse problems of one-dimensional coupled radiative and conductive heat transfer. To overcome the slow convergence of the ant colony optimization algorithm for continuous domain problems, a novel hybrid ant colony optimization and particle swarm optimization algorithm was proposed. To illustrate the performances of these algorithms, the thermal conductivity, absorption coefficient and scattering coefficient of the one-dimensional homogeneous semi-transparent medium were retrieved for several test cases. The temperature and radiative heat flux simulated by the finite volume method were served as inputs for the inverse analysis. Through function estimation and parameter estimation, the HAPO algorithm was proved to be effective and robust.
Wave-equation dispersion inversion
Li, Jing
2016-12-08
We present the theory for wave-equation inversion of dispersion curves, where the misfit function is the sum of the squared differences between the wavenumbers along the predicted and observed dispersion curves. The dispersion curves are obtained from Rayleigh waves recorded by vertical-component geophones. Similar to wave-equation traveltime tomography, the complicated surface wave arrivals in traces are skeletonized as simpler data, namely the picked dispersion curves in the phase-velocity and frequency domains. Solutions to the elastic wave equation and an iterative optimization method are then used to invert these curves for 2-D or 3-D S-wave velocity models. This procedure, denoted as wave-equation dispersion inversion (WD), does not require the assumption of a layered model and is significantly less prone to the cycle-skipping problems of full waveform inversion. The synthetic and field data examples demonstrate that WD can approximately reconstruct the S-wave velocity distributions in laterally heterogeneous media if the dispersion curves can be identified and picked. The WD method is easily extended to anisotropic data and the inversion of dispersion curves associated with Love waves.