The Experts below are selected from a list of 126924 Experts worldwide ranked by ideXlab platform
V Zalipaev - One of the best experts on this subject based on the ideXlab platform.
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dynamic Inverse Problem in a weakly laterally inhomogeneous medium theory and numerical experiment
Journal of Inverse and Ill-posed Problems, 2006Co-Authors: A S Blagovestchenskii, Yaroslav Kurylev, V ZalipaevAbstract:An Inverse Problem of wave propagation into a weakly laterally inhomogeneous medium occupying a half-space is considered in the acoustic approximation. The half-space consists of an upper layer and a semi-infinite bottom separated with an interface. An assumption of a weak lateral inhomogeneity means that the velocity of wave propagation and the shape of the interface depend weakly on the horizontal coordinates, x = (x1,x 2), in comparison with the strong dependence on the vertical coordinate, z, giving rise to a small parameter e ≪ 1. Expanding the velocity in power series with respect to e, we obtain a recurrent system of ID Inverse Problems. We provide algorithms to solve these Problems for the zero and first-order approximations. In the zero-order approximation, the corresponding 1D Inverse Problem is reduced to a system of non-linear Volterra-type integral equations. In the first-order approximation, the corresponding 1D Inverse Problem is reduced to a system of coupled linear Volterra integral equations. These equations are used for the numerical reconstruction of the velocity in both layers and the interface up to O(e2). © VSP 2006.
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Dynamic Inverse Problem in a weakly laterally inhomogeneous medium: Theory and numerical experiment
Journal of Inverse and Ill-Posed Problems, 2006Co-Authors: V ZalipaevAbstract:An Inverse Problem of wave propagation into a weakly laterally inhomogeneous medium occupying a half-space is considered in the acoustic approximation. The half-space consists of an upper layer and a semi-infinite bottom separated with an interface. An assumption of a weak lateral inhomogeneity means that the velocity of wave propagation and the shape of the interface depend weakly on the horizontal coordinates, x = (x1,x 2), in comparison with the strong dependence on the vertical coordinate, z, giving rise to a small parameter ε ≪ 1. Expanding the velocity in power series with respect to ε, we obtain a recurrent system of ID Inverse Problems. We provide algorithms to solve these Problems for the zero and first-order approximations. In the zero-order approximation, the corresponding 1D Inverse Problem is reduced to a system of non-linear Volterra-type integral equations. In the first-order approximation, the corresponding 1D Inverse Problem is reduced to a system of coupled linear Volterra integral equations. These equations are used for the numerical reconstruction of the velocity in both layers and the interface up to O(ε2). © VSP 2006.
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dynamic Inverse Problem in a weakly laterally inhomogeneous medium
arXiv: Mathematical Physics, 2005Co-Authors: A S Blagovestchenskii, Yaroslav Kurylev, V ZalipaevAbstract:An Inverse Problem of wave propagation into a weakly laterally inhomogeneous medium occupying a half-space is considered in the acoustic approximation. The half-space consists of an upper layer and a semi-infinite bottom separated with an interface. An assumption of a weak lateral inhomogeneity means that the velocity of wave propagation and the shape of the interface depend weakly on the horizontal coordinates, $x=(x_1,x_2)$, in comparison with the strong dependence on the vertical coordinate, $z$, giving rise to a small parameter $\e <<1$. Expanding the velocity in power series with respect to $\e$, we obtain a recurrent system of 1D Inverse Problems. We provide algorithms to solve these Problems for the zero and first-order approximations. In the zero-order approximation, the corresponding 1D Inverse Problem is reduced to a system of non-linear Volterra-type integral equations. In the first-order approximation, the corresponding 1D Inverse Problem is reduced to a system of coupled linear Volterra integral equations. These equations are used for the numerical reconstruction of the velocity in both layers and the interface up to $O(\e^2)$.
A S Blagovestchenskii - One of the best experts on this subject based on the ideXlab platform.
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dynamic Inverse Problem in a weakly laterally inhomogeneous medium theory and numerical experiment
Journal of Inverse and Ill-posed Problems, 2006Co-Authors: A S Blagovestchenskii, Yaroslav Kurylev, V ZalipaevAbstract:An Inverse Problem of wave propagation into a weakly laterally inhomogeneous medium occupying a half-space is considered in the acoustic approximation. The half-space consists of an upper layer and a semi-infinite bottom separated with an interface. An assumption of a weak lateral inhomogeneity means that the velocity of wave propagation and the shape of the interface depend weakly on the horizontal coordinates, x = (x1,x 2), in comparison with the strong dependence on the vertical coordinate, z, giving rise to a small parameter e ≪ 1. Expanding the velocity in power series with respect to e, we obtain a recurrent system of ID Inverse Problems. We provide algorithms to solve these Problems for the zero and first-order approximations. In the zero-order approximation, the corresponding 1D Inverse Problem is reduced to a system of non-linear Volterra-type integral equations. In the first-order approximation, the corresponding 1D Inverse Problem is reduced to a system of coupled linear Volterra integral equations. These equations are used for the numerical reconstruction of the velocity in both layers and the interface up to O(e2). © VSP 2006.
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dynamic Inverse Problem in a weakly laterally inhomogeneous medium
arXiv: Mathematical Physics, 2005Co-Authors: A S Blagovestchenskii, Yaroslav Kurylev, V ZalipaevAbstract:An Inverse Problem of wave propagation into a weakly laterally inhomogeneous medium occupying a half-space is considered in the acoustic approximation. The half-space consists of an upper layer and a semi-infinite bottom separated with an interface. An assumption of a weak lateral inhomogeneity means that the velocity of wave propagation and the shape of the interface depend weakly on the horizontal coordinates, $x=(x_1,x_2)$, in comparison with the strong dependence on the vertical coordinate, $z$, giving rise to a small parameter $\e <<1$. Expanding the velocity in power series with respect to $\e$, we obtain a recurrent system of 1D Inverse Problems. We provide algorithms to solve these Problems for the zero and first-order approximations. In the zero-order approximation, the corresponding 1D Inverse Problem is reduced to a system of non-linear Volterra-type integral equations. In the first-order approximation, the corresponding 1D Inverse Problem is reduced to a system of coupled linear Volterra integral equations. These equations are used for the numerical reconstruction of the velocity in both layers and the interface up to $O(\e^2)$.
J. Malmivuo - One of the best experts on this subject based on the ideXlab platform.
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Application of lead field theory and computerized thorax modeling for the ECG Inverse Problem
2001 Conference Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2001Co-Authors: H.g. Puurtinen, J. Hyttinen, P. Kauppinen, N. Takano, P. Laarne, J. MalmivuoAbstract:The ECG Inverse Problem is a widely studied area, and several different approaches have been used to solve it. The present study introduces the reciprocally calculated lead field concept for solving the ECG Inverse Problem. The lead field approach based. on the reciprocity theorem provides a procedure to calculate the computationally heavy forward Problem by a single solution for each ECG lead. In this study, one anatomically detailed 3D FDM model of the human thorax as a volume conductor was employed for forward and Inverse estimation of ECG potentials and cardiac sources, respectively. Several equivalent dipole sources were set into the cardiac muscle and the surface potential distributions applying 12, 24, 32, 64, and 120-lead ECG electrode configurations were computed. The Inverse Problem was solved in order to localize the dipoles based on the information obtained from the simulated ECG recordings and the characteristics of the volume conductor. The dipole localization errors ranged from 2 to 5 mm depending on the number of electrodes. Thus, the lead field method appears to be applicable for the solution of the ECG Inverse Problem.
Mingfeng Jiang - One of the best experts on this subject based on the ideXlab platform.
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Effect of Cardiac Motion on Solution of the Electrocardiography Inverse Problem
IEEE Transactions on Biomedical Engineering, 2009Co-Authors: Mingfeng Jiang, Ling Xia $^*$, Guofa Shou, Stuart CrozierAbstract:Previous studies of the ECG Inverse Problem often assumed that the heart was static during the cardiac cycle; consequently, a time-dependent geometrical error was thought to be unavoidably introduced. In this paper, cardiac motion is included in solutions to the electrocardiographic Inverse Problem. Cardiac dynamics are simulated based on a previously developed biventricular model that coupled the electrical and mechanical properties of the heart, and simulated the ventricular wall motion and deformation. In the forward computation, the heart surface source model method is employed to calculate the epicardial potentials from the action potentials, and then, the simulated epicardial potentials are used to calculate body surface potentials. With the inclusion of cardiac motion, the calculated body surface potentials are more reasonable than those in the case of static assumption. In the epicardial potential-based Inverse studies, the Tikhonov regularization method is used to handle ill-posedness of the ECG Inverse Problem. The simulation results demonstrate that the solutions obtained from both the static ECG Inverse Problem and the dynamic ECG Inverse Problem approaches are approximately the same during the QRS complex period, due to the minimal deformation of the heart in this period. However, with the most obvious deformation occurring during the ST-T segment, the static assumption of heart always generates something akin to geometry noise in the ECG Inverse Problem causing the Inverse solutions to have large errors. This study suggests that the inclusion of cardiac motion in solving the ECG Inverse Problem can lead to more accurate and acceptable Inverse solutions.
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The Use of Genetic Algorithms for Solving the Inverse Problem of Electrocardiography
2006 International Conference of the IEEE Engineering in Medicine and Biology Society, 2006Co-Authors: Mingfeng Jiang, Guofa ShouAbstract:Reconstruction of the epicardial potentials from the body surface potentials constitutes one form of the ill-posed Inverse Problem of electrocardiography (ECG). In this paper, we investigate the use of genetic algorithms (GAS) for regularizing ill-posed ECG Inverse Problem. The result shows that, GAS cannot be used to regularized ill-posed Problem without additional constraints, but combined with other methods or additional information about solutions, GAS is an efficient optimization technique for solving the ill-posed Inverse Problem. We adopt the Tikhonov regularized solutions as the additional information to construct the initial populations. This investigation suggests that the GAS may provide a useful tool for ECG Inverse Problem studies
Masahiro Okamoto - One of the best experts on this subject based on the ideXlab platform.
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efficient numerical optimization algorithm based on genetic algorithm for Inverse Problem
Genetic and Evolutionary Computation Conference, 2000Co-Authors: Daisuke Tominaga, Nobuto Koga, Masahiro OkamotoAbstract:We have developed an efficient algorithm based on the Genetic Algorithm(GA) for optimization of a model of a nonlinear system. Estimation of the interaction mechanisms among system components by using experimentally observed dynamic responses (time-courses) of some of the system components is generally referred to as "Inverse Problem". The S-system, which belongs to power-law formalism, is one of the best representations to solve such an Inverse Problem; the S-system is rich enough in structure to capture all relevant dynamics. In this paper, for the purpose of solving the Inverse Problem, we introduce the GA and propose an efficient procedure for the estimation of large numbers of parameters in the S-system formalism. We applied our method to a simple oscillatory system and a gene expression network.