• 한국지구물리탐사학회:학술대회논문집
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• 2008.10a
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• pp.51-56
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• 2008

The waveform inversion for isotropic media has ever been studied since the 1980s, but there has been few studies for anisotropic media. We present a seismic waveform inversion algorithm for 2-D heterogeneous transversely isotropic structures. A cell-based finite difference algorithm for anisotropic media in time domain is adopted. The steepest descent during the non-linear iterative inversion approach is obtained by backpropagating residual errors using a reverse time migration technique. For scaling the gradient of a misfit function, we use the pseudo Hessian matrix which is assumed to neglect the zero-lag auto-correlation terms of impulse responses in the approximate Hessian matrix of the Gauss-Newton method. We demonstrate the use of these waveform inversion algorithm by applying them to a two layer model and the anisotropic Marmousi model data. With numerical examples, we show that it's difficult to converge to the true model when we assumed that anisotropic media are isotropic. Therefore, it is expected that our waveform inversion algorithm for anisotropic media is adequate to interpret real seismic exploration data.

• 한국전산유체공학회:학술대회논문집
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• 2004.03a
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• pp.83-90
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• 2004

Substructuring methods are usually used in finite element structural analyses. In this study a multi-level substructuring algorithm is developed and proposed as a possible candidate for incompressible fluid solves. Finite element formulation for incompressible flow has been stabilized by a modified residual procedure proposed by Ilinca et.al.[5]. The present algorithm consists of four stages such as a gathering stage, a condensing stage, a solving stage and a scattering stage. At each level, a predetermined number of elements are gathered and condensed to form an element of higher level. At highest level, each subdomain consists of only one super-element. Thus, the inversion process of a stiffness matrix associated with internal degrees of freedom of each subdomain has been replaced by a sequential static condensation. The global algebraic system arising feom the assembly of each subdomains is solved using Conjugate Gradient Squared(CGS) method. In this case, pre-conditioning techniques usually accompanied by iterative solvers are not needed.

• ETRI Journal
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• v.41 no.3
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• pp.298-307
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• 2019

This paper investigates the use of the inverse-free sparse Bayesian learning (SBL) approach for peak-to-average power ratio (PAPR) reduction in orthogonal frequency-division multiplexing (OFDM)-based multiuser massive multiple-input multiple-output (MIMO) systems. The Bayesian inference method employs a truncated Gaussian mixture prior for the sought-after low-PAPR signal. To learn the prior signal, associated hyperparameters and underlying statistical parameters, we use the variational expectation-maximization (EM) iterative algorithm. The matrix inversion involved in the expectation step (E-step) is averted by invoking a relaxed evidence lower bound (relaxed-ELBO). The resulting inverse-free SBL algorithm has a much lower complexity than the standard SBL algorithm. Numerical experiments confirm the substantial improvement over existing methods in terms of PAPR reduction for different MIMO configurations.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.3
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• pp.167-170
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• 2018

The method of moments(MoM) is one of the most popular integral-equation-based full-wave simulation methods, and the multi-level fast multipole method(MLFMM) algorithm can be used for its efficient calculation. When calculating the surface current on the large scatterer in the MoM or MLFMM, iterative methods for the final matrix inversion are used. Among them, BiCGstab(l) has been widely adopted due to its good convergence rate. The number of iterations can be reduced when l becomes larger, but the number of operations per iteration is increased. Herein, we analyze the computational complexity of BiCGstab(l) in the MLFMM method and propose an optimum choice of l.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.1_2
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• pp.1-9
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• 2004

The important arithmetic operations over finite fields include exponentiation, division, and inversion. An exponentiation operation can be implemented using a series of squaring and multiplication operations using a binary method, while division and inversion can be performed by the iterative application of an AB$^2$ operation. Hence, it is important to develop a fast algorithm and efficient hardware for this operations. In this paper presents new bit-serial architectures for the simultaneous computation of multiplication and squaring operations, and the computation of an $AB^2$ operation over $GF(2^m)$ generated by an irreducible AOP of degree m. The proposed architectures offer a significant improvement in reducing the hardware complexity compared with previous architectures, and can also be used as a kernel circuit for exponentiation, division, and inversion architectures. Furthermore, since the Proposed architectures include regularity and modularity, they can be easily designed on VLSI hardware and used in IC cards.

• Geophysics and Geophysical Exploration
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• v.4 no.3
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• pp.70-79
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• 2001

The integral equation method is a powerful tool for numerical electromagnetic modeling. But the difficulty of this technique is the size of the linear equations, which demands excessive memory and calculation time to invert. This limitation of the integral equation method becomes critical in inverse problem. The conventional Born approximation, where the electric field in the anomalous body is approximated by the background field, is very rapid and easy to compute. However, the technique is inaccurate when the conductivity contrast between the body and the background medium is large. Quasi-linear, quasi-analytical and extended Born approximations are novel approaches to 3-D EM modeling based on the linearization of the integral equations for scattered EM field. These approximation methods are much less time consuming than full integral equation method and more accurate than conventional Born approximation. They we, however, still approximate methods for 3-D EM modeling. Iterative series methods such as modified Born, quasi-linear and quasi-analytical can be used to increase the accuracy of various approximation methods. Comparisons of numerical performance against a full integral equation and various approximation codes show that the iterative series methods are very accurate and almost always converge. Furthermore, they are very fast and easy to implement on a computer. In this study, extended Born series method is developed and it shows more accurate result than that of other series methods. Therefore, Iterative series methods, including extended Born series, open principally new possibilities for fast and accurate 3-D EM modeling and inversion.

• Computers and Concrete
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• v.11 no.5
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• pp.441-462
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• 2013

When using the conventional finite element method, a great number of grid nodes are necessary to describe the large and uneven temperature gradients in the concrete around cooling pipes when calculating the temperature field of mass concrete with cooling pipes. In this paper, the temperature gradient properties of the concrete around a pipe were studied. A new calculation method was developed based on these properties and an explicit iterative algorithm. With a small number of grid nodes, both the temperature distribution along the cooling pipe and the temperature field of the concrete around the water pipe can be correctly calculated with this new method. In conventional computing models, the cooling pipes are regarded as the third boundary condition when solving a model of concrete with plastic pipes, which is an approximate way. At the same time, the corresponding parameters have to be got by expensive experiments and inversion. But in the proposed method, the boundary condition is described strictly, and thus is more reliable and economical. And numerical examples were used to illustrate that this method is accurate, efficient and applicable to the actual engineering.

• The Journal of Engineering Geology
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• v.2 no.1
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• pp.47-57
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• 1992

Geophysical methods applied to water seepage problem in earth-fill embankment attempt to detect and map the estimate of size and depth of the seepage path. Seepage zones generally produce lOW resistivity anomalies due to high saturation of water. Dipole-dipole resistivity surveying technique, which is actually a combined sounding-profiling procedure, was used to delineate the seepage path through this study. In this study, the finite difference methods to solve the electric potential distribution in 2 112 dimension, was adopted as the numerical scheme for the forward problem. Second order Marquart's method, one the iterative damped least square methods, was selected for the automatic inversion. The computer program was implemented in FORTRAN 77 for 1 6-bit personal computer. In this paper, we present a case history which illustrates the application of dipole-dipole resistivity method to the delineation of water flow in earth-fill structures. Also the automatic two-dimensional resistivity inversion was applied to a field data where the interpretive advantages of the program become evident.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.31A no.6
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• pp.34-44
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• 1994

In this paper, an iterative inversion method in angular spectral domain is presented for microwave imaging of a perfectly conducting cylinder. Angular spectra are calculated from measured far-field scattered fields. And then both the propagating modes and the evanescent modes are defined. The center and initial shape of an unknown conductor may be obtained by the characteristics of angular spectra and the total scattering cross section (TSCS). Finally, the orignal shape is reconstructed by the modified Newton algorithm. By using well estimated initial shape the local minima can be avoided, which might appear when the nonlinear equation is solved with Newton algorithm. It is shown to be robust to noise in scattered fields via numerical examples by keeping only the propagating modes and filtering out the evanescent modes.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.9
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• pp.35-42
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• 1998

Finding a technique to achieve high machining precision and high productivity is an important issue for CNC machining. One of the solutions to meet better performance of machining is feedrate control. In this paper we present an adaptive feedrate neuro-control method for high precision and high speed machining. The adaptive neuro-control architecture consists of a neural network identifier(NNI) and an iterative learning control algorithm with inversion of the NNI. The NNI is an identifier for the nonlinear characteristics of feedrate and contour error, which is utilized in iterative learning for adaptive feedrate control with specified contour error tolerance. The proposed neuro-control method has been successfully evaluated for machining circular, corner and involute contours by computer simulations.