• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1504-1526
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• 2018

For uplink multi-user massive MIMO systems, conventional minimum mean square error (MMSE) linear detection method achieves near-optimal performance when the number of antennas at base station is much larger than that of the single-antenna users. However, MMSE detection involves complicated matrix inversion, thus making it cumbersome to be implemented cost-effectively and rapidly. In this paper, we first summarize in detail the state-of-the-art simplified MMSE detection algorithms that circumvent the complicated matrix inversion and hence reduce the computation complexity from ${\mathcal{O}}(K^3)$ to ${\mathcal{O}}(K^2)$ or ${\mathcal{O}}(NK)$ with some certain performance sacrifice. Meanwhile, we divide the simplified algorithms into two categories, namely the matrix inversion approximation and the classical iterative linear equation solving methods, and make comparisons between them in terms of detection performance and computation complexity. In order to further optimize the detection performance of the existing detection algorithms, we propose more proper solutions to set the initial values and relaxation parameters, and present a new way of reconstructing the exact effective noise variance to accelerate the convergence speed. Analysis and simulation results verify that with the help of proper initial values and parameters, the simplified matrix inversion based detection algorithms can achieve detection performance quite close to that of the ideal matrix inversion based MMSE algorithm with only a small number of series expansions or iterations.

• Geophysics and Geophysical Exploration
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• v.8 no.2
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• pp.129-136
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• 2005

The damped least-squares inversion has become a most popular method in finding the solution in geophysical problems. Generally, the least-squares inversion is to minimize the object function which consists of data misfits and model constraints. Although both the data misfit and the model constraint take an important part in the least-squares inversion, most of the studies are concentrated on what kind of model constraint is imposed and how to select an optimum regularization parameter. Despite that each datum is recommended to be weighted according to its uncertainty or error in the data acquisition, the uncertainty is usually not available. Thus, the data weighting matrix is inevitably regarded as the identity matrix in the inversion. We present a new inversion scheme, in which the data weighting matrix is automatically obtained from the analysis of the data resolution matrix and its spread function. This approach, named 'extended active constraint balancing (EACB)', assigns a great weighting on the datum having a high resolution and vice versa. We demonstrate that by applying EACB to a two-dimensional resistivity tomography problem, the EACB approach helps to enhance both the resolution and the stability of the inversion process.

• 한국지구물리탐사학회:학술대회논문집
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• 2007.06a
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• pp.329-336
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• 2007

For scaling of the gradient of misfit function, we develop a new pseudo-Hessian matrix constructed by combining amplitude field and pseudo-Hessian matrix. Since pseudo- Hessian matrix neglects the calculation of the zero-lag auto-correlation of impulse responses in the approximate Hessian matrix, the pseudo-Hessian matrix has a limitation to scale the gradient of misfit function compared to the approximate Hessian matrix. To validate the new pseudo- Hessian matrix, we perform frequency-domain elastic full waveform inversion using this Hessian matrix. By synthetic experiments, we show that the new pseudo-Hessian matrix can give better convergence to the true model than the old one does. Furthermore, since the amplitude fields are intrinsically obtained in forward modeling procedure, we do not have to pay any extra cost to compute the new pseudo-Hessian. We think that the new pseudo-Hessian matrix can be used as an alternative of the approximate Hessian matrix of the Gauss-Newton method.

• Geophysics and Geophysical Exploration
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• v.17 no.2
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• pp.95-103
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• 2014

This paper presents a practical inversion method for recovering a three-dimensional (3D) resistivity model and static shifts simultaneously. Although this method is based on a Gauss-Newton approach that requires a sensitivity matrix, the computer time can be greatly reduced by implementing a simple and effective procedure for updating the sensitivity matrix using the Broyden's algorithm. In this research, we examine the approximate inversion procedure and the weighting factor ${\beta}$ for static shifts through inversion experiments using synthetic MT data. In methods using the full sensitivity matrix constructed only once in the iteration process, a procedure using the full sensitivity in the earlier stage is useful to produce the smallest rms data misfit. The choice of ${\beta}$ is not critical below some threshold value. Synthetic examples demonstrate that the method proposed in this paper is effective in reconstructing a 3D resistivity structure from static-shifted MT data.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2002.03a
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• pp.20-27
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• 2002

Conventional Levenberg-Marquardt's nonlinear inversion method is simply modified by taking into account the second derivatives of the Hessian matrix so as to give robust inversion results. The weight of the second derivative terms is determined by the value of so-called λ in Levenberg-Marquardt's method. The new inversion method is applied to observed data from small-to-moderate earthquakes to simultaneously evaluate the modes parameters of the stochastic point-source model in and around the Korean Peninsula. Best estimates of the stochastic model parameters are obtained along with their statistics and compared with the previous results. Overall characteristics of the model parameters are found to be more of those of interplate than intraplate tectonic region.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.11a
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• pp.201-206
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• 2000

In this work transfer function synthesis method based on FRF data of each substructure is investigated for a complex structure composed of many substructures. Though the transfer function synthesis method has superiority to analyze the characteristics of interfaces among substructures effectively, many problems arise in the computation process, especially matrix inversion process. Due to computational problems, the error between the data obtained by test and the predictions through computations is inevitable. So in this paper, computational aspects in the transfer function synthesis method are examined through a steering system problem of passenger car. For the FBS method, frequency response functions of 3 substructures are measured experimentally. Effects of several parameters such as matrix inversion method, connection conditions between substructures and off-diagonal terms on system response are studied numerically.

• Journal of the Korean earth science society
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• v.37 no.5
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• pp.277-285
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• 2016

We introduce a depth scaling strategy to improve the accuracy of frequency-domain elastic full waveform inversion (FWI) using the new pseudo-Hessian matrix for seismic data without low-frequency components. The depth scaling strategy is based on the fact that the damping factor in the Levenberg-Marquardt method controls the energy concentration in the gradient. In other words, a large damping factor makes the Levenberg-Marquardt method similar to the steepest-descent method, by which shallow structures are mainly recovered. With a small damping factor, the Levenberg-Marquardt method becomes similar to the Gauss-Newton methods by which we can resolve deep structures as well as shallow structures. In our depth scaling strategy, a large damping factor is used in the early stage and then decreases automatically with the trend of error as the iteration goes on. With the depth scaling strategy, we can gradually move the parameter-searching region from shallow to deep parts. This flexible damping factor plays a role in retarding the model parameter update for shallow parts and mainly inverting deeper parts in the later stage of inversion. By doing so, we can improve deep parts in inversion results. The depth scaling strategy is applied to synthetic data without lowfrequency components for a modified version of the SEG/EAGE overthrust model. Numerical examples show that the flexible damping factor yields better results than the constant damping factor when reliable low-frequency components are missing.

• 전기의세계
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• v.23 no.3
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• pp.43-52
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• 1974

The matrix inversion is very inefficient for computing direct solutions of the large spare systems of linear equations that arise in many network problems as a large electrical power system. Optimally ordered triangular factorization of sparse matrices is more efficient and offers the other important computational advantages in some applications with this method. The direct solutions are computed from sparse matrix factors instead of a full inverse matrix, thereby gaining a significant advantage is speed and computer memory requirements. In this paper, it is shown that the sparse matrix method is superior to the inverse matrix method to solve the linear equations of large sparse networks. In addition, it is shown that the sparse matrix method is superior to the inverse matrix method to solve the linear equations of large sparse networks. In addition, it is shown that the solutions may be applied directly to sove the load flow in an electrical power system. The result of this study should lead to many aplications including short circuit, transient stability, network reduction, reactive optimization and others.

• Geophysics and Geophysical Exploration
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• v.6 no.2
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• pp.95-100
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• 2003

In this study, we developed reflection tomography inversion algorithm using Straight Ray Technique (SRT) which can calculate travel time easily and fast for complex geological structure. The inversion process begins by setting the initial velocity model as a constant velocity model that hat only impedance boundaries. The inversion process searches a layer-interface structure model that is able to explain the given data satisfactorily by inverting to minimize data misfit. For getting optimal solution, we used Gauss-Newton method that needed constructing the approximate Hessian matrix. We also applied the Marquart-Levenberg regularization method to this inversion process to prevent solution diverging. The ability of the method to resolve typical target structures was tested in a synthetic salt dome inversion. Using the inverted velocity model, we obtained the migration image close to that of the true velocity model.

• Proceedings of the KSEEG Conference
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• 2002.04a
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• pp.167-169
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• 2002

The extended Born, or localized nonlinear approximation of integral equation (IE) solution has been applied to inverting single-hole electromagnetic (EM) data using a cylindrically symmetric model. The extended Born approximation is less accurate than a full solution but much superior to the simple Born approximation. When applied to the cylindrically symmetric model with a vertical magnetic dipole source, however, the accuracy of the extended Born approximation is greatly improved because the electric field is scalar and continuous everywhere. One of the most important steps in the inversion is the selection of a proper regularization parameter for stability. Occam's inversion (Constable et al., 1987) is an excellent method for obtaining a stable inverse solution. It is extremely slow when combined with a differential equation method because many forward simulations are needed but suitable for the extended Born solution because the Green's functions, the most time consuming part in IE methods, are repeatedly re-usable throughout the inversion. In addition, the If formulation also readily contains a sensitivity matrix, which can be revised at each iteration at little expense. The inversion algorithm developed in this study is quite stable and fast even if the optimum regularization parameter Is sought at each iteration step. Tn this paper we show inversion results using synthetic data obtained from a finite-element method and field data as well.