• Journal of IKEEE
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• v.19 no.1
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• pp.33-40
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• 2015

Inverse problem in electrical impedance tomography (EIT) is highly ill-posed therefore prior information is used to mitigate the ill-posedness. Regularization methods are often adopted in solving EIT inverse problem to have satisfactory reconstruction performance. In solving the EIT inverse problem, iterative Gauss-Newton method is generally used due to its accuracy and fast convergence. However, its performance is still suboptimal and mainly depends on the selection of regularization parameter. Although, there are few methods available to determine the regularization parameter such as L-curve method they are sometimes not applicable for all cases. Moreover, regularization parameter is a scalar and it is fixed during iteration process. Therefore, in this paper, a novel method is used to determine the regularization parameter to improve reconstruction performance. Conductivity norm is calculated at each iteration step and it used to obtain the regularization parameter which is a diagonal matrix in this case. The proposed method is applied to human thorax imaging and the reconstruction performance is compared with traditional methods. From numerical results, improved performance of proposed method is seen as compared to conventional methods.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.182-185
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• 1996

The purpose of slate estimation in power system is to estimate the best-fit Slate variables from the measurements contaminated by various kind of noise. But because the majority of state estimation modules in EMS lack the convergence characteristics, sometimes the desirable outputs can't be obtained. So, in this paper, the new algorithm using the load now output as initial values in the state estimation calculation is proposed to guarantee the convergence. And if the load now outputs were used as the initial values in the calculation, the change in each step would be small compared to the original method using the flat start point. And the Inverse Lemma is used in the algorithm to calculate the new stale in each iteration step for reducing the calculation time. The proposed algorithm was tested on the IEEE 14, 30, 118 bus systems. Eventually, we were able to verity that the differences between the results obtained by the original method and proposed method were relatively small, and the effectiveness of the proposed algorithm increased when applied to the bigger systems.

• Bulletin of the Korean Mathematical Society
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• v.55 no.2
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• pp.431-448
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• 2018

This paper is concerned with the positive definite solutions of the nonlinear matrix equation $X-A^*{\bar{X}}^{-1}A=Q$, where A, Q are given complex matrices with Q positive definite. We show that such a matrix equation always has a unique positive definite solution and if A is nonsingular, it also has a unique negative definite solution. Moreover, based on Sherman-Morrison-Woodbury formula, we derive elegant relationships between solutions of $X-A^*{\bar{X}}^{-1}A=I$ and the well-studied standard nonlinear matrix equation $Y+B^*Y^{-1}B=Q$, where B, Q are uniquely determined by A. Then several effective numerical algorithms for the unique positive definite solution of $X-A^*{\bar{X}}^{-1}A=Q$ with linear or quadratic convergence rate such as inverse-free fixed-point iteration, structure-preserving doubling algorithm, Newton algorithm are proposed. Numerical examples are presented to illustrate the effectiveness of all the theoretical results and the behavior of the considered algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.9
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• pp.566-568
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• 2014

In this letter, an MMSE based iterative soft decision interference cancellation scheme for massive MIMO systems is proposed. To reduce the complexity, the proposed scheme uses the Sherman-Morrison-Woodbury formula to compute the entire MMSE filtering vectors in one iteration by one matrix inverse operation. Simulation results show that the proposed scheme also has a comparable BER to the conventional scheme for massive MIMO systems.

• Journal of Korea Multimedia Society
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• v.22 no.9
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• pp.1029-1035
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• 2019

In this paper, a tentative Kth order Goldschmidt floating point number Nth root algorithm for K order convergence rate in one iteration is proposed by applying Taylor series to the Goldschmidt square root algorithm. Using the proposed algorithm, Nth root and Nth inverse root can be computed from iterative multiplications without division. It also predicts the error of the algorithm iteration. It iterates until the predicted error becomes smaller than the specified value. Since the proposed algorithm only performs the multiplications until the error gets smaller than a given value, it can be used to improve the performance of a floating point number Nth root unit.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.1
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• pp.65-73
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• 2007

In the inverse perturbation method, enormous computational resource was required to obtain reliable results, because all unspecified DOFs were considered as unknown variables. Thus, in the present study, a reduced system method is used to condense the unspecified DOFs by using the specified DOFs, and to improve the computational efficiency as well as the solution accuracy. In most of the conventional reduction methods, transformation errors occur in the transformation matrix between the unspecified DOFs and the specified DOFs. Thus it is hard to obtain reliable and accurate solution of inverse perturbation problems by reduction methods due to the error in the transformation matrix. This numerical trouble is resolved in the present study by adopting iterative improved reduced system(IIRS) as well as by updating the transformation matrix at every step. In this reduction method, system accuracy is related to the selection of the primary DOFs and Iteration time. And both are dependent to each other So, the two level condensation method (TLCS) is selected as Selection method of primary DOFs for increasing accuracy and reducing iteration time. Finally, numerical verification results of the present iterative inverse perturbation method (IIPM) are presented.

• Structural Engineering and Mechanics
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• v.64 no.2
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• pp.271-278
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• 2017

In this paper, we propose a new conjugate gradient method which possesses the global convergence and apply it to solve inverse problems of the dynamic loads identification. Moreover, we strictly prove the stability and convergence of the proposed method. Two engineering numerical examples are presented to demonstrate the effectiveness and speediness of the present method which is superior to the Landweber iteration method. The results of numerical simulations indicate that the proposed method is stable and effective in solving the multi-source dynamic loads identification problems of practical engineering.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.9
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• pp.3655-3671
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• 2015

In this paper, we develop a novel object tracking method based on sparse representation. First, we propose a relaxed sparse representation model, based on which the tracking problem is casted as an inverse sparse representation process. In this process, the target template is able to be sparsely approximated by all candidate samples. Second, we present an objective function that combines the sparse representation process of different fragments, the relaxed representation scheme and a weight reference prior. Based on some propositions, the proposed objective function can be solved by using an iteration algorithm. In addition, we design a tracking framework based on the proposed representation model and a simple online update manner. Finally, numerous experiments are conducted on some challenging sequences to compare our tracking method with some state-of-the-art ones. Both qualitative and quantitative results demonstrate that the proposed tracking method performs better than other competing algorithms.

• Bulletin of the Korean Mathematical Society
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• v.40 no.4
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• pp.603-611
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• 2003

In this paper we extend the definition of K-positive definite operators from linear to Frechet differentiable operators. Under this setting, we derive from the inverse function theorem a local existence and approximation results corresponding to those of Theorems land 2 of the authors [8], in an arbitrary real Banach space. Furthermore, an asymptotically K-positive definite operator is introduced and a simplified iteration sequence which converges to the unique solution of an asymptotically K-positive definite operator equation is constructed.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.4
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• pp.393-402
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• 1990

An iterative learning contol method is presented for a class of linear periodic systems, in which a parameter estimator of the system together with an inverse system model is utilized to generate the control signal at each iteration. A convergence proof is given and two numerical examples are illustrated to show the validities of the algorithm. In particular, it is shown that the method is useful for the continuous path control of robot manipulators.