• ETRI Journal
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• v.35 no.5
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• pp.931-934
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• 2013

The weight calculation in an iterative algorithm is the most computationally costly task in computed tomography image reconstruction. In this letter, a fast algorithm to speed up the weight calculation is proposed. The classic square pixel rotation approximate calculation method for computing the weights in the iterative algorithm is first analyzed and then improved by replacing the square pixel model with a circular pixel model and the square rotation approximation with a segmentation method of a circular area. Software simulation and hardware implementation results show that our proposed scheme can not only improve the definition of the reconstructed image but also accelerate the reconstruction.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.7
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• pp.355-362
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• 2003

The fault analysis problem of a distribution network has many difficulties comes from the unbalance of loads or networks and the lacks of load information. The unbalance of loads or networks make the fault location difficult when it use the classical sequence transformation. Moreover the amount of load in the distribution networks fluctuates with time. This paper introduces a recent fault location algorithm using iterative method which handle the unbalance of the problem. But, the fault location errors comes from the load fluctuations still left. For the real application of the new fault location algorithm in distribution networks, this paper studied the effect of the load fluctuations in the algorithm.

• Journal of the Korean Mathematical Society
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• v.55 no.3
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• pp.719-734
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• 2018

An image restoration problem with Poisson noise arises in many applications of medical imaging, astronomy, and microscopy. To overcome ill-posedness, Total Variation (TV) model is commonly used owing to edge preserving property. Since staircase artifacts are observed in restored smooth regions, higher-order TV regularization is introduced. However, sharpness of edges in the image is also attenuated. To compromise benefits of TV and higher-order TV, the weighted sum of the non-convex TV and non-convex higher order TV is used as a regularizer in the proposed variational model. The proposed model is non-convex and non-smooth, and so it is very challenging to solve the model. We propose an iterative reweighted algorithm with the proximal linearized alternating direction method of multipliers to solve the proposed model and study convergence properties of the algorithm.

• Journal of applied mathematics & informatics
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• v.30 no.5_6
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• pp.935-950
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• 2012

In this paper, we introduce and study a new system of generalized set-valued quasi-variational-like inclusions with (A, ${\eta}$)-accretive mapping in Banach spaces. By using the resolvent operator associated with (A, ${\eta}$)-accretive mappings, we construct a new iterative algorithm for approximating the solution of this system of variational inclusions. We also prove the existence of solutions and the convergence of the sequences generated by the algorithm in Banach spaces. The results presented in this paper extend and improve some known results in the literature.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.346-346
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• 2000

We proposed a method of second-order iterative learning control with feedback, which shows an enhancement of convergence speed and robustness to the disturbances in our previous study. In this paper, we show that the proposed second-order iterative learning control algorithm with feedback is more effective and has better convergence performance than the algorithm without feedback in the case of the existence of initial condition errors. And the convergence woof of the proposed algorithm in the case of the existence of initial condition error is given in detail, and the effectiveness of the Proposed algorithm is shown by simulation results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.4C
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• pp.303-309
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• 2006

By combining the space-time diversity technique and iterative turbo codes, space-time turbo codes(STTCS) are able to provide powerful error correction capability. However, the multi-path transmission and iterative decoding structure of STTCS make the decoder very complex. In this paper, we propose a low complexity decoder, which can be used to decode STTCS as well as general iterative codes such as turbo codes. The efficient implementation of the backward recursion and the log-likelihood ratio(LLR) update in the proposed algorithm improves the computational efficiency. In addition, if we approximate the calculation of the joint LLR by using the approximate ratio(AR) algorithm, the computational complexity can be reduced even further. A complexity analysis and computer simulations over the Rayleigh fading channel show that the proposed algorithm necessitates less than 40% of the additions required by the conventional Max-Log-MAP algorithm, while providing the same overall performance.

• Kyungpook Mathematical Journal
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• v.53 no.3
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• pp.307-318
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• 2013

In this paper, we introduce and study a new system of variational inclusions with B-monotone operators in Banach spaces. By using the proximal mapping associated with B-monotone operator, we construct a new iterative algorithm for approximating the solution of this system of variational inclusions. We also prove the existence of solutions and the convergence of the sequences generated by the algorithm for this system of variational inclusions. The results presented in this paper extend and improve some known results in the literature.

• Journal of Information Processing Systems
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• v.16 no.1
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• pp.30-41
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• 2020

Lines and textures are natural properties of the surface of natural objects, and their images can be sparsely represented in suitable frames such as wavelets, curvelets and wave atoms. Based on characteristics that the curvelets framework is good at expressing the line feature and wavesat is good at representing texture features, we propose a model for the weighted sparsity constraints of the two frames. Furtherly, a multi-step iterative fast algorithm for solving the model is also proposed based on the split Bergman method. By introducing auxiliary variables and the Bergman distance, the original problem is transformed into an iterative solution of two simple sub-problems, which greatly reduces the computational complexity. Experiments using standard images show that the split-based Bergman iterative algorithm in hybrid domain defeats the traditional Wavelets framework or curvelets framework both in terms of timeliness and recovery accuracy, which demonstrates the validity of the model and algorithm in this paper.

• Journal of Electrical Engineering and information Science
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• v.1 no.2
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• pp.67-76
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• 1996

In the present paper we propose two new improved iterative restoration algorithms. One is to accelerate convergence of the steepest descent method using the improved search directions, while the other accelerates convergence by using preconditioners. It is also shown that the proposed preconditioned algorithm can accelerate iteration-adaptive iterative image restoration algorithm. The preconditioner in the proposed algorithm can be implemented by using the FIR filter structure, so it can be applied to practical application with manageable amount of computation. Experimental results of the proposed methods show good perfomance improvement in the sense of both convergence speed and quality of the restored image. Although the proposed methods cannot be directly included in spatially-adaptive restoration, they can be used as pre-processing for iteration-adaptive algorithms.

• The Korean Journal of Nuclear Medicine Technology
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• v.28 no.1
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• pp.35-40
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• 2024

Purpose: To improve the image quality in positron emission tomography (PET), the attenuation correction technique based on the computed tomography (CT) data is important process. However, the artifact is caused by metal material during PET/CT scan, and the image quality is degraded. Therefore, the purpose of this study was to evaluate image quality according to with and without iterative metal artifact reduction (iMAR) algorithm using customized 3D printing phantom. Materials and Methods: The Hoffman and Derenzo phantoms were designed. To protect the gamma ray transmission and express the metal portion, lead substance was located to the surface. The SiPM based PET/CT was used for acquisition of PET images according to application with and without iMAR algorithm. The quantitative methods were used by signal to noise ratio (SNR), coefficient of variation (COV), and contrast to noise ratio (CNR). Results and Discussion: The results shows that the image quality applying iMAR algorithm was higher 1.15, 1.19, and 1.11 times than image quality without iMAR algorithm for SNR, COV, and CNR. Conclusion: In conclusion, the iMAR algorithm was useful for improvement of image quality by reducing the metal artifact lesion.