• 대한수학회지
• /
• 제55권3호
• /
• pp.719-734
• /
• 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.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2003년도 하계학술대회 논문집 A
• /
• pp.125-127
• /
• 2003

The Conventional time-domain simulation of transient stability requires iterative calculation procedures to consider the saliency of generator. Recently, a non-iterative algorithm has successfully developed to take into account the generator saliency exactly with the use of $E_q'$-model. This study proposes an extended non-iterative algorithm by adopting the two-axis generator model. Given internal voltages and rotor angles of the generators, network voltages and generator currents can be directly calculated by solving a linear algebraic equation, which enables us to reduce the computation time remarkably.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제12권10호
• /
• pp.4835-4855
• /
• 2018

In this paper, we study the sparse signal recovery that uses information of both support and amplitude of the sparse signal. A convergent iterative algorithm for sparse signal recovery is developed using Majorization-Minimization-based Non-convex Optimization (MM-NcO). Furthermore, it is shown that, typically, the sparse signals that are recovered using the proposed iterative algorithm are not globally optimal and the performance of the iterative algorithm depends on the initial point. Therefore, a modified MM-NcO-based iterative algorithm is developed that uses prior information of both support and amplitude of the sparse signal to enhance recovery performance. Finally, the modified MM-NcO-based iterative algorithm is used to estimate the time-varying sparse wireless channels with temporal correlation. The numerical results show that the new algorithm performs better than related algorithms.

• 한국통신학회논문지
• /
• 제27권6A호
• /
• pp.524-532
• /
• 2002

이 논문은, 램버트 W 함수가 라플라스 신호원에 대한 최적 (최소평균제곱오차) 양자기의 비반복적 설계에 이용될 수 있다는 사실을 보고한다. 구체적으로, 라플라스 신호원에 최적인 양자기의 비반복적 설계법을 고찰하며, 설계에 필수적인 비선형 방정식의 점화식의 풀이가 램버트 W 함수를 사용한 닫힌 식으로 표현된다는 것을 발견하였고, 또 이 논문에서는 이 설계법이 지수함수 형태나 라플라스 확률밀도함수 형태를 갖는 신호원에만 적용된다는 것을 증명하였다. 이 논문의 기여점은, 양자기의 설계가 비반복적이며, 원하는 만큼의 정확도로 설계되기 때문에 설계에 필요한 계산 회수가 감소되고, 양자점과 경계값을 구하는데 있어 높은 정확도를 갖는다는 점이다. 또한, 수치결과를 통하여 최적 양자 왜곡이 팬터-다잇 상수에 단조 증기적으로 수렴하는 과정을 관찰하였으며, 최적 양자기의 최외곽 경계값인 중요변수의 근사식을 유도하였다.

• 제어로봇시스템학회논문지
• /
• 제7권12호
• /
• pp.1001-1008
• /
• 2001

This paper presents a new camera calibration algorithm for ill-conditioned cases in which the camera plane is nearly parallel to a set of non-coplanar calibration boards. for the ill-conditioned case, most of existing calibration approaches such as Tsais radial-alignment-constraint method cannot be applied. Recently, for the ill-conditioned coplanar calibration Lee&Lee[16] proposed an iterative algorithm based on the least square method. The non-coplanar calibration algorithm presented in this paper is an iterative two-stage procedure with extends the previous coplanar calibration algorithm. Through the first stage, camera, position and orientation parameters as well as one radial distortion factor are determined optimally for a given data of the scale factor and the focal length. In the second stage, the scale factor and the focal length are locally optimized. This process is repeated until any improvement cannot be expected any more Computational results are provided to show the performance of the algorithm developed.

• 대한의용생체공학회:의공학회지
• /
• 제8권2호
• /
• pp.151-160
• /
• 1987

An algorithm is suggested that truncted projection among the incomplete projections can be recovered from non-iterative extrapolation matrix by band-limited function. After the image being reconstructed from the recovered signals by non-iterative extrapolation, a known controur information and reprojection algorithm are used. It is shown that the reconstructed image using these algorithms is close to the original image. The effectiveness for these algorithms is proved by computer simulation.

• Nuclear Engineering and Technology
• /
• 제55권12호
• /
• pp.4350-4356
• /
• 2023

Radiation detection systems working at high count rates suffer from the overlapping of their output electric pulses, known as pulse pile-up phenomenon, resulting in spectrum distortion and degradation of the energy resolution. Pulse tail extrapolation is a pile-up correction method which tries to restore the shifted baseline of a piled-up pulse by extrapolating the overlapped part of its preceding pulse. This needs a mathematical model which is almost always nonlinear, fitted usually by a nonlinear least squares (NLS) technique. NLS is an iterative, potentially time-consuming method. The main idea of the present study is to replace the NLS technique by an integration-based non-iterative method (NIM) for pulse tail extrapolation by an exponential model. The idea of linear extrapolation, as another non-iterative method, is also investigated. Analysis of experimental data of a NaI(Tl) radiation detector shows that the proposed non-iterative method is able to provide a corrected spectrum quite similar with the NLS method, with a dramatically reduced computation time and complexity of the algorithm. The linear extrapolation approach suffers from a poor energy resolution and throughput rate in comparison with NIM and NLS techniques, but provides the shortest computation time.

• 대한수학회보
• /
• 제34권4호
• /
• pp.603-615
• /
• 1997

In this paper, we introduce and study a new class of random completely generalized nonlinear variational inclusions with non-compact valued random mappings and construct some new iterative algorithms. We prove the existence of random solutions for this class of random variational inclusions and the convergence of random iterative sequences generated by the algorithms.

• 대한수학회논문집
• /
• 제25권3호
• /
• pp.419-426
• /
• 2010

In this paper, a three-step iterative method is considered for finding a common element in the set of fixed points of a non-expansive mapping and in the set of solutions of a variational inclusion problem in a real Hilbert space.

• 제어로봇시스템학회논문지
• /
• 제18권6호
• /
• pp.579-583
• /
• 2012

The purpose of this paper is to suggest IDE (Incremental Displacement Estimation) algorithm for the previously proposed visually servoed paired structured light system. The system is composed of two sides facing with each other, each with one or two lasers with a 2-DOF manipulator, a camera, and a screen. The 6-DOF displacement between two sides can be estimated by calculating the positions of the projected laser beams and rotation angles of the manipulators. In the previous study, Newton-Raphson or EKF (Extended Kalman Filter) has been used as an estimation algorithm. Although the various experimental tests have validated the performance of the system and estimation algorithms, the computation time is relatively long since aforementioned algorithms are iterative methods. Therefore, in this paper, a non-iterative incremental displacement estimation algorithm which updates the previously estimated displacement with a difference of the previous and the current observed data is introduced. To verify the performance of the algorithm, experimental tests have been performed. The results show that the proposed non-iterative algorithm estimates the displacement with the same level of accuracy compared to the EKF with multiple iterations with significantly less computation time.