• Journal of applied mathematics & informatics
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• 제29권5_6호
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• pp.1303-1309
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• 2011

Based on the PRP method, a new spectral PRP conjugate gradient method has been proposed to solve general unconstrained optimization problems which produce sufficient descent search direction at every iteration without any line search. Under the Wolfe line search, we prove the global convergence of the new method for general nonconvex functions. The numerical results show that the new method is efficient for the given test problems.

• Journal of applied mathematics & informatics
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• 제34권1_2호
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• pp.157-165
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• 2016

In this paper, we develop a new hybridization conjugate gradient method for solving the unconstrained optimization problem. Under mild assumptions, we get the sufficient descent property of the given method. The global convergence of the given method is also presented under the Wolfe-type line search and the general Wolfe line search. The numerical results show that the method is also efficient.

• Journal of applied mathematics & informatics
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• 제22권1_2호
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• pp.461-466
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• 2006

In this paper, an algorithm with a new Armijo-type line search is proposed that ensure global convergence of a correlative Polak-Ribiere conjugate method for the unconstrained minimization of non-convex differentiable function.

• 한국통신학회논문지
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• 제31권9C호
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• pp.882-888
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• 2006

다중사용자 검출(multiuser detection)은 기존의 정합필터 방식에 비해 CDMA 시스템의 용량을 크게 증가시키고, 서비스 품질을 향상시킬 수 있는 기술이다. 본 논문에서는 gradient search(GS)에 기초하여 ML(maximu likelihood) metric을 간단히 계산할 수 있는 방법을 소개한다. ML 검출을 위해서는 사용자 확산부호 뿐만 아니라 전력도 알아야한다. 사용자 전력이 알려져 있지 않은 경우, 전력과 데이터를 동시에 추정하는 방법을 제시하였다. 제시한 방법으로 정확히 전력을 알고 데이터를 검출하는 GS 방식과 거의 동일한 성능을 얻을 수 있음을 컴퓨터 시뮬레이견 결과는 보여준다.

• 대한수학회보
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• 제50권1호
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• pp.73-81
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• 2013

In this paper, an efficient hybrid nonlinear conjugate gradient method is proposed to solve general unconstrained optimization problems on the basis of CD method [2] and DY method [5], which possess the following property: the sufficient descent property holds without any line search. Under the Wolfe line search conditions, we proved the global convergence of the hybrid method for general nonconvex functions. The numerical results show that the hybrid method is especially efficient for the given test problems, and it can be widely used in scientific and engineering computation.

• 한국유체기계학회 논문집
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• 제2권1호
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• pp.29-34
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• 1999

To develop the efficient numerical optimization method for the design of an airfoil, an evaluation of various methods coupled with two-dimensional Naviev-Stokes analysis is presented. Simplex method and Hook-Jeeves method we used as direct search methods, and steepest descent method, conjugate gradient method and DFP method are used as indirect search methods and are tested to determine the search direction. To determine the moving distance, the golden section method and cubic interpolation method are tested. The finite volume method is used to discretize two-dimensional Navier-Stokes equations, and SIMPLEC algorithm is used for a velocity-pressure correction method. For the optimal design of two-dimensional airfoil, maximum thickness, maximum ordinate of camber line and chordwise position of maximum ordinate are chosen as design variables, and the ratio of drag coefficient to lift coefficient is selected as an objective function. From the results, it is found that conjugate gradient method and cubic interpolation method are the most efficient for the determination of search direction and the moving distance, respectively.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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• pp.14-17
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• 1995

Various methods and techniques have been proposed for solving optimization problems; the methods have been applied to various practical problems. However the methods have demerits. The demerits which should be covered are, for example, falling into local minima, or, a slow convergence speed to optimal points. In this paper, Likelihood Search Method (L.S.M.) is proposed for searching for a global optimum systematically and effectively in a single framework, which is not a combination of different methods. The L.S.M. is a sort of a random search method (R.S.M.) and thus can get out of local minima. However exploitation of gradient information makes the L.S.M. superior in convergence speed to the commonly used R.S.M..

• 디지털콘텐츠학회 논문지
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• 제11권1호
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• pp.39-45
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• 2010

본 논문에서는 기울기 기반 빠른 정상점 탐색 방법론을 제시하고 시뮬레이션 결과를 제시한다. 제안하는 방법론은 유한 구간에서 단봉 그래프를 가지는 함수의 정상점(최대치)을 최대한 적은 수의 함수값을 참조하여 찾는 문제에 대한 솔루션으로, 대표적인 적용분야로는 자동초점이 있다. 우리는 정상점 탐색을 위해 주기적 탐색, 기울기 기반 탐색, 상세 탐색과 같이 세가지 탐색 전략을 통해 정상점을 찾는다. 노이즈가 첨가된 가우시안 함수를 발생시켜 시뮬레이션 한 결과 대략 8번탐색 횟수와 1.04의 오차를 보임을 알 수 있었다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(4)
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• pp.47-49
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• 2000

In this paper we propose the multiple local search method(MLSM) based on the motion information of the neighbor blocks. In the proposed method motions are estimated from the multiple searches of many candidate local search regions. To reduce the additional search points we avoid to search the same candidate regions previously visited using the distance from the initial search point to the recently found vector points. In the simulation the proposed method shows more excellent results than that of other gradient based method especially in the search of motion boundary.

• 산업기술연구
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• 제24권B호
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• pp.143-148
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• 2004

We present a fast algorithm for CDMA (code division multiple access) multiuser detection using the gradient guided search. The fast algorithm calculates the maximum likelihood (ML) metric so efficiently that it needs only O(K) additions in the presence of K users once some initialization is completed. The computational advantages of the fast algorithm over the conventional method are more noticeable as more iterations are required to obtain a suboptimal solution as in the initialization with matched filters.