• 제목/요약/키워드: Convex Function

검색결과 446건 처리시간 0.024초

ON CERTAIN CLASSES OF MULTIVALENT FUNCTIONS INVOLVING A GENERALIZED DIFFERENTIAL OPERATOR

  • Selvaraj, Chellian;Selvakumaran, Kuppathai A.
    • 대한수학회보
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    • 제46권5호
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    • pp.905-915
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    • 2009
  • Making use of a generalized differential operator we introduce some new subclasses of multivalent analytic functions in the open unit disk and investigate their inclusion relationships. Some integral preserving properties of these subclasses are also discussed.

ON THE CONVERGENCE OF THE UOBYQA METHOD

  • Han, Lixing;Liu, Guanghui
    • Journal of applied mathematics & informatics
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    • 제16권1_2호
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    • pp.125-142
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    • 2004
  • We analyze the convergence properties of Powell's UOBYQA method. A distinguished feature of the method is its use of two trust region radii. We first study the convergence of the method when the objective function is quadratic. We then prove that it is globally convergent for general objective functions when the second trust region radius p converges to zero. This gives a justification for the use of p as a stopping criterion. Finally, we show that a variant of this method is superlinearly convergent when the objective function is strictly convex at the solution.

Yield 최대화를 고려한 회로설계 (A Circuit design with Yield Maximization)

  • 김희석;임재석
    • 대한전자공학회논문지
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    • 제22권5호
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    • pp.102-109
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    • 1985
  • 다차원 Monte Carlo방법을 연구하여 새로운 yield 최대화 절차를 연구하였다. 새로 변형된 weight 선택 알고리즘을 MOS FET NAND 게이트에 적용하여 최대 yield추정을 하였다. 또한 본논문의 yield 최대화 절차는 목적함수가 non-convex일때도 적용된다.

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GRADIENT PROJECTION METHODS FOR THE n-COUPLING PROBLEM

  • Kum, Sangho;Yun, Sangwoon
    • 대한수학회지
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    • 제56권4호
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    • pp.1001-1016
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    • 2019
  • We are concerned with optimization methods for the $L^2$-Wasserstein least squares problem of Gaussian measures (alternatively the n-coupling problem). Based on its equivalent form on the convex cone of positive definite matrices of fixed size and the strict convexity of the variance function, we are able to present an implementable (accelerated) gradient method for finding the unique minimizer. Its global convergence rate analysis is provided according to the derived upper bound of Lipschitz constants of the gradient function.

CERTAIN GEOMETRIC PROPERTIES OF MODIFIED LOMMEL FUNCTIONS

  • Din, Muhey U;Yalcin, Sibel
    • 호남수학학술지
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    • 제42권4호
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    • pp.719-731
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    • 2020
  • In this article, we find some sufficient conditions under which the modified Lommel function is close-to-convex with respect to - log(1 - z) and ${\frac{1}{2}}\;{\log}\;\({\frac{1+z}{1-z}}\)$. Starlikeness, convexity and uniformly close-to-convexity of the modified Lommel function are also discussed. Some results related to the H. Silverman are also the part of our investigation.

스플라인 정칙자를 사용한 투과 단층촬영을 위한 벌점우도 영상재구성 (Penalized-Likelihood Image Reconstruction for Transmission Tomography Using Spline Regularizers)

  • 정지은;이수진
    • 대한의용생체공학회:의공학회지
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    • 제36권5호
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    • pp.211-220
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    • 2015
  • Recently, model-based iterative reconstruction (MBIR) has played an important role in transmission tomography by significantly improving the quality of reconstructed images for low-dose scans. MBIR is based on the penalized-likelihood (PL) approach, where the penalty term (also known as the regularizer) stabilizes the unstable likelihood term, thereby suppressing the noise. In this work we further improve MBIR by using a more expressive regularizer which can restore the underlying image more accurately. Here we used a spline regularizer derived from a linear combination of the two-dimensional splines with first- and second-order spatial derivatives and applied it to a non-quadratic convex penalty function. To derive a PL algorithm with the spline regularizer, we used a separable paraboloidal surrogates algorithm for convex optimization. The experimental results demonstrate that our regularization method improves reconstruction accuracy in terms of both regional percentage error and contrast recovery coefficient by restoring smooth edges as well as sharp edges more accurately.

Some Special Cases of a Continuous Time-Cost Tradeoff Problem with Multiple Milestones under a Chain Precedence Graph

  • Choi, Byung-Cheon;Chung, Jibok
    • Management Science and Financial Engineering
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    • 제22권1호
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    • pp.5-12
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    • 2016
  • We consider a time-cost tradeoff problem with multiple milestones under a chain precedence graph. In the problem, some penalty occurs unless a milestone is completed before its appointed date. This can be avoided through compressing the processing time of the jobs with additional costs. We describe the compression cost as the convex or the concave function. The objective is to minimize the sum of the total penalty cost and the total compression cost. It has been known that the problems with the concave and the convex cost functions for the compression are NP-hard and polynomially solvable, respectively. Thus, we consider the special cases such that the cost functions or maximal compression amounts of each job are identical. When the cost functions are convex, we show that the problem with the identical costs functions can be solved in strongly polynomial time. When the cost functions are concave, we show that the problem remains NP-hard even if the cost functions are identical, and develop the strongly polynomial approach for the case with the identical maximal compression amounts.

A meshfree adaptive procedure for shells in the sheet metal forming applications

  • Guo, Yong;Wu, C.T.;Park, C.K.
    • Interaction and multiscale mechanics
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    • 제6권2호
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    • pp.137-156
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    • 2013
  • In this paper, a meshfree shell adaptive procedure is developed for the applications in the sheet metal forming simulation. The meshfree shell formulation is based on the first-order shear deformable shell theory and utilizes the degenerated continuum and updated Lagrangian approach for the nonlinear analysis. For the sheet metal forming simulation, an h-type adaptivity based on the meshfree background cells is considered and a geometric error indicator is adopted. The enriched nodes in adaptivity are added to the centroids of the adaptive cells and their shape functions are computed using a first-order generalized meshfree (GMF) convex approximation. The GMF convex approximation provides a smooth and non-negative shape function that vanishes at the boundary, thus the enriched nodes have no influence outside the adapted cells and only the shape functions within the adaptive cells need to be re-computed. Based on this concept, a multi-level refinement procedure is developed which does not require the constraint equations to enforce the compatibility. With this approach the adaptive solution maintains the order of meshfree approximation with least computational cost. Two numerical examples are presented to demonstrate the performance of the proposed method in the adaptive shell analysis.

Constrained 최적화 기법을 이용한 Non-rigid 영상 등록 (Non-rigid Image Registration using Constrained Optimization)

  • 김정태
    • 한국통신학회논문지
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    • 제29권10C호
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    • pp.1402-1413
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    • 2004
  • 비강체 (non-rigid) 영상 등록에서 추정되는 좌표변환은 가역이어야 함으로 그 변환의 Jacobian 행렬식은 항상 양수 값을 가져야 한다. 본 논문에서는 이러한 가역 조건을 만족하는 좌표변환의 조건을 gradient 크기 제한의 조건으로 구한다. 또한 cubic B-spline을 이용한 변환 모델의 경우, 이 gradient 크기 제한 조건을 만족시키는 인수 집합을 이웃한 두 계수들의 차이가 제한된 인수들의 집합으로 구하였다. 이러한 인수들의 집합은 half space들의 교집합으로 이루어진 convex 집합이다. 본 논문에서는 이 convex 집합에 속하는 인수로 구성되는 좌표변환들 중에서 유사지수 (similarity measure) 를 최대로 만드는 변환을 gradient projection 최적화 기법을 통해 발견하였다. 이론적 분석, 폐 CT (Computed Tomography) 영상을 이용한 시뮬레이션 및 실험을 통하여, 제안된 알고리즘의 성능이 벌칙 함수 penalty function) 를 이용하는 기존의 방법보다 우수함을 증명하였다.