• Title/Summary/Keyword: Convex

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Convex-hull을 이용한 기하학적 특징 기반의 손 모양 인식 기법 (Hand shape recognition based on geometric feature using the convex-hull)

  • 최인규;유지상
    • 한국정보통신학회논문지
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    • 제18권8호
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    • pp.1931-1940
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    • 2014
  • x본 논문에서는 키넥트(Kinect) 시스템에서 획득한 깊이 영상으로부터 convex-hull을 이용한 기하학적 특징 기반의 손 모양 인식 기법을 제안한다. 키넥트 시스템은 깊이 영상과 사용자의 골격 정보를 제공하는 카메라로 손 영역 검출에 유용하게 활용할 수 있다. 제안하는 기법에서는 키넥트로 획득한 깊이 영상에서 손 영역을 검출하고, 이 손 영역의 convex-hull을 구한다. 손 모양에 따라서 변하는 convex-hull에서 잡음으로 생긴 경계점 및 인식에 불필요한 경계점을 일련의 기법을 통해 제거한다. 추려진 경계점을 통해 재구성된 convex-hull을 특정 다각형으로 판단하고, 이 다각형의 내각의 합을 이용하여 손 모양을 인식하게 된다. 실험을 통해 제안하는 기법이 인식하고자 하는 모델에 대하여 높은 인식률을 보여준다는 것을 확인하였고, 단순히 특정 방향으로 고정된 손 모양뿐만 아니라 같은 모양이나 방향이 틀어진 손 모양에 대해서도 우수한 인식 성능을 확인하였다.

Multi-loop PID Control Method of Brushless DC Motors via Convex Combination Method

  • Kim, Chang-Hyun
    • Journal of Electrical Engineering and Technology
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    • 제12권1호
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    • pp.72-77
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    • 2017
  • This paper proposes the explicit tuning rule of multi-loop PID controller for brushless direct current motors to predict the system behaviors in time and frequency domains, using properties of the convex combination method. The convex set of the proposed controllers formulates the envelope to satisfy the performances in time and frequency domains. The final control parameters are determined by solving the convex optimization problem subject to the constraints which are represented as convex set of time domain performances. The effectiveness of the proposed control method is shown in the numerical simulation, in which controller tuning algorithm and dynamics of brushless DC motor are well taken into account.

An efficient algorithm for the non-convex penalized multinomial logistic regression

  • Kwon, Sunghoon;Kim, Dongshin;Lee, Sangin
    • Communications for Statistical Applications and Methods
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    • 제27권1호
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    • pp.129-140
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    • 2020
  • In this paper, we introduce an efficient algorithm for the non-convex penalized multinomial logistic regression that can be uniformly applied to a class of non-convex penalties. The class includes most non-convex penalties such as the smoothly clipped absolute deviation, minimax concave and bridge penalties. The algorithm is developed based on the concave-convex procedure and modified local quadratic approximation algorithm. However, usual quadratic approximation may slow down computational speed since the dimension of the Hessian matrix depends on the number of categories of the output variable. For this issue, we use a uniform bound of the Hessian matrix in the quadratic approximation. The algorithm is available from the R package ncpen developed by the authors. Numerical studies via simulations and real data sets are provided for illustration.

2차원 패턴의 볼록 헐 알고리즘 (A Convex Hull Algorithm for 2D Patterns)

  • 홍기천;오일석
    • 한국멀티미디어학회논문지
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    • 제4권4호
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    • pp.363-369
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    • 2001
  • 본 논문에서는 2 차원 패턴을 위한 볼록 헐(convex hull) 알고리즘을 제안한다. 알고리즘은 크게 후보 볼록점 추출과 최종 볼록점 추출의 두 단계로 나된다. 첫 번째 단계에서는 볼록 헐의 볼록점이 될 수 없는 점들을 최대한 간단한 연산을 사용하여 제거함으로써 속도의 향상을 기한다. 두 번째 단계에서는 첫 번째 단계에서 구해진 후보 볼록점을 대상으로 최종 볼록 헐을 구한다. 이 방법은 매우 간단한 연산으로 구성되어 있기 때문에 수행 속도면에서 향상을 가져왔다. 실험 결과, 본 논문의 방법이 기존에 사용되던 두 개의 볼록 헐 알고리즘보다 2배내지 3배의 빠른 수행 속도를 보였다.

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NEW INEQUALITIES FOR GENERALIZED LOG h-CONVEX FUNCTIONS

  • NOOR, MUHAMMAD ASLAM;NOOR, KHALIDA INAYAT;SAFDAR, FARHAT
    • Journal of applied mathematics & informatics
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    • 제36권3_4호
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    • pp.245-256
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    • 2018
  • In the paper, we introduce some new classes of generalized logh-convex functions in the first sense and in the second sense. We establish Hermite-Hadamard type inequality for different classes of generalized convex functions. It is shown that the classes of generalized log h-convex functions in both senses include several new and known classes of log h convex functions. Several special cases are also discussed. Results proved in this paper can be viewed as a new contributions in this area of research.

A METHOD FOR TESTING SURFACE DEFORMS OF LARGE CONVEX MIRRORS

  • Kim Young-Soo
    • 한국우주과학회:학술대회논문집(한국우주과학회보)
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    • 한국우주과학회 2004년도 한국우주과학회보 제13권2호
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    • pp.254-257
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    • 2004
  • Both ground and space telescopes are being built larger and larger. Accordingly, the secondary mirrors become larger which are convex mostly on the surface form. Testing convex mirrors becomes more difficult and delicate than testing concave mirrors in optics, because additional optical components are needed to make the reflected rays converge. Hindle type tests are frequently used for measuring the surface deforms of convex mirrors, which employs a meniscus lens to reverse the diverted rays from the mirrors. In case of testing large convex mirrors by using Hindle type tests, attention would be needed as larger meniscus lens is required. A method of modified Hindle test has been studied and the characteristics are analyzed. In this paper, current method of testing convex mirrors is presented, and a new method is discussed.

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LMS기반 트랜스버설 필터의 컨벡스조합을 위한 부밴드 적응알고리즘 (Subband Adaptive Algorithm for Convex Combination of LMS based Transversal Filters)

  • 손상욱;이경표;최훈;배현덕
    • 전기학회논문지
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    • 제62권1호
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    • pp.133-139
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    • 2013
  • Convex combination of two adaptive filters is an efficient method to improve adaptive filter performances. In this paper, a subband convex combination method of two adaptive filters for fast convergence rate in the transient state and low steady state error is presented. The cost function of mixing parameter for a subband convex combination is defined, and from this, the coefficient update equation is derived. Steady state analysis is used to prove the stability of the subband convex combination. Some simulation examples in system identification scenario show the validity of the subband convex combination schemes.

Independence and maximal volume of d-dimensional random convex hull

  • Son, Won;Park, Seongoh;Lim, Johan
    • Communications for Statistical Applications and Methods
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    • 제25권1호
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    • pp.79-89
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    • 2018
  • In this paper, we study the maximal property of the volume of the convex hull of d-dimensional independent random vectors. We show that the volume of the random convex hull from a multivariate location-scale family indexed by ${\Sigma}$ is stochastically maximized in simple stochastic order when ${\Sigma}$ is diagonal. The claim can be applied to a broad class of multivariate distributions that include skewed/unskewed multivariate t-distributions. We numerically investigate the proven stochastic relationship between the dependent and independent random convex hulls with the Gaussian random convex hull. The numerical results confirm our theoretical findings and the maximal property of the volume of the independent random convex hull.

A CONSTRAINED CONVEX SPLITTING SCHEME FOR THE VECTOR-VALUED CAHN-HILLIARD EQUATION

  • LEE, HYUN GEUN;LEE, JUNE-YUB;SHIN, JAEMIN
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제23권1호
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    • pp.1-18
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    • 2019
  • In contrast to the well-developed convex splitting schemes for gradient flows of two-component system, there were few efforts on applying the convex splitting idea to gradient flows of multi-component system, such as the vector-valued Cahn-Hilliard (vCH) equation. In the case of the vCH equation, one need to consider not only the convex splitting idea but also a specific method to manage the partition of unity constraint to design an unconditionally energy stable scheme. In this paper, we propose a constrained Convex Splitting (cCS) scheme for the vCH equation, which is based on a convex splitting of the energy functional for the vCH equation under the constraint. We show analytically that the cCS scheme is mass conserving and unconditionally uniquely solvable. And it satisfies the constraint at the next time level for any time step thus is unconditionally energy stable. Numerical experiments are presented demonstrating the accuracy, energy stability, and efficiency of the proposed cCS scheme.

ON TRIGONOMETRICALLY QUASI-CONVEX FUNCTIONS

  • Numan, Selim;Iscan, Imdat
    • 호남수학학술지
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    • 제43권1호
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    • pp.130-140
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    • 2021
  • In this paper, we introduce and study the concept of trigonometrically quasi-convex function. We prove Hermite-Hadamard type inequalities for the newly introduced class of functions and obtain some new Hermite-Hadamard inequalities for functions whose first derivative in absolute value, raised to a certain power which is greater than one, respectively at least one, is trigonometrically quasi-convex convex. We also extend our initial results to functions of several variables. Next, we point out some applications of our results to give estimates for the approximation error of the integral the function in the trapezoidal formula.