• 제목/요약/키워드: O-Algorithm

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불완전한 궤적을 고려한 강건한 특징점 추적 알고리즘 (A Robust Algorithm for Tracking Feature Points with Incomplete Trajectories)

  • 정종면;문영식
    • 대한전자공학회논문지SP
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    • 제37권6호
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    • pp.25-37
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    • 2000
  • 특징점의 궤적은 인접한 프레임에 존재하는 특정점 사이의 대응관계로 정의할 수 있다. 실제 영상열에서 존재할 수 있는 잘못된 특징점(false positive, false negative)들은 특징점의 대응관계를 결정할 때 많은 문제를 야기하기 때문에 특징점의 대응관계를 찾는 문제는 어려운 문제로 알려져 있다. 본 논문에서는 새로운 궤적의 나타남, 사라짐 등 불완전한 궤적을 갖는 특징점들을 고려하는 특징점 추적기법을 제안한다. 정합 척도로서 가중치가 부여된 유클리디언 거리를 사용하고 특징점의 운동특성을 잘 반영할 수 있도록 그 가중치를 자동으로 조정한다. 대응점 탐색과정에서 치명적인 영향을 줄 수 있는 애매한 특징점이 존재하는 경우를 고려하여 인접한 프레임 사이의 정합점 결정을 그래프에 의한 최적 대응점 탐색문제로 해결한다. 제안하는 대응점 탐색 알고리즘은 실제 영상열에서 나타날 수 있는 잘못된 특징점들이 대응관계를 결정할 때 주는 영향을 최소화하기 위하여 국부 최적(local optimal)을 찾게되며, 인접한 두 프레임에 m, n개의 특징점이 주어졌을 경우, 최선의 경우 O(mn), 최악의 경우 O($m^2n$)의 계산량을 필요로 한다. 제안하는 알고리즘은 정합과정에서 잘못된 특징점을 고려하고, 특징점의 운동특성을 잘 반영함으로써 대량의 특징점을 추적하는데도 충분히 적용할 수 있음을 실험을 통해 확인하였다.

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Minimum Net profit Project Deleting Algorithm for Choice of Facility Expansion Projects Problem

  • Lee, Sang-Un
    • 한국컴퓨터정보학회논문지
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    • 제21권5호
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    • pp.161-166
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    • 2016
  • This paper suggests heuristic algorithm with O(m) linear time complexity for choice of expansion projects that can't be obtain the optimal solution using linear programming until now. This algorithm ascending sort of net profit for all projects. Then, we apply a simple method that deletes the project with minimum net profit until this result satisfies the carried over for n-years more than zero value. While this algorithm using simple rule, not the linear programing fails but the proposed algorithm can be get the optimal solution for experimental data.

LQ비행제어를 위한 무충돌 전환 구현 알고리즘 (Bumpless Transfer Implementation Algorithm for LQ Flight Control)

  • 김태신;박종후;권오규;박춘배
    • 한국항공우주학회지
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    • 제34권11호
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    • pp.35-41
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    • 2006
  • 이 논문에서는 항공기의 비행제어에 적용하기 위해 각각의 비행영역에서 설계된 LQ(Linear Quadratic)제어기를 비행영역이 바뀜에도 충돌 없이 교체할 수 있는 알고리즘을 제안한다. 이 알고리즘은 기존의 구현 알고리즘에 비해 LQ제어기에 적용하기 편리하게 유도되었고, 비선형 모델에도 적용할 수 있도록 트림점을 포함한 식으로 제시된다. 제안된 알고리즘의 성능을 확인하기 위해 시험표준 문제로 초음속 시험 항공기의 LQ제어문제에 적용하는 모의실험을 수행하고 제어성능이 우수함을 예시한다.

CNC 공작기계의 NURBS 보간 알고리즘에 관한 연구 (NURBS Interpolation Algorithm for CNC Machines)

  • 홍원표;양민양
    • 한국정밀공학회지
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    • 제17권12호
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    • pp.115-120
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    • 2000
  • Increasing demands on precision machining of free-form surface have necessitated that the tool to move not only position error as small as possible, but also with smoothly varying feedrates. This paper presents new algorithm for high precision 3D(3-dimensional) NURBS(Non-Uniform Rational B-Spline) interpolation in the reference-pulse technique. Based o the minimum path error strategy, interpolation algorithm was designed to follow the NURBS curve. Using this algorithm a real-time 3D NURBS interpolator was developed in software. The algorithm implemented in a PC showed promising results in interpolation error and speed performance. It is expected that this can be applied to the CNC systems for the high precision machining of complex shapes.

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An Efficient Recursive Total Least Squares Algorithm for Training Multilayer Feedforward Neural Networks

  • Choi Nakjin;Lim Jun-Seok;Sung Koeng-Mo
    • 한국음향학회:학술대회논문집
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    • 한국음향학회 2004년도 추계학술발표대회논문집 제23권 2호
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    • pp.527-530
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    • 2004
  • We present a recursive total least squares (RTLS) algorithm for multilayer feedforward neural networks. So far, recursive least squares (RLS) has been successfully applied to training multilayer feedforward neural networks. But, when input data contain additive noise, the results from RLS could be biased. Such biased results can be avoided by using the recursive total least squares (RTLS) algorithm. The RTLS algorithm described in this paper gives better performance than RLS algorithm over a wide range of SNRs and involves approximately the same computational complexity of $O(N^{2})$.

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변분법을 이용한 재귀신경망의 온라인 학습 (A on-line learning algorithm for recurrent neural networks using variational method)

  • 오원근;서병설
    • 제어로봇시스템학회논문지
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    • 제2권1호
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    • pp.21-25
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    • 1996
  • In this paper we suggest a general purpose RNN training algorithm which is derived on the optimal control concepts and variational methods. First, learning is regared as an optimal control problem, then using the variational methods we obtain optimal weights which are given by a two-point boundary-value problem. Finally, the modified gradient descent algorithm is applied to RNN for on-line training. This algorithm is intended to be used on learning complex dynamic mappings between time varing I/O data. It is useful for nonlinear control, identification, and signal processing application of RNN because its storage requirement is not high and on-line learning is possible. Simulation results for a nonlinear plant identification are illustrated.

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Adaptive System Identification Using an Efficient Recursive Total Least Squares Algorithm

  • Choi, Nakjin;Lim, Jun-Seok;Song, Joon-Il;Sung, Koeng-Mo
    • The Journal of the Acoustical Society of Korea
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    • 제22권3E호
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    • pp.93-100
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    • 2003
  • We present a recursive total least squares (RTLS) algorithm for adaptive system identification. So far, recursive least squares (RLS) has been successfully applied in solving adaptive system identification problem. But, when input data contain additive noise, the results from RLS could be biased. Such biased results can be avoided by using the recursive total least squares (RTLS) algorithm. The RTLS algorithm described in this paper gives better performance than RLS algorithm over a wide range of SNRs and involves approximately the same computational complexity of O(N²).

A WEIGHTED-PATH FOLLOWING INTERIOR-POINT ALGORITHM FOR CARTESIAN P(κ)-LCP OVER SYMMETRIC CONES

  • Mansouri, Hossein;Pirhaji, Mohammad;Zangiabadi, Maryam
    • 대한수학회논문집
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    • 제32권3호
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    • pp.765-778
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    • 2017
  • Finding an initial feasible solution on the central path is the main difficulty of feasible interior-point methods. Although, some algorithms have been suggested to remedy this difficulty, many practical implementations often do not use perfectly centered starting points. Therefore, it is worth to analyze the case that the starting point is not exactly on the central path. In this paper, we propose a weighted-path following interior-point algorithm for solving the Cartesian $P_{\ast}({\kappa})$-linear complementarity problems (LCPs) over symmetric cones. The convergence analysis of the algorithm is shown and it is proved that the algorithm terminates after at most $O\((1+4{\kappa}){\sqrt{r}}{\log}{\frac{x^0{\diamond}s^0}{\varepsilon}}\)$ iterations.

Fuzzy modeling using HPC-MEANS algorhthm and genetic algorithm

  • Ryu, Kye-Won;Lee, Won-Gyu;Kim, Seong-Hwan;Noh, Heung-Sik;Park, Mignon
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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    • pp.113-116
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    • 1994
  • In this paper. we suggest new fuzzy modeling algorithm, which can be easily implemented, by combining HPC-MEANS Algorithm and Genetic Algorithm. HPC-MEANS used to cluster the sample data in input-output space will hyper planes and to make structure identification roughly and Genetic Algorithm is used to nine the premise and consequent parameters. For the validity of suggested methods we model the system with I/O data from known system. and then compare two systems.

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Machine Layout Decision Algorithm for Cellular Formation Problem

  • Lee, Sang-Un
    • 한국컴퓨터정보학회논문지
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    • 제21권4호
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    • pp.47-54
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    • 2016
  • Cellular formation and layout problem has been known as a NP-hard problem. Because of the algorithm that can be solved exact solution within polynomial time has been unknown yet. This paper suggests a systematic method to be obtain of 2-degree partial directed path from the frequency of consecutive forward order. We apply the modified Kruskal algorithm of minimum spanning tree to be obtain the partial directed path. the proposed reverse constructive algorithm can be solved for this problem with O(mn) time complexity. This algorithm performs same as best known result of heuristic and metaheuristic methods for 4 experimental data.