• Title/Summary/Keyword: levenberg-marquardt

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A Model-based 3-D Pose Estimation Method from Line Correspondences of Polyhedral Objects

  • Kang, Dong-Joong;Ha, Jong-Eun
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.762-766
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    • 2003
  • In this paper, we present a new approach to solve the problem of estimating the camera 3-D location and orientation from a matched set of 3-D model and 2-D image features. An iterative least-square method is used to solve both rotation and translation simultaneously. Because conventional methods that solved for rotation first and then translation do not provide good solutions, we derive an error equation using roll-pitch-yaw angle to present the rotation matrix. To minimize the error equation, Levenberg-Marquardt algorithm is introduced with uniform sampling strategy of rotation space to avoid stuck in local minimum. Experimental results using real images are presented.

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Design of Portable E-Nose System using Neural Network Algorithm (신경회로망을 이용한 휴대용 E-Nose 시스템 개발)

  • Kim, Jeong-Do;Kim, Dong-Jin;Ham, Yu-Kyung;Hong, Cheol-Ho;Byun, Hyung-Gi
    • Proceedings of the KIEE Conference
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    • 2004.11c
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    • pp.39-42
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    • 2004
  • We have designed a portable electronic nose(e-nose) system using an array of commercial gas sensors for recognition and analyzing the various odours. In this paper, we have implemented a portable e-nose system using an array gas sensors and personal digital assistants(PDA) for recognizing and analyzing volatile organic compounds(VOCs) in the field. Field screening for pollutants has been a target of instrumental development for number of year. A portable e-nose system can be substantial benefit to rapidly localize the spacial extent of a pollution or to find pollutants source. And, by using PDA, E-nose have a better function such as the easy user-interface and data transfer by internet from on- site to remote computer. We adapted the Levenberg-Marquardt algorithm based on the back-propagation and proposed the method that could be predicted concentration levels of VOCs gases after classification by separating neural network into two parts.

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Correspondence Estimation for Wide Area Watching Camera System (광역관찰 카메라 시스템을 위한 카메라의 대응관계 계산)

  • 이동휘;최승현;이칠우
    • Proceedings of the IEEK Conference
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    • 2001.09a
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    • pp.415-418
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    • 2001
  • The automatic construction of large, high-resolution image mosaics is an active area of reasearch in the fields of photogrammetry, computer vision, image processing, and computer graphics. In this study, we describe a automatic mosaicing method that makes a panorama from images by placing camera in a emitted-grid. In the images captured by cameras, there must be a matched area and the area is in the particular area of the image. Initial transformation matrix, there(ore, is calculated from points searched in the partial area. It is possible to find best transformation matrix by Levenberg-Marquardt method. Finally, each images are multiplied by blending function and stitched by the transformation matrix to complete panoramic image.

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A study on the characteristic analysis and correction of non-linear bias error of an infrared range finder sensor for a mobile robot (이동로봇용 적외선 레인지 파인더센서의 특성분석 및 비선형 편향 오차 보정에 관한 연구)

  • 하윤수;김헌희
    • Journal of Advanced Marine Engineering and Technology
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    • v.27 no.5
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    • pp.641-647
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    • 2003
  • The use of infrared range-finder sensor as the environment recognition system for mobile robot have the advantage of low sensing cost compared with the use of other vision sensor such as laser finder CCD camera. However, it is not easy to find the previous works on the use of infrared range-finder sensor for a mobile robot because of the non-linear characteristic of that. This paper describes the error due to non-linearity of a sensor and the correction of it using neural network. The neural network consists of multi-layer perception and Levenberg-Marquardt algorithm is applied to learning it. The effectiveness of the proposed algorithm is verified from experiment.

Improvement of Alignment Accuracy in Electron Tomography

  • Jou, Hyeong-Tae;Lee, Sujeong;Kim, Han-Joon
    • Applied Microscopy
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    • v.43 no.1
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    • pp.1-8
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    • 2013
  • We developed an improved method for tilt series alignment with fiducial markers in electron tomography. Based on previous works regarding alignment, we adapted the Levenberg-Marquardt method to solve the nonlinear least squares problem by incorporating a new formula for the alignment model. We also suggested a new method to estimate the initial value for inversion with higher accuracy. The proposed approach was applied to geopolymers. A better alignment of the tilt series was achieved than that by IMOD S/W. The initial value estimation provided both stability and a good rate of convergence since the new method uses all marker positions, including those partly covering the tilt images.

The development of AT-Cut Quartz Organic Vapor Recognizing System Using Artificial Neural Network (인공신경망을 이용한 수정진동자 유기용매 인식시스템의 개발)

  • Park, Soo-Heang;Ryu, Min-Su
    • Journal of the Korean Society of Industry Convergence
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    • v.6 no.1
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    • pp.31-36
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    • 2003
  • 8개의 수정진동자 위에 서로 다른 종류의 Lipid를 코팅하여서 만든 센서 배열을 가지고 유기용매를 인식할 수 있는 System을 구성한다. 유기용매 인식센서에 대한 수학적 모델을 사용하여 여러 가지 유기용매에 대한 센서의 응답으로부터 센서 표면과 유기용매 간의 물질 전달속도 패턴과 친화력 패턴을 얻어 유기용매 종류를 인식하였다. 패턴인식은 인공신경망을 이용하였으며 인공신경망의 연결 강도 수정은 Levenberg-Marquardt 알고리즘을 사용하였다. 신경망의 출력은 4개로 하였고, 디지털 신호인 0과 1의 조합으로 유기용매 종류를 구분하였다. 이 시스템을 이용하여 9개의 유기용매 Acetone, Benzene, Chloroform, Carbon-tetrachloride, Ethylacetate, Buthylacetate, Cyclohexane, Dichloromethane, 1,1,2,2,Tetrachloroethane, 2,2,4Trimethylpentane을 구분하여 인식할 수 있었다.

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Charted Depth Interpolation: Neuron Network Approaches

  • Shi, Chaojian
    • Journal of Navigation and Port Research
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    • v.28 no.7
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    • pp.629-634
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    • 2004
  • Continuous depth data are often required in applications of both onboard systems and maritime simulation. But data available are usually discrete and irregularly distributed. Based on the neuron network technique, methods of interpolation to the charted depth are suggested in this paper. Two algorithms based on Levenberg-Marquardt back-propaganda and radial-basis function networks are investigated respectively. A dynamic neuron network system is developed which satisfies both real time and mass processing applications. Using hyperbolic paraboloid and typical chart area, effectiveness of the algorithms is tested and error analysis presented. Special process in practical applications such as partition of lager areas, normalization and selection of depth contour data are also illustrated.

Size Effect on Axial Compressive Strength of Notched Concrete Specimens

  • Yi, Seong-Tae;Kim, Jin-Keun
    • KCI Concrete Journal
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    • v.14 no.1
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    • pp.43-50
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    • 2002
  • In this study, size effect tests were conducted on axial compressive strength of concrete members. An experiment of Mode I failure, which is one of two representative compressive failure modes, was carried out by using dimensionally proportional cylindrical specimens (CS). An adequate notch length was taken from the experimental results obtained from the compressive strength experiment of various initial notch lengths. Utilizing the notch length, specimen sizes were then varied. In addition, new parameters for the modified size effect law (MSEL) were suggested using Levenberg-Marquardt's least square method (LSM). The test results show that size effect was apparent for axial compressive strength of cracked specimens. Namely, the effect of initial notch length on axial compressive strength size effect was apparent.

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Load model estimation method for residential load and nomal load using measured data (실측 데이터를 이용한 일반용부하와 가정용부하의 부하모델 추정방안)

  • Park, Rae-Jun;Kwon, Oh-Sung;Song, K.;Kim, Kyu-Ho;Park, Jung-Wook;Jo, Jong-Man;Lee, Sung-Moo
    • Proceedings of the KIEE Conference
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    • 2011.07a
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    • pp.606-607
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    • 2011
  • 전력계통의 부하를 모델링하기 위해서는 부하 모델 구조의 선정과 부하모델 구조의 파라미터를 추정하는 방법이 필요하다. 부하 모델의 구조는 ZIP모델을 사용하고, 부하 모델의 파라미터를 추정하는 방법으로는 Levenberg-Marquardt방법을 사용하여 한국전력공사 변전소이차 측에서 측정된 실측 데이터를 이용하여 부하를 모델링하였다. 또한 모델링된 부하의 대표파라미터를 선정하고 대표파라미터를 실제 계통에 적용하였을 때의 오차를 분석하였다.

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Online MTPA Control of IPMSM for Automotive Applications Based on Robust Nonlinear Optimization Technique (비선형 최적화 기법에 기반한 자동차용 영구자석 동기전동기의 실시간 MTPA 제어)

  • Kim, Hyeon-Sik;Sul, Seung-Ki;Yoo, Hyunjae
    • Proceedings of the KIPE Conference
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    • 2017.11a
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    • pp.71-72
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    • 2017
  • 본 논문에서는 비선형 최적화 기법을 이용하여 자기 포화(magnetic saturation) 및 교차 결합 현상(cross-coupling effect)을 고려한 매입형 영구자석 전동기(IPMSM)의 실시간 MTPA 제어 방법을 제안한다. 이는 토크 지령 추종과 최소 동손 운전을 만족하는 제한 최적화(constraint optimization) 문제로 접근할 수 있다. 이를 통해 유도한 연립 비선형 방정식의 경우, Levenberg-Marquardt 수치 해석법을 적용하여 안정적이면서 빠르게 해를 구할 수 있다. 이러한 방법을 이용하면 참조표(look-up table) 없이 운전 환경의 실시간 변동을 고려한 효율적인 MTPA 운전이 가능하다. 시뮬레이션을 통해 제안된 알고리즘의 전류 해가 최적 운전점과 일치함을 확인하였다.

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