• 제목/요약/키워드: Marquardt method.

검색결과 101건 처리시간 0.031초

Iris Recognition using Multi-Resolution Frequency Analysis and Levenberg-Marquardt Back-Propagation

  • Jeong Yu-Jeong;Choi Gwang-Mi
    • Journal of information and communication convergence engineering
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    • 제2권3호
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    • pp.177-181
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    • 2004
  • In this paper, we suggest an Iris recognition system with an excellent recognition rate and confidence as an alternative biometric recognition technique that solves the limit in an existing individual discrimination. For its implementation, we extracted coefficients feature values with the wavelet transformation mainly used in the signal processing, and we used neural network to see a recognition rate. However, Scale Conjugate Gradient of nonlinear optimum method mainly used in neural network is not suitable to solve the optimum problem for its slow velocity of convergence. So we intended to enhance the recognition rate by using Levenberg-Marquardt Back-propagation which supplements existing Scale Conjugate Gradient for an implementation of the iris recognition system. We improved convergence velocity, efficiency, and stability by changing properly the size according to both convergence rate of solution and variation rate of variable vector with the implementation of an applied algorithm.

과도탐침법을 이용한 액체의 열물성 동시측정 (The simultaneous measurement for thermal properties of liquids using transient probe method)

  • 배신철;김명윤
    • 대한기계학회논문집B
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    • 제21권2호
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    • pp.303-315
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    • 1997
  • The theoretical model for the transient probe method is the modified Jaeger model which is used perfect line source theory. The transient probe technique has been developed for the simultaneous determination of thermal conductivity, diffusivity and volumetric heat capacity of liquids. The Levenberg-Marquardt iteration method is adapted to obtain thermal property within nonlinear range. Experimental results of liquids were found to agree well with recommended thermal property data.

Precise Edge Detection Method Using Sigmoid Function in Blurry and Noisy Image for TFT-LCD 2D Critical Dimension Measurement

  • Lee, Seung Woo;Lee, Sin Yong;Pahk, Heui Jae
    • Current Optics and Photonics
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    • 제2권1호
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    • pp.69-78
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    • 2018
  • This paper presents a precise edge detection algorithm for the critical dimension (CD) measurement of a Thin-Film Transistor Liquid-Crystal Display (TFT-LCD) pattern. The sigmoid surface function is proposed to model the blurred step edge. This model can simultaneously find the position and geometry of the edge precisely. The nonlinear least squares fitting method (Levenberg-Marquardt method) is used to model the image intensity distribution into the proposed sigmoid blurred edge model. The suggested algorithm is verified by comparing the CD measurement repeatability from high-magnified blurry and noisy TFT-LCD images with those from the previous Laplacian of Gaussian (LoG) based sub-pixel edge detection algorithm and error function fitting method. The proposed fitting-based edge detection algorithm produces more precise results than the previous method. The suggested algorithm can be applied to in-line precision CD measurement for high-resolution display devices.

DC 순방향 바이어스 인가조건에서 Schottky 다이오드의 SPICE 모델 파라미터 추출 방법에 관한 연구 (The Study on the SPICE Model Parameter Extraction Method for the Schottky Diode Under DC Forward Bias)

  • 이은구
    • 전기학회논문지
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    • 제65권3호
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    • pp.439-444
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    • 2016
  • The method for extracting the SPICE model parameter of Schottky diode under DC forward bias is proposed. A method for improving the accuracy of the SPICE model parameter at various temperatures is proposed. Three analysis steps according to the magnitude of the current is used in order to extract the parameters effectively. At each analysis step, initial parameters are calculated by using the current-voltage equations and the Levenberg-Marquardt analysis is proceeded. To verify the validity of the proposed method, the SPICE model parameters for the BAT45 and FSV1045 under DC forward bias is extracted. Schottky diode currents obtained from the proposed method shows the average relative error of 6.1% and 9% compared with the measured data for the BAT45 and FSV1045 sample at various temperatures.

렌즈의 왜곡 모델을 이용한 카메라 보정에 관한 연구 (A Study on the Camera Calibration Using Lens Distortion Model)

  • Dong Min Woo
    • 전자공학회논문지B
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    • 제31B권2호
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    • pp.56-68
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    • 1994
  • The objective of camera calibration is to determine the internal optical characteristics of camera and the three-dimensional position and orientation of camera with respect to the real world. Calibration procedure for computer vision should be automatical, accurate and applicable to general purpose cameras and lenses. In this paper, we present camera calibration method which meets the above requirements. The algorithm is based on the two-stage method which takes into account lens distortion in the second stage. In this paper, the overdetermined nonlinear system is established in terms of the constraints to all directions and our calibration algorithm is proposed which is constructed by using Marquardt iterations and our calibration algorithm is proposed which is constructed by using Marquardt iteration method in solving nonlinear equations. Experimental results indicate that lens distortion should be taken into consideration for the calibration of the general-purpose lens. With 24 calibration points acquired out of 512$\times$512 image, the proposed algorithm came up with average error of less than 1 pixel and showed a higher accuracy over the conventional two-stage method.

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MOS 센서어레이를 이용한 냄새 분류 및 농도추정을 위한 LM-BP 알고리즘 응용 (LM-BP algorithm application for odour classification and concentration prediction using MOS sensor array)

  • 최찬석;변형기;김정도
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.210-210
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    • 2000
  • In this paper, we have investigated the properties of multi-layer perceptron (MLP) for odour patterns classification and concentration estimation simultaneously. When the MLP may be has a fast convergence speed with small error and excellent mapping ability for classification, it can be possible to use for classification and concentration prediction of volatile chemicals simultaneously. However, the conventional MLP, which is back-Propagation of error based on the steepest descent method, was difficult to use for odour classification and concentration estimation simultaneously, because it is slow to converge and may fall into the local minimum. We adapted the Levenberg-Marquardt(LM) algorithm [4,5] having advantages both the steepest descent method and Gauss-Newton method instead of the conventional steepest descent method for the simultaneous classification and concentration estimation of odours. And, We designed the artificial odour sensing system(Electronic Nose) and applied LM-BP algorithm for classification and concentration prediction of VOC gases.

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Viscoelastic behavior on composite beam using nonlinear creep model

  • Jung, Sung-Yeop;Kim, Nam-Il;Shin, Dong Ku
    • Steel and Composite Structures
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    • 제7권5호
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    • pp.355-376
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    • 2007
  • The purpose of this study is to predict and investigate the time-dependent creep behavior of composite materials. For this, firstly the evaluation method for the modulus of elasticity of whole fiber and matrix is presented from the limited information on fiber volume fraction using the singular value decomposition method. Then, the effects of fiber volume fraction on modulus of elasticity of GFRP are verified. Also, as a creep model, the nonlinear curve fitting method based on the Marquardt algorithm is proposed. Using the existing Findley's power creep model and the proposed creep model, the effect of fiber volume fraction on the nonlinear creep behavior of composite materials is verified. Then, for the time-dependent analysis of a composite material subjected to uniaxial tension and simple shear loadings, a user-provided subroutine UMAT is developed to run within ABAQUS. Finally, the creep behavior of center loaded beam structure is investigated using the Hermitian beam elements with shear deformation effect and with time-dependent elastic and shear moduli.

불변 특징모델을 이용한 카메라 동작인수 측정 (Estimation of Camera Motion Parameter using Invariant Feature Models)

  • 차정희;이근수
    • 한국컴퓨터정보학회논문지
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    • 제10권4호
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    • pp.191-201
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    • 2005
  • 본 논문에서는 카메라의 뷰포인트에 무관한 효율적인 불변특징을 기반으로 카메라의 동작인수를 산출하는 방법을 제안한다. 기존연구에서 사용된 특징정보는 카메라의 뷰포인트에 따라 변하기 때문에 정보양이 증가하여 정확한 특징추출이 어렵다. 또한 카메라 외부인수 산출을 위해 사용되는 LM(Levenberg-Marquardt)방법은 정확하게 목표 값에 수렴하지만 작은 스텝크기로 최소화를 진행하므로 소요시간이 긴 단점이 있다. 따라서 본 논문에서는 뷰포인트에 무관한 불변특징 추출방법과 이 특징들을 이용하여 2D 호모그래피로 찾은 카메라 동작인수를 LM 방법의 초기값으로 사용, 정확성과 수렴도를 향상시키는 2단계 카메라 동작인수산출 방법을 제안한다. 제안하는 방법은 특징 추출단계, 정합 단계, 2단계 카메라 동작인수 산출단계로 구성된다. 실험에서는 다양한 실내영상으로 제안한 방법과 기존 방법을 비교, 분석함으로써 제안한 알고리즘의 우수성을 입증하였다.

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LM 최적화 알고리즘을 이용한 유리함수 모델의 데이터 피팅 (A Data Fitting Technique for Rational Function Models Using the LM Optimization Algorithm)

  • 박재한;배지훈;백문홍
    • 제어로봇시스템학회논문지
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    • 제17권8호
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    • pp.768-776
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    • 2011
  • This paper considers a data fitting problem for rational function models using the LM (Levenberg-Marquardt) optimization method. Rational function models have various merits on representing a wide range of shapes and modeling complicated structures by polynomials of low degrees in both the numerator and denominator. However, rational functions are nonlinear in the parameter vector, thereby requiring nonlinear optimization methods to solve the fitting problem. In this paper, we propose a data fitting method for rational function models based on the LM algorithm which is renowned as an effective nonlinear optimization technique. Simulations show that the fitting results are robust against the measurement noises and uncertainties. The effectiveness of the proposed method is further demonstrated by the real application to a 3D depth camera calibration problem.

다수의 영상 특징점 정합을 위한 비선형 최적화 기법 (Nonlinear Optimization Method for Multiple Image Registration)

  • 안양근;홍지만
    • 방송공학회논문지
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    • 제17권4호
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    • pp.634-639
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    • 2012
  • 본 논문에서는 다수의 영상에서 발견된 특징점의 정확한 정합을 위한 비선형 최적화 기법을 제안한다. 영상에서 발견된 특징점은 선형 해법에 의해 다수의 영상간의 변환을 구할 수 있지만 큰 오차를 수반하게 된다. 이는 영상이 생성되는 모델이 비선형이며, 다수시점간의 운동역시 비선형의 형태를 띄기 때문이다. 하지만 다수의 영상의 비선형 최적화는 일반적인 비선형 해법을 도입하였을 때에는 복잡도가 지수적으로 증가하는 단점이 있다. 본 논문에서는 Levenberg-Marquardt 비선형 최적화 방법의 희박해법(Sparse solution)을 이용하여 다수의 특징점간의 변환을 구하는 방법을 보인다.