• Title/Summary/Keyword: Marquardt

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High performance switched reluctance drives with wide field weakening range

  • Marquardt Rainer;Hiller Marc
    • Proceedings of the KIPE Conference
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    • 2001.10a
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    • pp.779-784
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    • 2001
  • For electrical vehicles, switched reluctance drives present a promising alternative-compared to asynchronous and synchronous (permanent magnet) concepts. For these applications, a very wide field weakening range is a key issue. Other requirements include high torque output from a small machine and low current ripple at the DC-side without the use of bulky filters - when powered from fuel cells or advanced Lithium-Ion-batteries. A new converter and control strategy according to these requirements is presented and compared to existing designs. The comparison is done for a drive system with a continuous power rating of 30 to 40 kW.

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Intracranial Hemorrhagic Lesion Feature Extraction System Of Using Wavelet Transform and LMBP (웨이블렛 변환과 LMBP를 이용한 대뇌출혈성 병변 인식 시스템)

  • 정유정;정채영
    • Proceedings of the Korean Information Science Society Conference
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    • 2002.10d
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    • pp.625-627
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    • 2002
  • 본 논문에서는 의료영상 인식 기술 중 인식률이 뛰어나고 신뢰성 있는 대뇌출혈성 병변인식 시스템을 구현하기 위하여 신호처리 분야에서 주로 사용되는 Wavelet 변환과 신경망 기법을 이용하고자 한다. 그러나 신경망 기법에서 주로 사용되는 비선형 최적화기법인 Gradient descent BP는 최적화 문제점을 해결하기에는 수렴속도가 느리기 때문에 적합하지 않다. 따라서 본 논문에서는 기존 Gradient descent BP를 보완한 Levenberg-Marquardt Back-Propagation을 대뇌출혈성 병변인식에 적용하여 구현함으로써 총 50개의 패턴 중 45개의 영상이 인식에 성공하였고 전체 평균 인식률은 각각 90%와 87%의 인식률을 보였다.

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Impedance Imaging of Binary-Mixture Systems with Regularized Newton-Raphson Method

  • Kim, Min-Chan;Kim, Sin;Kim, Kyung-Youn
    • Journal of Energy Engineering
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    • v.10 no.3
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    • pp.183-187
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    • 2001
  • Impedance imaging for binary mixture is a kind of nonlinear inverse problem, which is usually solved iteratively by the Newton-Raphson method. Then, the ill-posedness of Hessian matrix often requires the use of a regularization method to stabilize the solution. In this study, the Levenberg-Marquredt regularization method is introduced for the binary-mixture system with various resistivity contrasts (1:2∼1:1000). Several mixture distribution are tested and the results show that the Newton-Raphson iteration combined with the Levenberg-Marquardt regularization can reconstruct reasonably good images.

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Camera Extrinsic Parameter Estimation using 2D Homography and Nonlinear Minimizing Method based on Geometric Invariance Vector (기하학적 불변벡터 기탄 2D 호모그래피와 비선형 최소화기법을 이용한 카메라 외부인수 측정)

  • Cha, Jeong-Hee
    • Journal of Internet Computing and Services
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    • v.6 no.6
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    • pp.187-197
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    • 2005
  • In this paper, we propose a method to estimate camera motion parameter based on invariant point features, Typically, feature information of image has drawbacks, it is variable to camera viewpoint, and therefore information quantity increases after time, The LM(Levenberg-Marquardt) method using nonlinear minimum square evaluation for camera extrinsic parameter estimation also has a weak point, which has different iteration number for approaching the minimal point according to the initial values and convergence time increases if the process run into a local minimum, In order to complement these shortfalls, we, first proposed constructing feature models using invariant vector of geometry, Secondly, we proposed a two-stage calculation method to improve accuracy and convergence by using 2D homography and LM method, In the experiment, we compared and analyzed the proposed method with existing method to demonstrate the superiority of the proposed algorithms.

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Study of Neural Network Training Algorithm Comparison and Prediction of Unsteady Aerodynamic Forces of 2D Airfoil (신경망 학습알고리즘의 비교와 2차원 익형의 비정상 공력하중 예측기법에 관한 연구)

  • Kang, Seung-On;Jun, Sang-Ook;Park, Kyung-Hyun;Jeon, Yong-Hee;Lee, Dong-Ho
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.37 no.5
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    • pp.425-432
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    • 2009
  • In this study, the ability of neural network in modeling and predicting of the unsteady aerodynamic force coefficients of 2D airfoil with the data obtained from Euler CFD code has been confirmed. Neural network models are constructed based on supervised training process using Levenberg-Marquardt algorithm, combining this into genetic algorithm, hybrid genetic algorithm and the efficiency of the two cases are analyzed and compared. It is shown that hybrid-genetic algorithm is more efficient for neural network of complex system and the predicted properties of the unsteady aerodynamic force coefficients of 2D airfoil by the neural network models are confirmed to be similar to that of the numerical results and verified as suitable representing reduced models.

Algorithm Study for Diagnosis the Breast Cancer Using LMA and FDTD (LMA와 FDTD를 이용한 유방암 진단용 알고리즘 연구)

  • Seo, Min-Gyeong;Kim, Tae-Hong;Mun, Ji-Yeon;Jeon, Soon-Ik;Pack, Jeong-Ki
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.22 no.12
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    • pp.1124-1131
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    • 2011
  • In this paper, image reconstruction algorithm for breast cancer detection using MT(Microwave Tomography) was investigated. The breast cancer detection system under development uses 16 transmit/receive antennas. The signal waveform was a sinusoidal wave at 900 MHz. To solve the 2D inverse scattering problem, we used the 2D FDTD (Finite Difference Time Domain) method for forward calculation and LMA(Levenberg-Marquardt Algorithm) for optimization. The result of the image reconstruction using the numerical phantom by MRI(Magnetic Resonance Imaging) obtained from real patient of breast cancer showed that we can detect the position of the tumor accurately.

A Study on the Leakage Characteristic Evaluation of High Temperature and Pressure Pipeline at Nuclear Power Plants Using the Acoustic Emission Technique (음향방출기법을 이용한 원전 고온 고압 배관의 누설 특성 평가에 관한 연구)

  • Kim, Young-Hoon;Kim, Jin-Hyun;Song, Bong-Min;Lee, Joon-Hyun;Cho, Youn-Ho
    • Journal of the Korean Society for Nondestructive Testing
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    • v.29 no.5
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    • pp.466-472
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    • 2009
  • An acoustic leak monitoring system(ALMS) using acoustic emission(AE) technique was applied for leakage detection of nuclear power plant's pipeline which is operated in high temperature and pressure condition. Since this system only monitors the existence of leak using the root mean square(RMS) value of raw signal from AE sensor, the difficulty occurs when the characteristics of leak size and shape need to be evaluated. In this study, dual monitoring system using AE sensor and accelerometer was introduced in order to solve this problem. In addition, artificial neural network(ANN) with Levenberg.Marquardt(LM) training algorithm was also applied due to rapid training rate and gave the reliable classification performance. The input parameters of this ANN were extracted from varying signal received from experimental conditions such as the fluid pressure inside pipe, the shape and size of the leak area. Additional experiments were also carried out and with different objective which is to study the generation and characteristic of lamb and surface wave according to the pipe thickness.

Estimation of Probability Density Function of Tidal Elevation Data (조위자료의 확률밀도함수 추정)

  • Hong Yeon Cho;Jeong Shin Taek;Oh Young Min
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.16 no.3
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    • pp.152-161
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    • 2004
  • Double-peak normal distribution function was suggested as the probability density function of the tidal elevation data in Korean coastal zone. Frequency distribution analysis was carried out using hourly tidal elevation data of the ten tidal gauging stations, i.e., Incheon, Kunsan, Mokpo, Cheju, Yeosu, Masan, Gadeokdo, Pusan, Pohang, and Sokcho which were served through the Internet Homepage by the National Ocean Research Institute. Based on the RMS error and $R^2$ value comparison analysis, it was found that this suggested function as the probability density function of the tidal elevation data was found to be more appropriate than the normal distribution function. The parameters of the double-peak function were estimated optimally using Levenberg-Marquardt method which was modified from the Newton method. The estimated parameters were highly correlated with the non-tidal constants of the tidal gauging stations.

A Case Study on Action Learning for the College Course 'Media Education for Children' (대학에서의 '아동미디어교육' 수업을 위한 액션러닝 사례 연구)

  • Hyun, Eunja;Kook, Kyeong-a;Kim, Bo-Gyu;Kim, Min-Jung;Kim, Hye-Min
    • The Journal of the Korea Contents Association
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    • v.18 no.5
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    • pp.525-538
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    • 2018
  • Action learning is a teaching method that is taught through the process of finding real problems and finding solutions. The purpose of this study was to examine the effectiveness of action learning for the college course 'media education for children' which was offered by the Department of Child Psychology and Education at S university in Seoul. According to the process of action learning suggested by Marquardt(2000), college students developed the problem of children's news literacy education and set the purpose, goal and contents of news literacy and developed teaching and learning method for the 6th grade elementary students and applied it to the education field. The college students' evaluation about the action learning lesson were collected by questionnaire and verbal. They found that active and voluntary problem-solving and field application through action learning helped to achieve the goals of the children's media education class. Finally, the importance of close cooperation with the educational field and of appropriate feedback were discussed as a necessary condition of action learning teaching method.

Estimation and Analysis of Two Moving Platform Passive Emitter Location Using T/FDOA and DOA (이동 수신기 환경에서 연속된 T/FDOA와 DOA를 이용한 고정 신호원의 위치 추정 방법)

  • Park, Jin-Oh;Lee, Moon Seok;Park, Young-Mi
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.1
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    • pp.121-131
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    • 2015
  • Passive emitter localization is preferred to use a small number of receivers as possible for the efficiency of strategic management in the field of modern electronic warfare support. Accurate emitter localization can be expected when utilizing continuous measurable parameters and a appropriate combination of theirs. For this reason, we compare CRLB (Cramer-Rao lower bound) of two moving platform with various measurable parameters to choose a appropriate combination of parameters for a better localization performance. And we propose the passive emitter localization method based on Levenberg-Marquardt algorithm with combined TDOA/FDOA and DOA to achieve better accuracy of emitter localization which is located on the ground and stationary. In addition, we present a method for determining the initial emitter position for LM algorithm's input to avoid the divergence of estimation and local minimum.