• 제목/요약/키워드: error minimization

검색결과 273건 처리시간 0.026초

충전부에 접촉된 인체의 전위특성에 관한 연구 (A Study on the Potential Characteristics of Human-body Contacted the Charging Part)

  • 송길목;최충석;정연하;노영수;곽희로;박중신
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2004년도 하계학술대회 논문집 C
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    • pp.1942-1944
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    • 2004
  • In this paper, we studied on the potential characteristics of human-body contacted the charging part. A charging part of electrical facilities and the earth are simulated by the e1ectrode pole and conductive rubber plates respectively. As the results of these follows, when the potential distribution of the human-body contacted the charging part is far from the electrode pole, a lot of currents flow through the human-body. Besides human-body non-contacted the charging part is affected by step voltage. Therefore, we could find out the causes of the electric shock accidents and be expected to the data for minimization of human error occurred the workspace.

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Blind adaptive receiver for uplink multiuser massive MIMO systems

  • Shin, Joonwoo;Seo, Bangwon
    • ETRI Journal
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    • 제42권1호
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    • pp.26-35
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    • 2020
  • Herein, we consider uplink multiuser massive multiple-input multiple-output systems when multiple users transmit information symbols to a base station (BS) by applying simple space-time block coding (STBC). At the BS receiver, two detection filters for each user are used to detect the STBC information symbols. One of these filters is for odd-indexed symbols and the other for even-indexed symbols. Using constrained output variance metric minimization, we first derive a special relation between the closed-form optimal solutions for the two detection filters. Then, using the derived special relation, we propose a new blind adaptive algorithm for implementing the minimum output variance-based optimal filters. In the proposed adaptive algorithm, filter weight vectors are updated only in the region satisfying the special relation. Through a theoretical analysis of the convergence speed and a computer simulation, we demonstrate that the proposed scheme exhibits faster convergence speed and lower steady-state bit error rate than the conventional scheme.

하이브리드법에 의한 HMM-Net 분류기의 학습 (On Learning of HMM-Net Classifiers Using Hybrid Methods)

  • 김상운;신성효
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 1998년도 추계종합학술대회 논문집
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    • pp.1273-1276
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    • 1998
  • The HMM-Net is an architecture for a neural network that implements a hidden Markov model (HMM). The architecture is developed for the purpose of combining the discriminant power of neural networks with the time-domain modeling capability of HMMs. Criteria used for learning HMM-Net classifiers are maximum likelihood (ML), maximum mutual information (MMI), and minimization of mean squared error(MMSE). In this paper we propose an efficient learning method of HMM-Net classifiers using hybrid criteria, ML/MMSE and MMI/MMSE, and report the results of an experimental study comparing the performance of HMM-Net classifiers trained by the gradient descent algorithm with the above criteria. Experimental results for the isolated numeric digits from /0/ to /9/ show that the performance of the proposed method is better than the others in the respects of learning and recognition rates.

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Pseudoinverse Matrix Decomposition Based Incremental Extreme Learning Machine with Growth of Hidden Nodes

  • Kassani, Peyman Hosseinzadeh;Kim, Euntai
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제16권2호
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    • pp.125-130
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    • 2016
  • The proposal of this study is a fast version of the conventional extreme learning machine (ELM), called pseudoinverse matrix decomposition based incremental ELM (PDI-ELM). One of the main problems in ELM is to determine the number of hidden nodes. In this study, the number of hidden nodes is automatically determined. The proposed model is an incremental version of ELM which adds neurons with the goal of minimization the error of the ELM network. To speed up the model the information of pseudoinverse from previous step is taken into account in the current iteration. To show the ability of the PDI-ELM, it is applied to few benchmark classification datasets in the University of California Irvine (UCI) repository. Compared to ELM learner and two other versions of incremental ELM, the proposed PDI-ELM is faster.

Detection of Second-Layer Corrosion in Aging Aircraft Fuselage

  • Kim, Noh-Yu;Achenbach, J.D.
    • 비파괴검사학회지
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    • 제26권6호
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    • pp.417-426
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    • 2006
  • A Digital X-ray imaging system using Compton backscattering has been developed to obtain a cross-sectional profile and mass loss of corroded lap-splices of aging aircraft from density variation. A slit-type camera was designed to focus on a small scattering volume inside the material, from which the backscattered photons are collected by a collimated scintillator detector for interpretation of material characteristics. The cross section of the lap-joint is scanned by moving the scattering volume through the thickness direction of the specimen. The mass loss of each layer has been estimated from a Compton backscatter A-scan to obtain the thickness of each layer including the aluminum sheet, the corrosion layer and the sealant. Quantitative information such as location and width of planar corrosion in the lap splices of fuselages is obtained by deconvolution using a nonlinear least-square error minimization method(BFGS method): A simple reconstruction model is also introduced to overcome distortion of the Compton backscatter data due to attenuation effects attributed to beam hardening and quantum noise.

On Development of Lower Order Aggregated Model for the Linear Large-Scale Model

  • 유병우
    • 경영과학
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    • 제15권2호
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    • pp.125-142
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    • 1998
  • The aggregation on linear large-scale dynamic systems is examined in this paper and a "two-step" approach is proposed. In this procedure, the aggregated system consists of two subsystems. The first subsystem represents aggregation through the retainment of dominant eigenvalues of the original system, leading to a first approximation of the desired output of the original system. The purpose of augmenting it with a second subsystem is to provide an estimation of the error on the first approximation, thus permitting a second correction to the output approximation and resulting in an output approximation of greater accuracy. Optimization techniques are discussed for the determination of unknown parameters in the aggregated system. These techniques use minimization principles of certain suitable performance indices and are developed for both single input-single output and multiple input-multiple output system. Numerical examples illustrating these procedures are given and the results are compared with those obtained using existing methods. Finally, a pharmacokinetics problem is studied from the aggregation point of view.

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Halbach 배열 영구자석형 Planar Motor의 수직적 해석 및 영향 (A study of normal force and its effect in a SPMPM with Halbach array)

  • 황예;주건배;한광규;김규탁
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2006년도 추계학술대회 논문집 전기기기 및 에너지변환시스템부문
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    • pp.86-88
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    • 2006
  • This paper presents normal force analysis and its minimization of synchronous permanent magnet planar motor(SPMPM) with Halbach array. Firstly, the experimental error of thrust is investigated and it is caused by the friction force generated by normal force. Then normal force Is analyzed by Maxwell stress tensor. At last, the normal force is minimized by using genetic algorithm and it is decreased from 672.83[N] to 144.24[N] remarkably.

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Prediction of concrete strength using serial functional network model

  • Rajasekaran, S.;Lee, Seung-Chang
    • Structural Engineering and Mechanics
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    • 제16권1호
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    • pp.83-99
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    • 2003
  • The aim of this paper is to develop the ISCOSTFUN (Intelligent System for Prediction of Concrete Strength by Functional Networks) in order to provide in-place strength information of the concrete to facilitate concrete from removal and scheduling for construction. For this purpose, the system is developed using Functional Network (FN) by learning functions instead of weights as in Artificial Neural Networks (ANN). In serial functional network, the functions are trained from enough input-output data and the input for one functional network is the output of the other functional network. Using ISCOSTFUN it is possible to predict early strength as well as 7-day and 28-day strength of concrete. Altogether seven functional networks are used for prediction of strength development. This study shows that ISCOSTFUN using functional network is very efficient for predicting the compressive strength development of concrete and it takes less computer time as compared to well known Back Propagation Neural Network (BPN).

Dimethyl Ether-Air 예혼합화염의 축소 반응 메카니즘 개발 (The Development of the Short Mechanism for Premixed Dimethyl Ether-Air Flames)

  • 이기용;이수각
    • 한국연소학회:학술대회논문집
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    • 한국연소학회 2012년도 제45회 KOSCO SYMPOSIUM 초록집
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    • pp.211-214
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    • 2012
  • A short reaction mechanism was developed in order to predict the flame phenomena in premixed Dimethyl Ether-Air flame with the methods of SEM-CM(Simulation Error Minimization Connectivity Method), sensitivity analysis, and the rate of production analysis. It consisted of 31 species including nitrogen as inert gas and 177 elementary reactions. The flame structures obtained using a detailed reaction mechanism and the short reaction mechanism were compared with various equivalence ratios and pressure, and the results were in good agreement. Therefore, the short reaction mechanism would be used to aim at studying the development of a reduced reaction mechanism.

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The Development of Application Programs for Optimal Feeder Operation Through Distribution Automatic System

  • Ha, Bok-Nam;Seol, Ieel-Ho;Jeong, Mi-Ae
    • KIEE International Transactions on Power Engineering
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    • 제4A권1호
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    • pp.42-47
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    • 2004
  • This paper presents the various application programs for the Distribution Automation System (DAS) of the Korea Electric Power Corporation (KEPCO)'s distribution system. These programs are developed to allow for optimal operation in the areas of feeder automation, relay coordination, loss minimization and so on. They are single line diagram auto creation programs for the feeder, service restoration program, protection coordination program, data error detection program, and optimal network reconfiguration program. The details of these programs are presented for validity and effectiveness.