• Title/Summary/Keyword: MLP.

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COMPARATIVE STUDY ON FLUX FUNCTIONS AND LIMITERS FOR THE EULER EQUATIONS (Euler 방정식의 유량함수(Flux Function)와 제한자(Limiter) 특성 비교 연구)

  • Chae, E.J.;Lee, S.
    • Journal of computational fluids engineering
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    • v.12 no.1
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    • pp.43-52
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    • 2007
  • A comparative study on flux functions for the 2-dimensional Euler equations has been conducted. Explicit 4-stage Runge-Kutta method is used to integrate the equations. Flux functions used in the study are Steger-Warming's, van Leer's, Godunov's, Osher's(physical order and natural order), Roe's, HLLE, AUSM, AUSM+, AUSMPW+ and M-AUSMPW+. The performance of MUSCL limiters and MLP limiters in conjunction with flux functions are compared extensively for steady and unsteady problems.

Spoken Digit Recognition Using URAN(Universally Reconstructable Artificial Neural-network)VLSI Chip (URAN VLSI chip을 이용한 숫자음 인식)

  • 김기철
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1993.06a
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    • pp.117-120
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    • 1993
  • In this paper, we explore the possibility of URAN(Universally Reconstructable Artificial Neural-network) VLSI chip for speech recognition. URAN, a newly developed analog-digital hybrid neural chip, is discussed in respects to its input, output, and weight accuracy and their relations to its performance on speaker independent digit recognition. Multi-layer perceptron(MLP) nets including a large frame input layer are used to recognize a digit syllable at a forward retrieval. The simulation results using the full and limited floating precision computations for the input, output, and weight variables of the network give the comparable classification performance. An MLP with piecewise linear hidden and output units is also trained successfully using low accuracy computation.

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APPLICATION OF NEURAL NETWORK FOR THE CLOUD DETECTION FROM GEOSTATIONARY SATELLITE DATA

  • Ahn, Hyun-Jeong;Ahn, Myung-Hwan;Chung, Chu-Yong
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.34-37
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    • 2005
  • An efficient and robust neural network-based scheme is introduced in this paper to perform automatic cloud detection. Unlike many existing cloud detection schemes which use thresholding and statistical methods, we used the artificial neural network methods, the multi-layer perceptrons (MLP) with back-propagation algorithm and radial basis function (RBF) networks for cloud detection from Geostationary satellite images. We have used a simple scene (a mixed scene containing only cloud and clear sky). The main results show that the neural networks are able to handle complex atmospheric and meteorological phenomena. The experimental results show that two methods performed well, obtaining a classification accuracy reaching over 90 percent. Moreover, the RBF model is the most effective method for the cloud classification.

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Security Level Decision Problem in MLP-based Secure OS (다중등급 보안 운영체제에서의 보안 등급 결정 문제)

  • Kang, Jung-Min;Shin, Wook;Park, Chun-Gu;Lee, Dong-Ik;Lee, Kyeong-Ho
    • Annual Conference of KIPS
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    • 2001.10b
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    • pp.943-946
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    • 2001
  • 대부분의 안전한 운영체제는 주체와 객체에 보안 등급을 부여하여 운영하는 다중등급 정책(MLP: Multi-Level Policy)을 수용하고 있으며, BLP 모델은 이 정책을 표현하는 검증된 대표적인 모델이다. 하지만 이러한 다중 등급 보안 운영체제들은 접근 주체인 프로세스가 접근 객체로서 존재하는 등급화 된 프로그램을 실행 시 새로운 프로세스를 위한 보안 등급을 부여해야 하는데, 접근 주체와 접근 객체의 보안 등급이 다를 경우 보안 등급 결정 문제가 발생하며 정보보호의 목적에 위배되는 결과가 발생한다. 이에 본 논문에서는 위에 언급된 문제를 해결할 수 있는 방안을 BLP 모델 측면에서 고찰한다.

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Development of EMD-based Fault Diagnosis System for Induction Motor (EMD 기반의 유도 전동기 고장 진단 시스템 개발)

  • Kang, Jungsun
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.24 no.9
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    • pp.675-681
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    • 2014
  • This paper proposes a fault diagnosis system for an induction motor. This system uses empirical mode decomposition(EMD) to extract fault signatures and multi-layer perceptron(MLP) neural network to facilitate an accurate fault diagnosis. EMD can not only decompose a signal adaptively but also provide intrinsic mode functions(IMFs) containing natural oscillatory modes of the signal. However, every IMF does not represent fault signature, an IMF selection algorithm based on harmonics and their energy of each IMF is proposed. The selected IMFs are utilized for fault classification using MLP and this system shows approximately 98 % diagnosis accuracy for the fault vibration signal of the induction motor.

Rail Surface Defect Detection System of Next-Generation High Speed Train (차세대 고속열차의 레일표면 결함 검출 시스템)

  • Choi, Woo-Yong;Kim, Jeong-Yeon;Yang, Il-Dong
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.66 no.5
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    • pp.870-876
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    • 2017
  • In this paper, we proposed the automatic vision inspection system using multi-layer perceptron to detect the defects occurred on rail surface. The proposed system consists of image acquisition part and analysis part. Rail surface image is acquired as equal interval using line scan camera and lighting. Mean filter and dynamic threshold is used to reduce noise and segment defect area. Various features to characterize the defects are extracted. And they are used to train and distinguish defects by MLP-classifier. The system is installed on HEMU-430X and applied to analyze the rail surface images acquired from Honam-line at high speed up to 300 km/h. Recognition rate is calculated through comparison with manual inspection results.

A Study on Single Vowels Recognition using VQ and Multi-layer Perceptron (VQ와 Multi-layer perceptron을 이용한 단모음 인식에 관한 연구)

  • 안태옥;이상훈;김순협
    • The Journal of the Acoustical Society of Korea
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    • v.12 no.1
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    • pp.55-60
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    • 1993
  • 본 논문은 불특정 화자의 단모음 인식에 관한 연구로써, VQ(Vectro Quantization)와 MLP(multi-layer perceptron)에 의한 음성 인식 방법을 제안한다. 이 방법은 VQ codebook을 구하고 이를 이용해서 관측열(observation sequence)을 구해각 codeword가 데이터로부터 가질 수 있는 확률값을 계산하여 이 값을 신경 회로망의 입력으로 사용하는 방법이다. 인식 대상으로는 한국어 단모음을 선정하였으며 10명의 남성 화자가 8개의 단모음을 10번씩 발음한 것으로 시스템의 효율성을 알아보기 위해 VQ/HMM(hidden markov model)에 의한 인식과 비교 실험한다. 실험 결과에 의하면, 시스템의 단순성에도 불구하고 학습능력애 뛰어난 관계로 VQ/HMM보다 VQ와 MLP에 의한 음성 인식률이 향상됨을 보여준다.

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Nonlinear Approximations Using Modified Mixture Density Networks (변형된 혼합 밀도 네트워크를 이용한 비선형 근사)

  • 조원희;박주영
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2004.10a
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    • pp.543-546
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    • 2004
  • Bishop과 Nabney에 의해 소개된 기존의 혼합 밀도 네트워크(Mixture Density Network)에서는 조건부 확률밀도 함수의 매개변수들(parameters)이 하나의 MLP(multi-layer perceptron)의 출력 벡터로 주어진다. 최근에는 변형된 혼합 밀도 네트워크(Modified Mixture Density Network)라고 하는 이름으로 조건부 확률밀도 함수의 선분포(priors), 조건부 평균(conditional means), 그리고 공분산(covariances) 등이 각각 독립적인 MLP의 출력벡터로 주어지는 경우를 다룬 연구가 보고된 바 있다. 본 논문에서는 조건부 평균이 입력에 관해 선형인 경우를 위한 버전에 대한 이론과 매트랩 프로그램 개발 및 적용을 다룬다. 본 논문에서는 우선 일반적인 혼합 밀도 네트워크에 대해 간단히 설명하고, 혼합 밀도 네트워크의 출력인 다층 퍼셉트론의 매개변수를 각각 다른 다층 퍼셉트론에서 학습시키는 변형된 혼합 밀도 네트워크를 설명한 후, 각각 다른 다층 퍼셉트론을 통해 매개변수를 얻는 것은 동일하나 평균값은 선형함수를 통해 얻는 혼합 밀도 네트워크 버전을 소개한다. 그리고, 모의실험을 통하여 이러한 혼합 밀도 네트워크를의 적용가능성에 대해 알아본다.

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Fuzzy System and Knowledge Information for Stock-Index Prediction

  • Kim, Hae-Gyun;Bae, Hyeon;Kim, Sung-Shin
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.172.6-172
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    • 2001
  • In recent years, many attempts have been made to predict the behavior of bonds, currencies, stock, or other economic markets. Most previous experiments used multilayer perceptrons(MLP) for stock market forecasting, The Kospi 200 Index is modeled using different neural networks and fuzzy system predictions. In this paper, a multilayer perceptron architecture, a dynamic polynomial neural network(DPNN) and a fuzzy system are used to predict the Kospi 200 index. The results of prediction is compared with the root mean squared error(RMSE) and the scatter plot. The results show that the fuzzy system is performing slightly better than DPNN and MLP. We can develop the desired fuzzy system by learning methods ...

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STUDY ON FLUX FUNCTIONS FOR THE EULER EQUATIONS (Euler 방정식의 Flux Function 특성 비교 연구)

  • Chae, E.J.;Lee, S.
    • 한국전산유체공학회:학술대회논문집
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    • 2006.10a
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    • pp.36-40
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    • 2006
  • A comparative study on flux functions for the 2-dimensional Euler equations has been conducted. Explicit 4-stage Runge-Kutta method is used to integrate the equations. Flux functions used in the study are Steger-Warming's, van Leer's. Godunov's, Osher's(physical order and natural order), Roe's, HILE, AUSM, AUSM+ and AUSMPW+. The performance of MUSCL limiters and MLP limiters in conjunction with flux functions are compared extensively for steady and unsteady problems.

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