• Title/Summary/Keyword: Modelling Error

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A Measurement Error Correction Algorithm of Road Structure for Traveling Vehicle's Fluctuation Using VF Modeling (VF 모델링을 이용한 주행차량의 진동에 대한 도로 계측오차 보정 알고리듬)

  • Jeong, Yong-Bae;Kim, Jung-Hyun;Seo, Kyung-Ho;Kim, Tae-Hyo
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • 2005.11a
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    • pp.190-200
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    • 2005
  • In this paper, the image modelling of road's lane markings is established using view frustum(VF) modeling. This algorithm also involve the real time processing of the 3D position coordinate and the distance data from the camera to the points on the 3D world coordinate by the camera calibration. In order to reduce their measurement error, an useful algorithm for which analyze the geometric variations clue to traveling vehicle's fluctuation using VF model is proposed. In experiments, without correction, for instance, the $0.4^{\circ}$ of pitching rotation gives the error of $0.4^{\sim}0.6m$ at the distance of 10m, but the more far distance cause exponentially the more error. We confirmed that this algorithm can be reduced less than 0.1m of error at the same condition.

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Comparison of the neural networks with spline interpolation in modelling superheated water (물의 과열증기 모델링에 대한 신경회로망과 스플라인법 비교)

  • Lee, Tae-Hwan;Park, Jin-Hyun;Kim, Bong-Hwan
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2007.10a
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    • pp.246-249
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    • 2007
  • In numerical analysis for phase change material, numerical values of thermodynamic properties such as temperature, pressure, specific volume, enthalpy and entropy are required. But the steam table or diagram itself cannot be used without modelling. In this study applicability of neural networks in modelling superheated vapor region of water was examined by comparing with the quadratic spline. neural network consists of an input layer with 2 nodes, two hidden layers and an output layer with 3 nodes. Quadratic spline interpoation method was also applied for comparison. Neural network model revealed smaller percentage error to quadratic spline interpolation. From these results, it is confirmed that the neural networks could be powerful method in modelling the superheated range of the steam table.

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Modelling the wide temperature range of steam table using the neural networks (신경회로망을 사용한 넓은 온도 범위의 증기표 모델링)

  • Lee, Tae-Hwan
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.11
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    • pp.2008-2013
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    • 2006
  • In numerical analysis on evaluating the thermal performance of the thermal equipment, numerical values of thermodynamic properties such as temperature, pressure, specific volume, enthalpy and entropy are required. But the steam table itself cannot be used without modelling. In this study applicability of neural networks in modelling the wide temperature range of wet saturated vapor region was examined. the multi-layer neural network consists of a input layer with 1 node, two hidden layers with 10 and 20 nodes respectively and a output layer with 6 nodes. Quadratic and cubic spline interpoations methods were also applied for comparison. Neural network model revealed similar percentage error to spline interpolation. From these results, it is confirmed that the neural networks could be powerful method in modelling the wide range of the steam table.

Comparison of the neural networks with spline interpolation in modelling superheated water (물의 과열증기 모델링에 대한 신경회로망과 스플라인 보간법 비교)

  • Lee, Tae-Hwan;Park, Jin-Hyun;Kim, Bong-Hwan
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.12 no.4
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    • pp.685-690
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    • 2008
  • In numerically evaluating the thermal performance of the heat exchanger, numerical values of thermodynamic properties such as temperature, pressure, specific volume, enthalpy and entropy are required. But the steam table or diagram itself cannot be directly used without modelling. In this study the applicability of neural networks in modelling superheated water vapor was examined. The multi-layer neural networks consist of an input layer with 2 nodes, two hidden layers with 15 and 25 nodes respectively and an output layer with 3 nodes. Quadratic spline interpolation was also applied for comparison. Neural networks model revealed smaller percentage error compared with spline interpolation. From this result, it is confirmed that the neural networks could be a powerful method in modelling the superheated water vapor.

A Single Sensor Active Noise Control Considering The Characteristics of The Speaker and The Microphone (스피커와 마이크의 전달특성을 고려한 단일 센서 능동소음제어)

  • 김현태;박장식
    • Journal of Korea Multimedia Society
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    • v.6 no.7
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    • pp.1131-1138
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    • 2003
  • Active noise control(ANC) is an approach to noise reduction in which a secondary noise source destructively interferes with the unwanted noise is introduced. Generally, the performance of ANC is determined how well a secondary noise tracks noises. A secondary noise is generated from the cancelling speaker and a error sensor pick up error signal. The transfer function between the cancelling speaker and the error sensor is not flat and distorts secondary noises. Consequently, the performance of ANC is degraded by the transfer function. In this paper, a single sensor ANC which considers the characteristics of the speaker and the error sensor is proposed. To reduce distortion of secondary noises, the transfer function is estimated by adaptive inverse modelling and the primary noises are estimated by Kalman filter. Experimental results show that the proposed single sensor ANC effectively attenuates noises.

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Spacecraft Attitude Determination Study using Predictive Filter (Predictive Filter를 이용한 인공위성 자세결정 연구)

  • Choi , Yoon-Hyuk;Bang, Hyo-Choong
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.33 no.11
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    • pp.48-56
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    • 2005
  • Predictive filter theory proposed recently can be characterized by inherent advantages of estimating modelling error and overcoming the disadvantage of the Kalman filter theory. A one-step ahead error is minimized to produce optimized filter performance in the form of the predictive filter. The main advantage of this filter lies in the ability to estimate both state vector and system model error. In this paper, attitude estimation results based upon the predictive filter theory is addressed. Mathematical formulation for estimating bias signal is peformed by using the predictive filter theory, and attitude estimation based upon vector observation is presented. From the results of this study, the potential applicability of the predictive filter is highlighted.

The Effects of Roll Misalignment Errors, Shooting Distance, and Vergence Condition of 3D Camera on 3D Visual Fatigue (시각피로 모형: 카메라의 회전오차, 촬영 거리, 수렴 조건이 입체 시각피로에 미치는 영향)

  • Li, Hyung-Chul O.;Park, JongJin;Kim, ShinWoo
    • Journal of Broadcast Engineering
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    • v.18 no.4
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    • pp.589-598
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    • 2013
  • In order to understand 3D visual fatigue, it is necessary to examine the visual fatigue induced by camera parameters as well as that induced by a pre-existing 3D content. In the present study, we examined the effects of camera parameters, such as roll misalignment error, shooting distance and vergence condition on 3D visual fatigue and we modelled it. The results indicate that roll misalignment error, shooting distance and vergence condition affect 3D visual fatigue and the effect of roll misalignment error on 3D visual fatigue is evident specifically when screen disparity is relatively small.

Floating-Poing Quantization Error Analysis in Subband Codes System

  • Park, Kyu-Sik
    • The Journal of the Acoustical Society of Korea
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    • v.16 no.1E
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    • pp.41-48
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    • 1997
  • The very purpose of subband codec is the attainment of data rate compression through the use of quantizer and optimum bit allocation for each decimated signal. Yet the question of floating-point quantization effects in subband codec has received scant attention. There has been no direct focus on the analysis of quantization errors, nor on design with quantization errors embedded explicitly in the criterion. This paper provides a rigorous theory for the modelling, analysis and optimum design of the general M-band subband codec in the presence of the floating-point quantization noise. The floating-point quantizers are embedded into the codec structure by its equivalent multiplicative noise model. We then decompose the analysis and synthesis subband filter banks of the codec into the polyphase form and construct an equivalent time-invariant structure to compute exact expression for the mean square quantization error in the reconstructed an equivalent time-invariant structure to compute exact expression for the mean square quantization error in the reconstructed output. The optimum design criteria of the subband codec is given to the design of the analysis/synthesis filter bank and the floating-point quantizer to minimize the output mean square error. Specific optimum design examples are developed with two types of filter of filter banks-orthonormal and biorthogonal filter bank, along with their perpormance analysis.

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A New Design Method of Sliding Mode Fuzzy Controller with Robust and fast Performance (강인성과 응답 성능을 고려한 슬라이딩모드 퍼지 제어기 설계에 관한 연구)

  • 박창우;이장욱
    • Proceedings of the IEEK Conference
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    • 1998.10a
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    • pp.425-428
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    • 1998
  • This paper proposes a new fuzzy controller using variable structure control theory. In this paper, after the time-varying fuzzy sliding surface is designed, the fuzzy rules are defined based on the variable structure control theory. This design method makes the fuzzy controller design more structured and can guarantee the stability and robustness of the fuzzy controller and overcome the shortcoming of the variable structure system. Through computer simulation and experiment of nonlinear inverted pendulum system, this thesis demonstrate that system has the robustness against disturbance and modelling error, and the tracking performance of it is improved.

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