• Title/Summary/Keyword: Reducing Parameter

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Reducing Bias of the Minimum Hellinger Distance Estimator of a Location Parameter

  • Pak, Ro-Jin
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.1
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    • pp.213-220
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    • 2006
  • Since Beran (1977) developed the minimum Hellinger distance estimation, this method has been a popular topic in the field of robust estimation. In the process of defining a distance, a kernel density estimator has been widely used as a density estimator. In this article, however, we show that a combination of a kernel density estimator and an empirical density could result a smaller bias of the minimum Hellinger distance estimator than using just a kernel density estimator for a location parameter.

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Jackknife Estimation in an Exponential Model

  • Woo, Jung-Soo
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.1
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    • pp.193-200
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    • 2004
  • Parametric estimation of truncated point in a truncated exponential distribution will be considered. The MLE, bias reducing estimator and the ordinary jackknife estimator of the truncated parameter will be compared by mean square errors. And the MME and MLE of mean parameter and estimations of the right tail probability in the distribution will be compared by their MSE's.

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A Study on Reducing Profile Error of Multi Spindle Control in NC Machine Tools (NC 공작기계(工作機械) 동시다축제어(同時多軸制御)에서의 오차 저감)

  • Park, Jong-Bong
    • Journal of the Korean Society of Industry Convergence
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    • v.3 no.2
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    • pp.115-121
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    • 2000
  • This paper presents reducing method of profile error on a mechanical tuning for multi-spindle control of NC machine tools. To reduce the profile error in the feed drive system, it is useful to adopt same transfer function of multi spindle machine tools. By selecting the correction vector of servo rigidity and natural vibration on JK map, multi spindle control can be tuned by mechanical parameters with small profile error.

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Parameter Reduction in Digital Adaptive Flight Control System for Spaceplanes

  • Togasaki, Yoshihiro;Shimada, Yuzo;Uchiyama, Kenji
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.995-1000
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    • 2004
  • A digital adaptive flight control system is presented for a Japanese automatic landing flight experiment vehicle (ALFLEX). In previous adaptive control systems based on a linear-parameter-varying (LPV) form, the output behavior was excellent, while the behavior of the adjusted parameters was unsatisfactory. In the present study, to obtain a more appropriate parameter adjustment law, the relationship between the coefficient matrices in a continuous-time state equation and the coefficients of a pulse transfer function in a discrete system for conventional aircraft is investigated. As a result, it is revealed that the coefficients of the numerator can be treated as a linear function of dynamic pressure (linear-parameter-varying: LPV), while the coefficients of the denominator can be treated as constant (linear-time-invariant: LTI). From the above analysis, an improved parameter adjustment law is derived by reducing the number of the adjustment parameters. Simulation results also revealed both good output tracking and good parameter adjustment compared with the previous results.

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Camera Extrinsic Parameter Estimation using 2D Homography and LM Method based on PPIV Recognition (PPIV 인식기반 2D 호모그래피와 LM방법을 이용한 카메라 외부인수 산출)

  • Cha Jeong-Hee;Jeon Young-Min
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.43 no.2 s.308
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    • pp.11-19
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    • 2006
  • In this paper, we propose a method to estimate camera extrinsic parameter based on projective and permutation invariance point features. Because feature informations in previous research is variant to c.:men viewpoint, extraction of correspondent point is difficult. Therefore, in this paper, we propose the extracting method of invariant point features, and new matching method using similarity evaluation function and Graham search method for reducing time complexity and finding correspondent points accurately. In the calculation of camera extrinsic parameter stage, we also propose two-stage motion parameter estimation method for enhancing convergent degree of LM algorithm. In the experiment, we compare and analyse the proposed method with existing method by using various indoor images to demonstrate the superiority of the proposed algorithms.

Robust $L_2-L_{\infty}$ Filter Design for Uncertain Time-Delay Systems via a Parameter-Dependent Lyapunov Function Approach (파라미터에 종속적인 리아푸노프 함수 기법에 의한 불확실 시간지연 시스템을 위한 강인한 $L_2-L_{\infty}$ 필터 설계)

  • Choi, Hyoun-Chul;Jung, Jin-Woo;Shim, Hyung-Bo;Seo, Jin-H.
    • Proceedings of the KIEE Conference
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    • 2008.10b
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    • pp.177-178
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    • 2008
  • An LMI-based method for robust $L_2-L_{\infty}$ filter design is proposed for poly topic uncertain time-delay systems. By using the Projection Lemma and a suitable linearizing transformation, a strict LMI condition for $L_2-L_{\infty}$ filter design is obtained, which does not involve any iterations for design-parameter search, any couplings between the Lyapunov and system matrices, nor any system-dependent filter parameterization. Therefore, the proposed condition enables one to easily adopt, with help of efficient numerical solvers, a parameter-dependent Lyapunov function approach for reducing conservatism, and to design both robust and parameter-dependent filters for uncertain and parameter-dependent time-delay systems, respectively.

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Optimization procedure for parameter design using neural network (파라미터 설계에서 신경망을 이용한 최적화 방안)

  • Na, Myung-Whan;Kwon, Yong-Man
    • Journal of the Korean Data and Information Science Society
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    • v.20 no.5
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    • pp.829-835
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    • 2009
  • Parameter design is an approach to reducing performance variation of quality characteristic value in products and processes. Taguchi has used the signal-to-noise ratio to achieve the appropriate set of operating conditions where variability around target is low in the Taguchi parameter design. However, there are difficulties in practical application, such as complexity and nonlinear relationships among quality characteristics and control factors (design factors), and interactions occurred among control factors. Neural networks have a learning capability and model free characteristics. There characteristics support neural networks as a competitive tool in processing multivariable input-output implementation. In this paper we propose a substantially simpler optimization procedure for parameter design using neural network. An example is illustrated to compare the difference between the Taguchi method and neural network method.

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Experiment Design Parameter for the Effect of Surface Texturing on Metal Surface (금속표면의 Surface texturing 효과에 대한 실험적 설계변수)

  • Chae Y.H.
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2005.06a
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    • pp.1145-1150
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    • 2005
  • The aim of this paper is to investigate the effect of surface texturing on metal surface and to understand the potential of friction reduction through micro-scale dimple to fabricate by photolithography on pin-on-disk test using flat-on-flat contact geometry. It was verify that the friction property with respect to the same pitch has been influence on the size of dimple under lubricated sliding contact. Also, we can recognize from Stribeck curve that the friction property has a connection with the size of dimple. It can explain a relationship between the friction coefficient and a dimensionless parameter for lubrication condition. The friction property has been an effect on the size of surface texture on reduction friction, not only because the density of dimple, but also because the ratio of diameter/pitch. This ratio of approximately 0.5 is recommend under the tested friction condition. It suggested that the ratio of d/p is an important parameter for surface texture design.

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An Enhanced Technologies of Intelligent HVAC PID Controller by Parameter Tuning based on Machine Learning

  • Kim, Jee Hyun;Cho, Young Im
    • Journal of the Korea Society of Computer and Information
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    • v.22 no.12
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    • pp.27-34
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    • 2017
  • Design of an intelligent controller for efficient control in smart building is one of the effective technologies to reduce energy consumption by reducing response time with keeping comfortable level for inhabitants. In this paper, we focus on how to find major parameters in order to enhance the ability of HVAC(heating, ventilation, air conditioning) PID controller. For the purpose of that, we use machine learning technologies for tuning HVAC devices. We show the simulation results to illustrate the behavioral relation of whole system and each control parameter while learning process.

Finite Element Analysis and Geometric Parameter Optimization for BMT Driving Assembly (BMT 구동장치의 유한요소해석 및 형상변수 최적화)

  • Park, Young-Whan;Kwak, Jae-Seob;Jiating, Yan
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.19 no.2
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    • pp.178-183
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    • 2010
  • Base-mounted type(BMT) driving assembly in CNC machine tools is an indispensable part to improve productivity by reducing tool changeover time and to meet the ever-increasing demand of precision machine tools. This study aimed to perform finite element analysis and geometric parameter optimization to improve the efficiency of BMT driving assembly. First, simulations for three-dimensional structural and vibration analysis were performed using ANSYS/Workbench on the initial geometric models of BMT driving assembly. After analyzing stress and deformation concentration zones, several new geometrical models were designed and evaluated by design of experiments and ANSYS/DesignXplorer. Through a series of analysis-evaluation-modification cycles, it was seen that designed models were effective in determining optimal geometry of BMT driving assembly.