• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 제14회 신호처리 합동 학술대회 논문집
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• pp.91-94
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• 2001

Recently a constant-norm constraint equation-error method was proposed to solve the bias problem in adaptive IIR filtering. However, the method adopts a fixed step-size and thus results in slow convergence for a small step-size and significant misadjustment error for a largestep-size. In this paper, we propose a variable step-size (VSS) algorithm that greatly improves convergence properties of the constant-norm constraint equation-error method. The analysis and the simulation results show that the proposed method indeed achieves both fast convergence and small misadjustment error.

• The Journal of the Acoustical Society of Korea
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• 제16권3E호
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• pp.62-68
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• 1997

In this paper, a modified adaptive sign (MAS) algorithm based on a mixed norm error criterion is proposed. The mixed norm error criterion of be minimized is constructed as a combined convex function of the mean-absolute error and the mean-absolute error to the third power. A convergence analysis of the MAS algorithm is also presented. Under a set of mild assumptions, a set of nonlinear evolution equations that characterizes the statistical mean and mean-squared behavior of the algorithm is derived. Computed simulations are carried out to verify the validity of our derivations.

• 한국산업융합학회 논문집
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• 제3권2호
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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.

• 충청수학회지
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• 제24권2호
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• pp.141-146
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• 2011

Kou et al. presented a class of new variants of Ostrowski's method in their paper (J. of Comput. Appl. Math., 209(2007), pp.153-159) whose title is "Some variants of Ostrowski's method with seventh-order convergence". They proposed an incorrect error equation, although they showed a correct seventh-order of convergence. The main objective of this note is to establish the correct error equation of the method and confirm its validity via concrete numerical examples.

• 충청수학회지
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• 제21권4호
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• pp.483-492
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• 2008

The k-fold pseudo-Newton's method is proposed and its convergence behavior is investigated near a simple zero. The order of convergence is proven to be at least k + 2. The asymptotic error constant is explicitly given in terms of k and the corresponding simple zero. High-precison numerical results are successfully implemented via Mathematica and illustrated for various examples.

• 충청수학회지
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• 제25권3호
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• pp.579-587
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• 2012

A fourth-order family of triparametric extensions of Jarratt's method are proposed in this paper to find a simple root of nonlinear algebraic equations. Convergence analysis including numerical experiments for various test functions apparently verifies the fourth-order convergence and asymptotic error constants.

• 충청수학회지
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• 제27권1호
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• pp.133-143
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• 2014

A new three-step quadraparametric family of eighth-order iterative methods free from second derivatives are proposed in this paper to find a simple root of a nonlinear equation. Convergence analysis as well as numerical experiments confirms the eighth-order convergence and asymptotic error constants.

• 전기전자학회논문지
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• 제23권1호
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• pp.120-126
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• 2019

최근 에너지 인터넷에서 지능형 원격검침 인프라를 이용하여 확보된 대량의 전력사용데이터를 기반으로 효과적인 전력수요 예측을 위해 다양한 기계학습기법에 관한 연구가 활발히 진행되고 있다. 본 연구에서는 전력량 데이터와 같은 시계열 데이터에 대해 효율적으로 패턴인식을 수행하는 인공지능 네트워크인 Gated Recurrent Unit(GRU)을 기반으로 딥 러닝 모델을 제안하고, 실제 가정의 전력사용량 데이터를 토대로 예측 성능을 분석한다. 제안한 학습 모델의 예측 성능과 기존의 Long Short Term Memory (LSTM) 인공지능 네트워크 기반의 전력량 예측 성능을 비교하며, 성능평가 지표로써 Mean Squared Error (MSE), Mean Absolute Error (MAE), Forecast Skill Score, Normalized Root Mean Squared Error (RMSE), Normalized Mean Bias Error (NMBE)를 이용한다. 실험 결과에서 GRU기반의 제안한 시계열 데이터 예측 모델의 전력량 수요 예측 성능이 개선되는 것을 확인한다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 1998년도 춘계학술대회논문집; 용평리조트 타워콘도, 21-22 May 1998
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• pp.670-677
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• 1998

Many of the adaptive noise control systems utilize a form of the least mean square (LMS) algorithm. In the active control of noise, it is common practice to locate an error microphone far from the control source to avoid the near-field effects by evanescent waves. Such a distance between the control source and the error microphone makes a certain level of time-delay inevitable and, hence, may yield undesirable effects on the convergence properties of control algorithms such as filtered-x LMS. This paper discusses the dependence of the convergence rate on the acoustic error path in these popular algorithms and introduces new algorithms which increase the convergence region regardless of the time-delay in the acoustic error path. Performances of the new LMS algorithms are presented in comparison with those by the conventional algorithms based on computer stimulations and experiments.

• 한국산업융합학회 논문집
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• 제24권6_2호
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• pp.947-952
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• 2021

In this paper, the simplified kinematic error model for Delta parallel robot is presented, which can enable the analytical forward kinematics essentially for kinematic calibration calculations instead of the numerical one. The simplified kinematic error model is proposed and the forward kinematics including the error parameters is analytically derived. The kinematic calibration algorithm of the Delta parallel robot with 90 degree arrangement using laser tracker and the experiment result are presented.