• Communications for Statistical Applications and Methods
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• 제8권3호
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• pp.633-641
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• 2001

The least squares method is usually applied when estimating the parameters in the regression models. However the least square estimator is not very efficient when the distribution of the error is skewed. In this paper, we propose the asymmetric least square estimator for a particular nonlinear time series regression model, and give the simple and practical sufficient conditions for the strong consistency of the estimators.

• The Journal of Asian Finance, Economics and Business
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• 제5권1호
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• pp.11-16
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• 2018

This research examines the alternative ways of estimating the coefficient of non-diversifiable risk, namely beta coefficient, in Capital Asset Pricing Model (CAPM) introduced by Sharpe (1964) that is an essential element of assessing the value of diverse assets. The non-parametric methods used in this research are the robust Least Trimmed Square (LTS) and Maximum likelihood type of M-estimator (MM-estimator). The Jackknife, the resampling technique, is also employed to validate the results. According to finance literature and common practices, these coecients have often been estimated using Ordinary Least Square (LS) regression method and monthly return data set. The empirical results of this research pointed out that the robust Least Trimmed Square (LTS) and Maximum likelihood type of M-estimator (MM-estimator) performed much better than Ordinary Least Square (LS) in terms of eciency for large-cap stocks trading actively in the United States markets. Interestingly, the empirical results also showed that daily return data would give more accurate estimation than monthly return data in both Ordinary Least Square (LS) and robust Least Trimmed Square (LTS) and Maximum likelihood type of M-estimator (MM-estimator) regressions.

• 한국통신학회논문지
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• 제39A권6호
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• pp.333-342
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• 2014

본 논문은 OFDM 블록에 파일럿 심볼들이 빗 형태의 패턴에 따라 배치된 경우, 가상 부반송파를 가지는 OFDM 시스템의 channel frequency response (CFR)를 추정하는 여러 방식들을 서로 비교한다. 채널 임펄스 응답을 먼저 예측하는 것이 목적인 minimum mean square error (MMSE) 기반의 채널추정 방식과 누설현상의 억제가 목적인 MMSE 기반의 채널추정 방식이 지금까지 비교되지 않았기 때문에, 본 논문에서는 후자 방식과 전자 방식의 mean square error (MSE) 값들의 차이가 양수가 됨을 유도함으로써 전자 방식의 우수성을 논리적으로 증명한다. 아울러 본 논문에서는 파일럿 수의 변화가 MMSE 기반 채널추정 방식과 least-square (LS) 기반 채널 추정 방식의 성능에 미치는 영향을 조사한다. 컴퓨터 시뮬레이션을 통해 채널추정 방식들의 성능을 정량적으로 확인한다.

• 드라이브 ㆍ 컨트롤
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• 제14권3호
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• pp.40-49
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• 2017

This study presents an online estimation of an excavator's rotational inertia by using recursive least square with forgetting. It is difficult to measure rotational inertia in real systems. Against this background, online estimation of rotational inertia is essential for improving safety and automation of construction equipment such as excavators because changes in inertial parameter impact dynamic characteristics. Regarding an excavator, rotational inertia for swing motion may change significantly according to working posture and digging conditions. Hence, rotational inertia estimation by predicting swing motion is critical for enhancing working safety and automation. Swing velocity and damping coefficient were used for rotational inertia estimation in this study. Updating rules are proposed for enhancing convergence performance by using the damping coefficient and forgetting factors. The proposed estimation algorithm uses three forgetting factors to estimate time-varying rotational inertia, damping coefficient, and torque with different variation rates. Rotational inertia in a typical working scenario was considered for reasonable performance evaluation. Three simulations were conducted by considering several digging conditions. Presented estimation results reveal the proposed estimation scheme is effective for estimating varying rotational inertia of the excavator.

• The Journal of the Acoustical Society of Korea
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• 제23권4E호
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• pp.103-107
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• 2004

In this Paper, we propose an algorithm called partitioned recursive least square (PRLS) that involves a procedure that partitions a large data matrix into small matrices, applies RLS scheme in each of the small sub matrices and assembles the whole size estimation vector by concatenation of the sub-vectors from RLS output of sub matrices. Thus, the algorithm should be less complex than the conventional RLS and maintain an almost compatible estimation performance.

• 조명전기설비학회논문지
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• 제17권3호
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• pp.103-109
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• 2003

전력계통의 자동화에 있어 측정되는 데이터의 정확성은 기본적으로 확립되어야 할 요건이다. 측정된 데이터는 통신 장애나 기기 자체의 오동작으로 인해 오차를 포함할 수 있으며, 이러한 오차는 상태추정에 의해 줄어들 수 있으나, 잘못 측정된 일부 값에 의해 상태추정의 전반적인 신뢰도가 저하될 수 있다. 본 논문에서는 가중최소 상태추정과 카이스퀘어 이론에 근거한 잘못 측정된 데이터의 검출 알고리즘이 제안되었으며, 이를 국내 154kV 변전소에 적용하였다. C 언어와 비쥬얼 베이직을 사용하여 GUI 환경의 시뮬레이터를 개발하였으며, 다른 운용 시스템과의 연계를 고려하여 TCP/IP 프로토콜을 탑재하였다.

• Journal of the Korean Data and Information Science Society
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• 제11권1호
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• pp.1-18
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• 2000

본 논문에서는 가장 많이 사용되는 시계열 모형중의 하나인 자기회귀모형에서 모수를 추정하는 방법으로 최소 절대 편차 추정법(least absolute deviation estimation)을 포함한 로버스트한 추정방법 (robust estimation)의 사용을 제안하고 모의 실험을 통하여 이러한 방법들을 기존의 최소 제곱 추정 방법과 예측의 관점에서 비교 검토하여 시계열 자료분석에서의 로버스트한 모수 추정 방법의 유효성을 확인해 보고자 한다.

• 한국소음진동공학회논문집
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• 제13권4호
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• pp.239-246
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• 2003

Application of the filtered-x Least Mean Square(LMS) adaptive filter to active noise control requires to estimate the transfer characteristics between the output and the error signal of the adaptive controller. In this paper, we derive the filtered-x adaptive noise control algorithm and analyze its convergence behavior when the acoustic noise consists of multiple sinusoids. The results of the convergence analysis of the filtered-x LMS algorithm indicate that the effects of the parameter estimation inaccuracy on the convergence behavior of the algorithm are characterized by two distinct components Phase estimation error and estimated gain. In particular, the convergence is shown to be strongly affected by the accuracy of the phase response estimate. Simulation results are presented to support the theoretical convergence analysis.

• 제어로봇시스템학회논문지
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• 제13권7호
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• pp.683-687
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• 2007

In last decades, several linearization methods for the AOA measurements have been proposed, for example, Gauss-Newton method and Closed-Form solution. Gauss-Newton method can achieve high accuracy, but the convergence of the iterative process is not always ensured if the initial guess is not accurate enough. Closed-Form solution provides a non-iterative solution and it is less computational. It does not suffer from convergence problem, but estimation error is somewhat larger. This paper proposes a Self-Tuning Weighted Least Square AOA algorithm that is a modified version of the conventional Closed-Form solution. In order to estimate the error covariance matrix as a weight, a two-step estimation technique is used. Simulation results show that the proposed method has smaller positioning error compared to the existing methods.

• International Journal of Aerospace System Engineering
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• 제7권1호
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• pp.21-27
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• 2020

Quasi steady stall is a phenomenon to characterize the aerodynamic behavior of aircraft at high angle of attack region. Generally, it is exercised from a steady state level flight to stall and its recovery to the initial flight in a calm weather. For a theoretical study, such maneuver is demonstrated in the form of aerodynamic model which consists of aircraft's stability and control derivatives. The current research paper is focused on the appropriate selection of aerodynamic model for the maneuver and estimation of the unknown model coefficients using least-square method. The statistical accuracy of the estimated parameters is presented in terms of standard deviations. Finally, the validation has been presented by comparing the measured data to the simulated data from different models.