• 자원ㆍ환경경제연구
• /
• 제10권4호
• /
• pp.515-545
• /
• 2001

This paper introduces the least absolute deviations estimation of the contingent valuation model, which corresponds to the semi-parametric estimation of discrete choice models by Manski (1975, 1985) and Lee (1992). The least absolute deviations estimation is more robust to mis-specified distributional assumptions in the estimation of the contingent valuation model, compared to the maximum likelihood estimation. The full identification and strong consistency of the estimation are proved and its application to different formats of contingent valuation survey data is discussed. Simulation studies are designed to evaluate its operational characteristics including computational strategies, small sample properties and the efficiency gain of a follow-up question. The bias and efficiency of least absolute deviations and maximum likelihood estimation are compared in the presence of heteroskedasticity.

• 전자공학회논문지
• /
• 제50권5호
• /
• pp.281-286
• /
• 2013

본 논문에서는 에지 검출을 이용한 잡음 예측 방법을 제안하였다. 이 방법은 필터 기반으로 한 잡음 예측 방법이다. 에지 검출은 잡음 예측에 영향을 미치는 구조나 세밀한 정보들을 제거하기 위함이다. 에지 검출을 하기 위하여, 영상의 세밀함에 안정적인 수정한 래셔널 필터를 사용하였다. 제안한 잡음 예측 방법은 다양한 형태의 영상들의 잡음 예측에 더욱 효율적으로 적용되며 기존의 필터 기반으로 한 잡음 예측 방법들보다 좋은 결과를 얻는다.

• 한국음향학회지
• /
• 제39권1호
• /
• pp.32-37
• /
• 2020

본 논문은 l₁놈-Recursive Least Squares(RLS)에 수치 계산상 견실화를 더한 새로운 알고리즘을 제안한다. Eksioglu와 Tanc는 희소성 음향 채널 추정을 위해서 l₁놈-RLS 알고리즘을 구현하였다. 그러나 이 알고리즘의 근간인 RLS 계산법 역행렬 계산에서 수치 계산상의 불안정성을 지니고 있다. 본 논문에서는 이런 불안정성을 낮추는 새로운 알고리즘을 제안한다. 그리고 제안한 방법을 사용했을 때 수치적 불안정성에 대한 성능이 개선되었음을 보인다.

• 한국통신학회논문지
• /
• 제38C권4호
• /
• pp.365-370
• /
• 2013

본 논문에서는 비정규 잡음에 강인한 직교 주파수 분할 다중화 (orthogonal frequency division multiplexing: OFDM) 블라인드 주파수 옵셋 추정기들을 제안한다. 먼저 복소 등방성 코시 과정으로 모델링 된 비정규 잡음 환경에서 최대 우도 (maximum likelihood: ML) 추정기를 제안한다. 또한, ML 기반의 보다 간단한 추정기를 제안한다. 모의실험을 통해 제안한 추정기들이 비정규 잡음에 강인하며 기존 추정기보다 우수한 주파수 옵셋 추정 성능을 가짐을 보인다.

• 제어로봇시스템학회논문지
• /
• 제22권5호
• /
• pp.346-352
• /
• 2016

This paper proposes an adaptive robust control method for an acrobot system in the presence of input disturbance. The acrobot system is a typical example of the underactuated system with complex nonlinearity and strong dynamic coupling. Also, disturbance can cause limit cycle phenomenon which appears in the acrobot system around the desired unstable equilibrium point. To minimize the effect of the disturbance, we apply a fuzzy disturbance estimation method for the swing-up and balancing control of the acrobot system. In this paper, both disturbance observer and controller for the acrobot system are designed and verified through mathematical proof and simulations.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1993년도 하계학술대회 논문집 B
• /
• pp.784-786
• /
• 1993

Recently, in the industrial applications, the sensorless system is developed, but the sensorless system is required to have robustness for the measurement noise and disturbance. In this paper, for the sensorless system, the method of designing a robust sliding mode observer taking account of the ability of disturbance and noise attenuation is presented. Also, the strategy for the estimation of rotor flux using the sliding mode observer, which is robust to the measurement noise, is described. Robustness are achieved by assigning the pole of the the system during the sliding motion in such a way as to minimize the effects of the disturbances on the rotor flux estimation error. Finally, using worst case desist and LQC(least square error design), the sliding mode absolver is verified by computer simulations.

• Communications for Statistical Applications and Methods
• /
• 제27권6호
• /
• pp.701-714
• /
• 2020

Quantitative high throughput screening (qHTS) assays are used to assess toxicity for many chemicals in a short period by collectively analyzing them at several concentrations. Data are routinely analyzed using nonlinear regression models; however, we propose a new method to analyze qHTS data using a nonlinear mixed effects model. qHTS data are generated by repeating the same experiment several times for each chemical; therefor, they can be viewed as if they are repeated measures data and hence analyzed using a nonlinear mixed effects model which accounts for both intra- and inter-individual variabilities. Furthermore, we apply a one-step approach incorporating robust estimation methods to estimate fixed effect parameters and the variance-covariance structure since outliers or influential observations are not uncommon in qHTS data. The toxicity of chemicals from a qHTS assay is classified based on the significance of a parameter related to the efficacy of the chemicals using the proposed method. We evaluate the performance of the proposed method in terms of power and false discovery rate using simulation studies comparing with one existing method. The proposed method is illustrated using a dataset obtained from the National Toxicology Program.

• 한국지능시스템학회:학술대회논문집
• /
• 한국지능시스템학회 2007년도 추계학술대회 학술발표 논문집
• /
• pp.341-344
• /
• 2007

This paper proposes an alternative robust adaptive high-gain fuzzy observer design scheme and its application to synchronization of chaotic systems. The structure of the proposed observer is represented by Takagi-Sugeno fuzzy model and has the integrator of the estimation error. This improves the performance of high-gain observer and makes the proposed observer robust against noisy measurements, uncertainties and parameter perturbations as well. Using Lyapunov stability theory, an adaptive law is derived and the stability of the proposed observer is analyzed. Some simulation result is given to present the validity of theoretical derivations and the performance of the proposed observer.

• 전기학회논문지
• /
• 제61권2호
• /
• pp.284-290
• /
• 2012

This paper addresses a new passive target tracking problem using the range differences measured by cooperative UAVs. In order to solve the range difference based passive target tracking problem within the framework of linear robust state estimation, the uncertain linear measurement model which contains the stochastic parameter uncertainty is derived by using the noisy range difference measurements. To cope with the performance degradation due to the stochastic parameter uncertainty, the recently developed non-conservative robust Kalman filtering technique [1] is applied. For the cruciform formation flying UAVs, the relationship between the target tracking performance and the measurement errors is quantitatively analyzed. The proposed filter has practical advantages over the classical nonlinear filters because, for its recursive linear structure, it can provide satisfactory convergence properties and is suitable for real-time multiple UAVs applications. Through the simulations, the usefulness of the proposed method is demonstrated.

• Communications for Statistical Applications and Methods
• /
• 제7권2호
• /
• pp.371-383
• /
• 2000

Lindsay (1994) and Basu et al (1997) show that another density-based distance called the negative exponential disparity (NED) is an excellent competitor to the Hellinger distance (HD) in generating an asymptotically fully efficient and robust estimator. Bhattacharya and Basu (1996) consider estimation of the locations of several normal populations when an order relation between them is known to be true. They empirically show that the robust HD based weighted likelihood estimators compare favorably with the M-estimators based on Huber's $\psi$ function, the Gastworth estimator, and the trimmed mean estimator. In this paper we investigate the performance of the weighted likelihood estimator based on the NED as a robust alternative relative to that based on the HD. The NED based estimator is found to be quite competitive in the settings considered by Bhattacharya and Basu.