• 제목/요약/키워드: Robust Estimation

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견실한$H_\infty$FIR 필터를 이용한 불확실성 기동표적의 추적 (Maneuvering Target Tracking in Uncertain Parameter Systems Using RoubustH_\inftyFIR Filters)

  • 유경상;김대우;권오규
    • 대한전기학회논문지:전력기술부문A
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    • 제48권3호
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    • pp.270-277
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    • 1999
  • This paper deals with the maneuver detection and target tracking problem in uncertain parameter systems using a robust{{{{ { H}_{ } }}}} FIR filter to improve the unacceptable tracking performance due to the parametr uncertainty. The tracking filter used in the current paper is based on the robust{{{{ { H}_{ } }}}} FIR filter proposed by Kwon et al. [1,2] to estimate the state signal in uncertain systems with parameter uncertainty, and the basic scheme of the proposed method is the input estimation approach. Tracking performance of the maneuver detection and target tracking method proposed is compared with other techniques, Bogler allgorithm [4] and FIR tracking filter [2], via some simulations to examplify the good tracking performance of the proposed method over other techniques.

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Panoramic Image Stitching using SURF

  • You, Meng;Lim, Jong-Seok;Kim, Wook-Hyun
    • 융합신호처리학회논문지
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    • 제12권1호
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    • pp.26-32
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    • 2011
  • This paper proposes a new method to process panoramic image stitching using SURF(Speeded Up Robust Features). Panoramic image stitching is considered a problem of the correspondence matching. In computer vision, it is difficult to find corresponding points in variable environment where a scale, rotation, view point and illumination are changed. However, SURF algorithm have been widely used to solve the problem of the correspondence matching because it is faster than SIFT(Scale Invariant Feature Transform). In this work, we also describe an efficient approach to decreasing computation time through the homography estimation using RANSAC(random sample consensus). RANSAC is a robust estimation procedure that uses a minimal set of randomly sampled correspondences to estimate image transformation parameters. Experimental results show that our method is robust to rotation, zoom, Gaussian noise and illumination change of the input images and computation time is greatly reduced.

고유구조 지정을 이용한 다중출력 시스템의 강인한 관측기 설계 (Robust Observer Design for Multi-Output Systems Using Eigenstructure Assignment)

  • 허건수;남준철
    • 대한기계학회논문집A
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    • 제28권11호
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    • pp.1621-1628
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    • 2004
  • This paper proposes a design methodology for the robust observer using the eigenstructure assignment in multi-output systems so that the observer is less sensitive to the ill-conditioning factors such as unknown initial estimation error, modeling error and measurement bias in transient and steady-state observer performance. The robustness of the observer can be achieved by selecting the desired eigenvector matrix to have a small condition number that guarantees the small upper bound of the estimation error. So the left singular vectors of the unitary matrix spanned by space of the achievable eigenvectors are selected as a desired eigenvectors. Also, this paper proposes how to select the desired eigenvector based on the measure of observability and designs the observer with small gain. An example of a spindle drive system is simulated to validate the robustness to the ill-conditioning factors in the observer performance.

Deep learning-based scalable and robust channel estimator for wireless cellular networks

  • Anseok Lee;Yongjin Kwon;Hanjun Park;Heesoo Lee
    • ETRI Journal
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    • 제44권6호
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    • pp.915-924
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    • 2022
  • In this paper, we present a two-stage scalable channel estimator (TSCE), a deep learning (DL)-based scalable, and robust channel estimator for wireless cellular networks, which is made up of two DL networks to efficiently support different resource allocation sizes and reference signal configurations. Both networks use the transformer, one of cutting-edge neural network architecture, as a backbone for accurate estimation. For computation-efficient global feature extractions, we propose using window and window averaging-based self-attentions. Our results show that TSCE learns wireless propagation channels correctly and outperforms both traditional estimators and baseline DL-based estimators. Additionally, scalability and robustness evaluations are performed, revealing that TSCE is more robust in various environments than the baseline DL-based estimators.

Some efficient ratio-type exponential estimators using the Robust regression's Huber M-estimation function

  • Vinay Kumar Yadav;Shakti Prasad
    • Communications for Statistical Applications and Methods
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    • 제31권3호
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    • pp.291-308
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    • 2024
  • The current article discusses ratio type exponential estimators for estimating the mean of a finite population in sample surveys. The estimators uses robust regression's Huber M-estimation function, and their bias as well as mean squared error expressions are derived. It was campared with Kadilar, Candan, and Cingi (Hacet J Math Stat, 36, 181-188, 2007) estimators. The circumstances under which the suggested estimators perform better than competing estimators are discussed. Five different population datasets with a well recognized outlier have been widely used in numerical and simulation-based research. These thorough studies seek to provide strong proof to back up our claims by carefully assessing and validating the theoretical results reported in our study. The estimators that have been proposed are intended to significantly improve both the efficiency and accuracy of estimating the mean of a finite population. As a result, the results that are obtained from statistical analyses will be more reliable and precise.

적응적 가중치 함수를 이용한 모션 벡터의 필터링 (Filtering Motion Vectors using an Adaptive Weight Function)

  • 장석우;김진욱;이근수;김계영
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제31권11호
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    • pp.1474-1482
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    • 2004
  • 본 논문에서는 적응적 가중치 함수를 이용하여 블록 단위의 모션 벡터를 필터링하는 방법을 제안한다. 제안하는 방법에서는 먼저 인접한 영상을 받아 들여 가변적 크기의 블록 정합 방법을 이용하여 모션 벡터를 추출한다. 그리고 추출된 모션 벡터를 강건 예측에 적용하여 아웃라이어(outlier)를 제거함으로써 강건 예측에서 사용하는 동작 모델에 근접한 모션 벡터만을 추출한다. 제안된 적응적 강건 예측은 연속적인 시그모이드 가중치 함수를 사용하여 정상 자료와 아웃라이어의 소속 정도를 보다 효과적으로 표현한다. 또한, 최소화 기법의 반복 단계에서 잔여에러가 감소함에 따라 점진적으로 시그모이드 가중치 함수를 조율함으로써 정상 자료와 아웃라이어를 보다 유연하게 분리한다. 실험에서는 카메라의 동작이 포함된 비디오 데이타를 입력 받아 성능을 비교 분석함으로써 제안한 방법의 우수함을 보인다.

Robust Features and Accurate Inliers Detection Framework: Application to Stereo Ego-motion Estimation

  • MIN, Haigen;ZHAO, Xiangmo;XU, Zhigang;ZHANG, Licheng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권1호
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    • pp.302-320
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    • 2017
  • In this paper, an innovative robust feature detection and matching strategy for visual odometry based on stereo image sequence is proposed. First, a sparse multiscale 2D local invariant feature detection and description algorithm AKAZE is adopted to extract the interest points. A robust feature matching strategy is introduced to match AKAZE descriptors. In order to remove the outliers which are mismatched features or on dynamic objects, an improved random sample consensus outlier rejection scheme is presented. Thus the proposed method can be applied to dynamic environment. Then, geometric constraints are incorporated into the motion estimation without time-consuming 3-dimensional scene reconstruction. Last, an iterated sigma point Kalman Filter is adopted to refine the motion results. The presented ego-motion scheme is applied to benchmark datasets and compared with state-of-the-art approaches with data captured on campus in a considerably cluttered environment, where the superiorities are proved.

시간-주파수 영역 반사파 시스템에서 가중강인최소자승 필터를 이용한 주파수 추정 (Frequency Estimation for Time-Frequency Domain Reflectometry using Weighted Robust Least Squares Filter)

  • 곽기석;나원상;두승호;최가형;윤태성;박진배;고재원
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2007년도 제38회 하계학술대회
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    • pp.1640-1641
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    • 2007
  • In this paper, an experiment of weighted robust least squares frequency estimation for the Gaussian envelope chirp signal which is used in the time-frequency domain reflectometry system was carried out. By incorporating the forgetting factor to the frequency estimator, the weighted robust least squares filter achieved good enough frequency estimation performance for the chirp signal and it can be adopted to implement not only low cost time-frequency domain reflectometry but also real-time time-frequency domain reflectometry implementation.

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불확실성을 고려한 디젤엔진의 견실한 이상검출 (Application of robust fault detection method for uncertain systms to diesel engine system)

  • 유경상;김대우;권오규
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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    • pp.1419-1422
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    • 1997
  • This paper deals with the Appliation of robust fault detection problem in uncertain linear systems, having both model mismatch and noise. A robust fault detection method presented by Kwon et al.(1994) for SISO uncertain systems. Here we experimented this method to the diesel engine systems described by difference ARMA models. The model mismatch includes here linearization error as well as undermodeling. Comparisons are made with alternative fault detection method which do not account noise. The new method is shown to have good performance.

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MRAS를 이용한 약계자 영역에서 유도 전동기의 속도 센서 없는 벡터 제어 (Speed Sensorless Vector Control of Induction Motor using MRAS in Field-Weakening region)

  • 박태식;김남정;유지윤;박귀태
    • 전력전자학회:학술대회논문집
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    • 전력전자학회 1996년도 창립기념 전력전자학술발표회 논문집
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    • pp.1-4
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    • 1996
  • The purpose of this treatise is to estimate speed of an induction motor and realize a robust speed control system with estimated speed in field-weakening region. A speed estimation is based on Model Reference Adaptive System(MRAS) technique and two flux estimator are designed to be robust against parameter variation. The MRAS-based overall control scheme has been implemented on 7.5kW Spindle induction motor control system. And it is verified that the proposed control scheme is very stable and robust in field-weakening region.

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