• 전기학회논문지
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• 제68권1호
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• pp.83-89
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• 2019

In this paper, beam forming using moving least squares method (MLSM) is studied. In the previous research, the least squares method (LSM), one of the data interpolation methods, was used to determine the desired beam pattern and obtain a beam pattern that minimizes the square of the error with the desired beam pattern. However, LSM has a disadvantage in that the beam pattern can not be formed to satisfy the exact steering angle of the desired beam pattern and the peak sidelobe level (PSLL) condition. To overcome this drawback, MLSM is used for beam forming. In order to verify, the proposed method is applied in beam forming of Bezier platform array antenna which is one of conformal array antenna platform.

• 대한기계학회논문집A
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• 제36권7호
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• pp.777-787
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• 2012

본 논문에서는 여러 가지 충격하에서 압저항 고충격 미소가속도계의 과도 출력전압의 계산시 발생하는 방대한 계산 시간 문제를 모드중첩법 및 최소자승법을 이용하여 압저항 미소가속도계의 실시간 출력전압 계산이 가능하도록 효율적인 출력전압 과도해석 방법을 제안한다. 우선 정적 압저항-구조 해석을 통하여 미소가속도계의 변위와 출력전압을 계산하고 출력전압을 특정 위치의 변위에 관한 2차 다항식으로 근사화하여 그 회귀계수를 최소자승법을 통하여 결정한다. 이후에 모드중첩법을 통하여 여러 방향의 고충격하에서 미소가속도계의 과도 변위응답을 계산하고, 이 변위응답을 변위로 표현되는 출력전압 근사식에 대입하여 과도 출력전압을 예측한다. 100,000 G 고충격파, 사인파, 계단파 및 사각파 등의 여러 가지 고충격 입력에 대한 압저항 미소가속도계의 수치예제를 통하여 제안한 방법의 정확성 및 효율성을 검증하였다.

• Journal of Information Processing Systems
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• 제19권4호
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• pp.527-539
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• 2023

In the positioning algorithm of two-dimensional planar sensor array, the estimation error of time difference-ofarrival (TDOA) algorithm is difficult to avoid. Thus, how to achieve accurate positioning is a key problem of the positioning technology based on planar array. In this paper, a method of sensor reliability discrimination is proposed, which is the foundation for selecting positioning sensors with small error and excellent performance, simplifying algorithm, and improving positioning accuracy. Then, a positioning model is established. The estimation characteristics of the least square method are fully utilized to calculate and fuse the positioning results, and the non-uniform weighting method is used to correct the weighting factors. It effectively handles the decreased positioning accuracy due to measurement errors, and ensures that the algorithm performance is improved significantly. Finally, the characteristics of the improved algorithm are compared with those of other algorithms. The experiment data demonstrate that the algorithm is better than the standard least square method and can improve the positioning accuracy effectively, which is suitable for vibration detection with large noise interference.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 추계학술대회논문집
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• pp.886-890
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• 2007

Machine fault prognosis techniques have been considered profoundly in the recent time due to their profit for reducing unexpected faults or unscheduled maintenance. With those techniques, the working conditions of components, the trending of fault propagation, and the time-to-failure are forecasted precisely before they reach the failure thresholds. In this work, we propose an approach of Least Square Regression Tree (LSRT), which is an extension of the Classification and Regression Tree (CART), in association with one-step-ahead prediction of time-series forecasting technique to predict the future conditions of machines. In this technique, the number of available observations is firstly determined by using Cao's method and LSRT is employed as prognosis system in the next step. The proposed approach is evaluated by real data of low methane compressor. Furthermore, the comparison between the predicted results of CART and LSRT are carried out to prove the accuracy. The predicted results show that LSRT offers a potential for machine condition prognosis.

• 한국군사과학기술학회지
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• 제12권1호
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• pp.114-122
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• 2009

An adaptive Kalman filter is designed as a post-navigation filter to improve the accuracy of GPS receiver's navigation performance in high dynamic environments. Not only the adaptive Kalman filter reduces the large noise error of navigation data which is obtained by least square method, but also the filter is not degraded as normal Kalman filter in high acceleration movements because the system noise is estimated. Also an initialization structure of the filter is desisted in consideration for irregular output condition of navigation data by least squared method such as reacquisition status in GPS receiver. The filter performance is verified by GPS simulator which has the simulation capability of high velocity and acceleration. Finally, a vehicle test including DGPS is executed to conform the real improvement of that filter performance. This filter can be applied to various data measurement systems to improve accuracy in high dynamic conditions besides GPS receiver.

• Journal of Biosystems Engineering
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• 제33권6호
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• pp.438-445
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• 2008

The purpose of this study was to develop a measurement model based on PLS (Partial least square) method for blood pressures. Measurement system for blood pressure signals consisted of pressure sensor, va interface and embedded module. A mercury sphygmomanometer was connected with the measurement system through 3-way stopcock and used as reference of blood pressures. The blood pressure signals of 20 subjects were measured and tests were repeated 5 times per each subject. Total of 100 data were divided into a calibration set and a prediction set. The PLS models were developed to determine the systolic and the diastolic blood pressures. The PLS models were evaluated by the standard methods of the British Hypertension Society (BHS) protocol and the American Association for the Advancement of Medical Instrumentation (AAMI). The results of the PLS models were compared with those of MAA (maximum amplitude algorithm). The measured blood pressures with PLS method were highly correlated to those with a mercury sphygmomanometer in the systolic ($R^2=0.85$) and the diastolic blood pressure ($R^2=0.84$). The results showed that the PLS models were the effective tools for blood pressure measurements with high accuracy, and satisfied the standards of the BHS protocol and the AAMI.

• 대한전기학회논문지:시스템및제어부문D
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• 제51권5호
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• pp.212-219
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• 2002

In this paper, the epipolar geometry, genera17y used as a pin-hole camera model, is newly adapted to our proposed method that enables the affine reconstruction of the 3D object from two projected views. The proposed method models the projective projection of inherent X-ray imaging system, obviates the need to attach artifirially constructed material on the body, and requires none of the prior-knowledge regarding to intrinsic and extrinsic parameters of two X-ray imaging systems. The optimum numerical solution is obtained by applying the least mean square estimator to corresponding points on two projected X-ray planes. The performance of this proposed method is Quantitatively analyzed using computer synthesized model of Cochlear implantation electrodes. In simulated experiments, the propnsed method is insensitive to the added random noise, the scaling factor change, the center point change, and rotational angular change between two projection planes, as well as enables the stable 3D reconstruction in least square sense even in worst testing cases.

• Journal of Mechanical Science and Technology
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• 제17권10호
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• pp.1552-1562
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• 2003

In this paper, we propose a new PIV methodology for obtaining a velocity field from a sequence of multiple image data based on a least-square principle (also known as MQD; minimum quadratic difference) for the grey level difference between two neighboring frames of image data. We investigated both the accuracy of the result and the time consumption in the computation. It turns out that the proposed method is not only accurate but fast compared with the conventional correlation PIV techniques. Our method is applied to the spin-up flows and the results show that the method can be a good substitution for the conventional algorithms employed in the existing commercial codes.

• 한국정보전자통신기술학회논문지
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• 제7권3호
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• pp.132-136
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• 2014

본 논문에서는 주어진 데이터 전처리를 통한 새로운 형태의 TSK기반 퍼지 추론 시스템을 제안한다. 제안된 모델은 주어진 데이터의 효율적인 처리를 위해 클러스터링 기법인 Fuzzy C-Means 클러스터링 방법을 이용하였다. 제안된 새로운 형태의 퍼지추론 시스템의 전반부는 FCM 을 통하여 정규화된 멤버쉽 함수와 클러스터 수를 결정하기 때문에, 멤버쉽함수의 형태 및 개수를 정의할 필요가 없어, 모델의 구조 또한 간단한 형태를 이룬다. 본 논문에서 사용된 후반부는 4가지 형태로-간략추론, 1차선형추론, 2차선형추론, 변형된 2차선형추론-가 있으며, 이는 효율적인 후반부구조를 찾는데 주도적인 역할을 한다. 또한 제안된 모델의 후반부 파라미터 계수는 Weighted Least Squares Estimation(WLSE)을 사용하여 동정하며, Least Squares Estimation(LSE)를 적용한 모델의 성능과 비교한다. 마지막으로, Boston housing 데이터를 사용하여 제안된 모델의 성능을 평가하였다.

• 한국음향학회지
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• 제22권3호
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• pp.224-232
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• 2003

본 논문에서는 능동 소나의 구성 방법 및 관측 오차에 따른 위치 추정 성능에 대해서 다룬다. 능동 소나는 구성 방법에 따라서 크게 단상태 (Monostatic) 소나, 양상태 (Bistatic) 소나, 다중상태 (Multistatic) 소나로 분류될 수 있으며, 각각의 오차에 대한 특성이 서로 다르다 각 수신기가 거리 정보와 방위 정보를 얻을 수 있다는 가정하에 단상태, 양상태 소나와 다중상태 소나의 위치 추정 성능에 대해 비교해 보고 기존의 정보 융합 방법인 최소 자승법 (LS: Least square)에 가중치를 주는 가중치 최소 지승법 (WLS: Weighted least square)을 제안하였다. 또한, 제안된 방법을 이용하여 수신기의 수, 송수신기간 거리와 위치 추정 성능과의 연관성에 대하여 알아보고 효과적인 다중상태 소나 배치에 대한 연구를 수행하였다. 모의 실험결과 다중상태 소나의 위치 추정 제곱근 오차평균이 단상태 소나에 비해 약 35.98%, 양상태 소나에 비해 약 37.45% 우수한 것을 볼 수 있었으며 WLS가 LS에 비해 평균 7.4% 우수한 성능을 나타내었고 각 센서에 입력되는 정보의 분산 차가 클수록 성능 향상율이 증가하는 경향을 보였다.