• 한국음향학회지
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• 제29권1호
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• pp.18-23
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• 2010

RLS (Recursive Least Squares) 알고리즘은 적응 알고리즘의 대표적인 알고리즘이다. 하지만, 기본적인 RLS 알고리즘은 빠르게 움직이는 신호와 같은 비정상 (non-stationary) 신호환경에서는 좋은 성능을 가질 수 없다는 단점이 있다. 이를 해결하기 위하여 가변 망각 인자를 가지는 RLS 알고리즘이 등장하였으나, 기존의 가변 망각 인자 RLS 알고리즘은 연산량이 너무 많다는 단점이 있다. 본 논문에서는 이를 해결하기 위하여, 상대적으로 적은 연산량으로 AFF-RLS 알고리즘과 비슷한 성능을 내는 RLS 알고리즘을 제안한다.

• Journal of Astronomy and Space Sciences
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• 제34권1호
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• pp.19-30
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• 2017

The optical wide-field patrol network (OWL-Net) is a Korean optical surveillance system that tracks and monitors domestic satellites. In this study, a batch least squares algorithm was developed for optical measurements and verified by Monte Carlo simulation and covariance analysis. Potential error sources of OWL-Net, such as noise, bias, and clock errors, were analyzed. There is a linear relation between the estimation accuracy and the noise level, and the accuracy significantly depends on the declination bias. In addition, the time-tagging error significantly degrades the observation accuracy, while the time-synchronization offset corresponds to the orbital motion. The Cartesian state vector and measurement bias were determined using the OWL-Net tracking data of the KOMPSAT-1 and Cryosat-2 satellites. The comparison with known orbital information based on two-line elements (TLE) and the consolidated prediction format (CPF) shows that the orbit determination accuracy is similar to that of TLE. Furthermore, the precision and accuracy of OWL-Net observation data were determined to be tens of arcsec and sub-degree level, respectively.

• Journal of the Korean Data and Information Science Society
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• 제21권5호
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• pp.831-839
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• 2010

최소제곱 서포트벡터기계는 비선형회귀분석과 분류에 널리 쓰이는 커널기법이다. 본 논문에서는 금융시계열자료의 평균 및 변동성을 추정하기 위하여 평균의 추정 방법으로는 가중최소제곱 서포트벡터기계, 변동성의 추정 방법으로는 최소제곱 서포트벡터기계를 사용하는 비선형 평균 일반화 이분산 자기회귀모형을 제안한다. 제안된 모형은 선형 일반화 이분산 자기회귀모형 및 선형 평균 일반화 이분산 자기회귀모형보다 더 나은 추정 능력을 가진다는 것을 실제자료의 추정을 통하여 보였다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1992년도 추계학술대회 논문집
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• pp.161-165
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• 1992

The important properties of industrial scale or weighing machine operated in production lines are quickness and precision. This paper presents an algorithm which meets the importance. The algorithm of Recursive Least Squares Regression is described for the weighing system simulated as a dynamic model of the second order. Using the model and the algorithm, model parameters and then the mass being weighed can be determined from the step input. The performance of the algorithm is illustrated in digital simulation. Discussions have been extended to the development of fast converging algorithm. It turns out that the algorithm shows several desirable features suitable for microcomputer assisted realtime signal processing.

• 한국통신학회논문지
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• 제37권4B호
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• pp.309-316
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• 2012

본 논문에서는 WPAN의 NLOS(Non Line of Sight)환경에서 최소자승법을 적용한 위치인식 보정 알고리즘을 제안하고, 성능을 분석하였다. 이동 중인 이동노드의 위치인식 정확도를 향상시키기 위해 먼저 일정한 속도로 이동 중인 이동노드의 거리 값들을 SDS-TWR(Symmetric Double-Sided Two-Way Ranging)로 측정 한 후 이들을 사용하여 삼각 측량법(Triangulation)으로 위치를 측정하고, 그다음 최소자승법을 적용하여 위치인식 값을 보정하였다. NLOS환경에서 실험한 결과, 삼변 측량법, 칼만필터 및 최소자승법을 적용한 경우의 위치인식 평균오차는 ${\pm}1m$, ${\pm}0.2m$, ${\pm}0.1m$로 측정됨을 확인하였다. 결론적으로 제안한 최소자승법을 적용한 위치인식 보정 알고리즘의 위치인식 정확도는 삼각측량법에 의한 위치인식 정확도 보다 평균 86.0%, 칼만필터에 의한 위치인식 정확도 보다 평균 16.0% 향상된 것이다.

• 제어로봇시스템학회논문지
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• 제11권7호
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• pp.627-632
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• 2005

RAIM techniques based on TLS have rarely been addressed because TLS requires a great number of computations. In this paper, the particular form of the observation matrix H, is exploited so as to develop a new TLS-based sequential algorithm to identify an errant satellite. The algorithm allows us to enjoy the advantages of TLS with less computational burden. The proposed algorithm is verified through a numerical simulation.

• International Journal of Control, Automation, and Systems
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• 제2권2호
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• pp.165-170
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• 2004

RAIM techniques based on TLS have rarely been addressed because TLS requires a great number of computations. In this paper, the particular form of the observation matrix H, is exploited so as to develop a new TLS-based sequential algorithm to identify an errant satellite. The algorithm allows us to enjoy the advantages of TLS with less computational burden. The proposed algorithm is verified through a numerical simulation.

• 약학회지
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• 제43권2호
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• pp.160-168
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• 1999

The purpose of this study was to determine pharmacokinetic parameters of vancomycin using peak and trough plasma level (PTL) and Bayesian analysis in 20 Korean normal volunteers, 16 gastric cancer and 12 lymphoma patients and also using the compartment model dependent (nonlinear least squares regression: NLSR) and compartment model independent (Lagrange) analysis in 10 ovarian cancer patients. Nonparametric expected maximum (NPEM) algorithm for calculation of the population pharmacokinetic parameters was used, and these parameters were applied for clinical pharmacokinetic parameters by Bayesian analysis. Vancomycin was administered as dose of 1.0 g every 12 hrs for 3 days by IV infusion over 60 minutes in normal volunteers, gastric cancer and lymphoma patients. Population pharmacokinetic parameters, K and Vd in gastric cancer and lymphoma patients using NPEM algorithm were $0.158{\pm}0.014{\;}hr^{-1},{\;}0.630{\pm}0.043{\;}L/kg{\;}and{\;}0.131{\pm}0.0261{\;}hr^{-1},{\;}0.631{\pm}0.089{\;}L/kg$ respectively. The K and Vd in gastric cancer and lymphoma patients using Bayesian analysis were $0.151{\pm}0.027,{\;}0.126{\pm}0.056{\;}hr^{-1}{\;}and{\;}0.62{\pm}0.105,{\;}0.63{\pm}0.095{\;}L/kg$. The K and Vd in ovarian cancer patient using the NLSR and Lagrange analysis were $0.109{\pm}0.008,{\;}0.126{\pm}0.012{\;}hr^{-1}{\;}and{\;} 0.76{\pm}0.08,{\;}0.69{\pm}0.19{\;}L/kg$, respectively. It is necessary for effective dosage regimen of vancomycin in cancer patients to use these population parameters.

• 전기학회논문지
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• 제58권12호
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• pp.2520-2528
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• 2009

In this paper, we proposed tracking detection methodology using information granulation-based fuzzy radial basis function neural networks (IG-FRBFNN). According to IEC 60112, tracking device is manufactured and utilized for experiment. We consider 12 features that can be used to decide whether tracking phenomenon happened or not. These features are considered by signal processing methods such as filtering, Fast Fourier Transform(FFT) and Wavelet. Such some effective features are used as the inputs of the IG-FRBFNN, the tracking phenomenon is confirmed by using the IG-FRBFNN. The learning of the premise and the consequent part of rules in the IG-FRBFNN is carried out by Fuzzy C-Means (FCM) clustering algorithm and weighted least squares method (WLSE), respectively. Also, Hierarchical Fair Competition-based Parallel Genetic Algorithm (HFC-PGA) is exploited to optimize the IG-FRBFNN. Effective features to be selected and the number of fuzzy rules, the order of polynomial of fuzzy rules, the fuzzification coefficient used in FCM are optimized by the HFC-PGA. Tracking inference engine is implemented by using the LabVIEW and loaded into embedded system. We show the superb performance and feasibility of the tracking detection system through some experiments.

• 한국전자파학회논문지
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• 제28권11호
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• pp.894-901
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• 2017

요동이 존재하는 환경에서 항법 장비 정확도의 한계 및 시스템 지연 오차 등으로 방위 위상 오차가 필연적으로 발생하는 항공기 탑재 SAR(Synthetic Aperture Radar)의 경우, 방위 위상 오차를 신호처리 알고리즘으로 추정하고 보상하는 자동 초점(Autofocus: AF) 기법 적용이 필수적이다. 본 논문에서는 수정된 가중치 최소 자승기법(Modified Weighted Least-Squares: MWLS)에 의한 자동 초점 알고리즘을 제안한다. 새로운 방식의 표적 선정 및 정렬과 방위 방향 반복 위상 추정 방식을 통해 기존 WLS보다 견고한 성능을 보이게 된다. 비행 시험을 통해 획득한 SAR 원시데이터에 제안한 방식을 적용하고 성능을 분석하여 제안한 방식의 유효함과 우수성을 입증하도록 한다.