• 한국통신학회논문지
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• 제33권4C호
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• pp.305-311
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• 2008

본 논문에서는 실시간 자동차 환경에서 VSSNLMS(variable step size normalized least mean square)를 이용하여 적응 잡음 제거 알고리즘을 제안한다. 기본적인 ANC(adaptive noise canceller)알고리즘인 LMS알고리즘은 알고리즘의 간단성 때문에 가장 많이 사용되고 있다. 그러나 LMS알고리즘은 수렴율과 실시간 환경에서의 정확성 사이에서 문제를 가지고 있다. 이러한 문제를 풀기 위해, 비정장성 환경에서 잡음제거를 위해 VSSLMS알고리즘이 사용된다. 본 논문에서 실시간 데이터 입력 시스템을 사용하여 컴퓨터 시뮬레이션 함으로써, VSSLMS알고리즘이 LMS알고리즘에 비해 수렴율과 정확성 이 모두에 더 효율적이라는 것을 입증한다.

• 한국통신학회논문지
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• 제34권5C호
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• pp.521-526
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• 2009

In this paper, a complex-valued recursive least squares escalator filter algorithm with reduced computational complexity for complex-valued signal processing applications is presented. The local tap weight of RLS-ESC algorithm is updated by incrementing its old value by an amount equal to the local estimation error times the local gain scalar, and for the gain scalar, the local input autocorrelation is calculated at the previous time. By deriving a new gain scalar that can be calculated by using the current local input autocorrelation, reduced computational complexity is accomplished. Compared with the computational complexity of the complex-valued version of RLS-ESC algorithm, the computational complexity of the proposed method can be reduced by 50% without performance degradation. The reduced computational complexity of the proposed algorithm is even less than that of the LMS-ESC. Simulation results for complex channel equalization in 64QAM modulation schemes demonstrate that the proposed algorithm has superior convergence and constellation performance.

• 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.

• 정보저장시스템학회논문집
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• 제9권1호
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• pp.5-9
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• 2013

Page-oriented holographic data storage (HDS) is very sensitive to the disturbances. However, vibration effect by disc imbalance can be ignored because data pages are recorded and retrieved with stop-go rotation. Therefore, just estimating de-track due to eccentricity of disc is enough to construct stable track servo system. In this paper, propose the spacing of track servo patterns optimization method using Least Mean Square (LMS) estimation algorithm. Through the patterns spacing optimization, storage density maximize can be achieved.

• 전자공학회논문지S
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• 제36S권7호
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• pp.81-89
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• 1999

통신에 의한 전송 영상은 잡음이나 번짐 또는 일그러짐 등을 항상 포함한다. 본 논문에서는 적응형 일반스텍 최적화 필터(OAGSF: optimal adaptive generalized stack filter)라는 영상복원 공간 필터를 제안하였는데, 이는 영상의 복원에서 잡음 제거율과 외곽선 정보의 보존률의 증가을 위해 신경회로맘의 역전파 학습 알고리즘의 가중치 학습 알고리즘을 기반으로 적응형 일반스택 필터(AGSF)를 최적화 시킨 것이다. 적응형 일반스택 필터는 일반스택 필터(GSF: generalized stack filter)와 적응형 다단계 메디안 필터(AMMF; adaptive multistage median filter)로 구분하고, 일반스텍 필터는 스택 필너치 기능을 보완한것이고, 적응형 다단계 메디안 필터는 메디안 필터의 외곽선 정보 보존률을 높인 것이다. 신경회로망의 역전파 학습 알고리즘에 대하여 두가지 가중치 학습 알고리즘인 최소평균절대 (LMA:Least Mean Absolute) 알고리즘과 최소평균자승(LMS: Least Mean Square) 알고리즘을 이용하여 적응형 일반스택 필터를 최적화하였다. 본 논문에서 제시한 신경회로망을 이용한 영상복원 공간필터에 대해 실험결과를 통해 제시하였다.

• 한국공작기계학회논문집
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• 제12권2호
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• pp.79-85
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• 2003

An algorithm for fitting with Least Square is a traditional and an effective method in processing with experimental data. Due to the lack of definite representation, it is difficult to fit measured data with free curves or surfaces. B-Spline is usefully utilized to express free curves and surfaces with a few parameters. This paper presents the combination of these two techniques to process the point data measured from CMM and other similar instruments. This research shows tests and comparison of the simulation results from two techniques.

• 한국생산제조학회지
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• 제22권3호
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• pp.394-401
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• 2013

A new Rockwell hardness (HRC) model using a volumetric parameter by a least square and fractal interpolation method is suggested. The results are also investigated in comparison to real measured hardness data. For this purpose, the measurement of an indented volume is performed using a confocal laser scanning microscope (CLSM), and the captured height encoded image (HEI) is used as an original surface for the calculation of the indented volume. After configuring the surface, the constructed volume is calculated and used as an independent variable for HRC hardness modeling. The hardness model is established using an experimental modeling technique involving a least square algorithm and fractal interpolating model, and this suggested model can be used to reliably predict the Rockwell hardness. These techniques can also be applied to the modeling of the Brinnell and Vickers hardnesses using a volumetric variable.

• 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.

• 한국인터넷방송통신학회논문지
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• 제9권2호
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• pp.111-116
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• 2009

본 논문은 차세대 고속무선 DTV(Digital Television)를 위한 터보복호기반의 위상 옵셋 추정 기법이 대해 연구하였다. 위상 추정기법은 터보 복호기 외부에 추정기를 두어 다음 상태의 위상을 추정하기 위해 LMS (Least Mean Square) 방식을 사용하였다. 기존의 LMS 방식은 구현이 간결하지만 고정의 스텝 사이즈를 가지고 있으므로 시간에 따라 변화하는 다중 경로 환경에서는 채널 추정이 힘들며 트래킹 능력이 떨어지는 단점을 가지고 있다. 따라서 본 논문에서는 고정 스텝 사이즈가 아닌 채널의 상태에 따라 스텝 사이즈를 변화 시키는 가변 스텝사이즈를 갖는 LMS 방식을 제안한다. 모의실험은 임의의 위상 옵셋에 대하여 수행되었으며, 제안한 방식이 기존의 방식에 비해 개선된 성능을 보임을 알 수 있었다.

• 통합자연과학논문집
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• 제15권3호
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• pp.99-110
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• 2022

Solar photovoltaic (PV) system shows a non-linear current (I) -voltage (V) characteristics, which depends on the surrounding environment factors, such as irradiance, temperature, and the wind. Solar PV system, with current (I) - voltage (V) and power (P) - Voltage (V) characteristics, specifies a unique operating point at where the possible maximum power point (MPP) is delivered. At the MPP, the PV array operates at maximum power efficiency. In order to continuously harvest maximum power at any point of time from solar PV modules, a good MPPT algorithms need to be employed. Currently, due to its simplicity and easy implementation, Perturb and Observe (P&O) algorithms are the most commonly used MPPT control method in the PV systems but it has a drawback at suddenly varying environment situations, due to constant step size. In this paper, to overcome the difficulties of the fast changing environment and suddenly changing the power of PV array due to constant step size in the P&O algorithm, least mean Square (LMS) methods is proposed together with P&O MPPT algorithm which is superior to traditional P&O MPPT. PV output power is predicted using LMS method to improve the tracking speed and deduce the possibility of misjudgment of increasing and decreasing the PV output. Simulation results shows that the proposed MPPT technique can track the MPP accurately as well as its dynamic response is very fast in response to the change of environmental parameters in comparison with the conventional P&O MPPT algorithm, and improves system performance.