• 대한전자공학회논문지
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• 제22권2호
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• pp.18-24
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• 1985

주파수 영역-적응 필터는 시간 영역-원응 필터에 비하여 필터 차수가 일정치 이상으로 높아졌을 경우에는 계산량에 있어서 유리하게 된다. 본 논문에서는 각파수 영역-적응 필터 알고리즘에 관하여 μ-FLMS 알고리즘이라는 하나의 새로운 형태를 재시하였으며, 이 알고리즘과 시간 영역-적응 필터 μ-FLMS 알고리즘의 특성을 비교하였다. 두 필터의 특성을 비교한 결과, 동일한 수검속도하에서 주파수 영역-적응 필터가 계산량에서 유리하였다.

• 대한전자공학회논문지
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• 제27권3호
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• pp.145-155
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• 1990

適應 循環 필터에서 시스템 傳達 函數의 極點이 單位圓 밖으로 나감으로써 시스템이 불안정해지는 것을 방지하기 위해 適應 補償器를 채용한 適應 循環 필터 알고리듬을 제안하였고 제안한 알고리듬이 超安定性을 만족한다는 것을 證明하였다. 제안한 알고리듬 適應 雜音 除去器에 응용하여 LS방법의 適應 循環 필터를 이용한 適應 雜音 除去器, 適應 非循環 필터를 이용한 適應 雜音 除去器와의 성능을 比較하여 제안한 알고리듬의 妥當性을 立證하였다.

• Journal of Communications and Networks
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• 제9권1호
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• pp.18-27
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• 2007

The conventional normalized least mean square (NLMS) algorithm is the most widely used for adaptive identification within a non-stationary input context. The convergence of the NLMS algorithm is independent of environmental changes. However, its steady state performance is impaired during input sequences with low dynamics. In this paper, we propose a new NLMS algorithm which is, in the steady state, insensitive to the time variations of the input dynamics. The square soot (SR)-NLMS algorithm is based on a normalization of the LMS adaptive filter input by the Euclidean norm of the tap-input. The tap-input power of the SR-NLMS adaptive filter is then equal to one even during sequences with low dynamics. Therefore, the amplification of the observation noise power by the tap-input power is cancelled in the misadjustment time evolution. The harmful effect of the low dynamics input sequences, on the steady state performance of the LMS adaptive filter are then reduced. In addition, the square root normalized input is more stationary than the base input. Therefore, the robustness of LMS adaptive filter with respect to the input non stationarity is enhanced. A performance analysis of the first- and the second-order statistic behavior of the proposed SR-NLMS adaptive filter is carried out. In particular, an analytical expression of the step size ensuring stability and mean convergence is derived. In addition, the results of an experimental study demonstrating the good performance of the SR-NLMS algorithm are given. A comparison of these results with those obtained from a standard NLMS algorithm, is performed. It is shown that, within a non-stationary input context, the SR-NLMS algorithm exhibits better performance than the NLMS algorithm.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 B
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• pp.689-692
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• 2003

In this paper, we propose an adaptive beamforming algorithm for array antenna. The proposed beamforming algorithm, based on Block LMS (Block - Least Mean Squares) algorithm, has a variable step size from coefficient update. This method shows some advantages that the convergence speed is fast and the calculation time can reduced using a block LMS algorithm from frequency domain. As the adaptive parameter approaches a stationary state, it could reduce the number of filter coefficient update with the help of various step size. In this paper we compared the efficiency of the proposed algorithm with a standard LMS algorithm which is a representative method of adaptive beamforming.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.57-60
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• 2003

We have proposed the adaptive noise reduction algorithm using the MDFT. The algorithm proposed use the linear prediction coefficients of the AR method based on Sign algorithm that is the modified LMS instead of the least mean square(LMS). The signals with a random noise tracking performance are examined through computer simulations and confirmed that the high speed adaptive noise reduction processing system is realized with rapid convergence.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 A
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• pp.341-344
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• 1993

This paper presents the general MRAC algorithm design, it's real time implementation and investigates the effect of purely deterministic disturbances to adaptive control algorithm. The design of adaptive control algorithm to reject the disturbances properly is also presented. In real time application, adaptive control algorithm is considered to investigate its performance by using DC motor. Disturbance rejection algorithm is investigated in simulation.

• 한국통신학회논문지
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• 제10권6호
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• pp.308-316
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• 1985

주파수 영역에서 블록 적응 필터(Block Adaptive Filter),의 새로운 구현 방법을 제시하였다. 블록 적응 필터링은 입력값을 Block 단위로 하였을 때 출력에서도 블록 단위 또는 유한한 값을 갖도록 하는 것이다. 본 논문에서는 Gordard 이론을 이용하여 Block Adaptive Filter의 고속 수렴 알고리즘을 전개하고 Saito의 알고리즘과 BLMS알고리즘의 수렴 결과와 비교하였다. 그 결과 본 논문에서 제시한 주파수 영역블럭 적응 필터의 알고리즘(FBAF)이 BLMS알고리즘의 수렴상태보다 빠르게 수렴하며 Satio의 알고리즘의 수렴 오차보다는 줄어들었다.

• 한국정보처리학회논문지
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• 제7권10호
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• pp.3155-3163
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• 2000

자동차 번호판 인식 시스템에서 가장 중요한 요소는 자동차 이미지 영역에서 번호판 영역을 추출, 추출된 영역에서 문자추출, 추출된 문자의 인식등의 과정이다. 본 논문은 자동차 번호판 인식과정에서 적응 알고리즘을 이용하여 보다 정확한 인식이 될 수 있도록 한다. 본 논문에서 사용하는 적응 알고리즘은 기존의 방식과는 달리 특정한 알고리즘을 이용하여 인식을 하지 않고 다양한 알고리즘을 이용한 인식 결과의 조합으로 최적의 해법을 찾는다. 번호판 인식을 위한 적응 알고리즘은 원형 정합 알고리즘, 벡터 알고리즘, 세선화 알고리즘 등이다. 적응 알고리즘을 이용한 실험 결과 자동차 이미지에 대해서 90% 이상 인식이 가능함을 확인할 수 있었다.

• Journal of Information Processing Systems
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• 제16권6호
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• pp.1479-1494
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• 2020

As an important part of image processing, image demosaicking has been widely researched. It is especially necessary to propose an efficient interpolation algorithm with good visual quality and performance. To improve the limitations of residual interpolation (RI), based on RI algorithm, minimalized-Laplacian RI (MLRI), and iterative RI (IRI), this paper focuses on adaptive RI (ARI) and proposes an improved ARI (IARI) algorithm which obtains more distinct R, G, and B colors in the images. The proposed scheme fully considers the brightness information and edge information of the image. Since the ARI algorithm is not completely adaptive, IARI algorithm executes ARI algorithm twice on R and B components according to the directional difference, which surely achieves an adaptive algorithm for all color components. Experimental results show that the improved method has better performance than other four existing methods both in subjective assessment and objective assessment, especially in the complex edge area and color brightness recovery.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 심포지엄 논문집 정보 및 제어부문
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• pp.56-58
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• 2004

In this paper, we propose an adaptive beamforming algorithm for array antenna. The proposed beamforming algorithm is based on EDS (Euclidean Direction Search) algorithm. Generally LMS algorithm has a much slower rate of convergence, but its low computational complexity and robustness make it a representative method of adaptive beamforming. Although the RLS algorithm is known for its fast convergence to the optimal Wiener solution, it still suffers from high computational complexity and poor performance. The proposed EDS algorithm has a rapid convergence better than LMS algorithm, and has a computational more simple complexity than RLS algorithm. In this paper we compared the efficiency of the EDS algorithm with a standard LMS algorithm.