• 대한전기학회논문지
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• 제38권11호
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• pp.905-912
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• 1989

An adaptive control scheme is presented for uncertain systems whose uncertainties are upper-bounded by a linear combination of unknown constants and known continuous functions. The state of the closed-loop system is proven to be ultimately bounded. The proposed method modifies the method of Corless and Leitmann in the following two respects. First, the linear region of the saturation function in controller is fixed. Second, the intergration from in parameter estimator is replaced by a low pass filter form. These modifications prevent performance degradation and destabilization of the control system more effectively. The norm of the system states can be made sufficiently small by an appropriate choice of design parameters in the control law. The applicability of the proposed scheme is demonstrated in the position control of a simple pendulum via simulation.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 1999년도 추계종합학술대회
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• pp.248-251
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• 1999

We extend the sue of the method of least square to develop a recursive algorithm for the design of adaptive transversal filters such that, given the least-square estimate of this vector of the filter at iteration n-1, we may compute the updated estimate of this vector at i(oration n upon the arrival of new data. The RLS algorithm may be viewed as a special case of the Kalman filter. Indeed this special relationship between the RLS algorithm and the Kalman filter is considered. We begin the development of the RLS algorithm by reviewing some basic relations that pertain to the method of least squares. Then, by exploiting a relation in matrix algebra known as the matrix inversion lemma, we develop the RLS algorithm. An important feature of the RLS algorithm is that it utilizes information contained in the input data, extending back to the instant of time when the algorithm is initiated. The resulting rate of convergence is therefore typically an order of magnitude faster than the simple LMS algorithm. This improvement in performance, however, Is achieved at the expensive of a large increase in computational complexity.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2019년도 제59차 동계학술대회논문집 27권1호
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• pp.83-86
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• 2019

Histogram equalization is extensively used for image contrast enhancement in various applications due to its effectiveness and its modest functions. In image research, image enhancement is one of the most significant and arduous technique. The image enhancement aim is to improve the visual appearance of an image. Different kinds of images such as satellite images, medical images, aerial images are affected from noise and poor contrast. So it is important to remove the noise and improve the contrast of the image. Therefore, for this purpose, we apply a median filter on MR image as the median filter remove the noise and preserve the edges effectively. After applying median filter on MR image we have used intensity transformation function on the filtered image to increase the contrast of the image. Than applied the histogram equalization (HE) technique on the filtered image. The simple histogram equalization technique over enhances the brightness of the image due to which the important information can be lost. Therefore, adaptive histogram equalization (AHE) and contrast limited histogram equalization (CLAHE) techniques are used to enhance the image without losing any information.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1854-1857
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• 1991

A numerically efficient modification of a variable step size LMS (Least Mean Squares) algorithm is proposed. This proposed algorithm is very simple in calculation and has a variable step size adjusted by the filter output error. Its additional computational burden with respect to the conventional LMS algorithm is only two multiplications, two substraction, an addition and some bit operations. In a simulation example, it is shown that the proposed algorithm has not only the faster convergence rate but also less misadjustments in the environment of highly nonstationary and correlated data.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 1998년도 추계종합학술대회
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• pp.574-577
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• 1998

In this paper, a new simple and efficient technique to improve the convergence speed of LMS algorithm is proposed in an interference-limited multi-path fading environment as encountered in indoor wireless communications. The convergence characteristics of the proposed algorithm, whose coefficients are multiply adapted in a symbol time period by recycling the received data, are analyzed to prove theoretically the improvement of convergence speed. The theoretical analysis shows that the data-recycling in technique can increase convergence speed by (B+1) times without increasing the computational complexity substantially where B is the number of recycled data. The results of the computer simulation demonstrate that the simulation results are in accordance with the theoretical analysis and the superiority of the filter algorithm.

• International journal of advanced smart convergence
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• 제1권1호
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• pp.6-13
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• 2012

An improved algorithm for image quality assessment is presented. First a simple model of human visual system, consisting of a nonlinear function and a 2-D filter, processes the input images. This filter has one user-defined parameter, whose value depends on the reference image. This way the algorithm can adapt to different scenarios. In the next step the average value of locally computed correlation coefficients between the two processed images is found. This criterion is closely related to the way in which human observer assesses image quality. Finally, image quality measure is computed as the average value of locally computed correlation coefficients, adjusted by the average correlation coefficient between the reference and error images. By this approach the proposed measure differentiates between the random and signal dependant distortions, which have different effects on human observer. Performance of the proposed quality measure is illustrated by examples involving images with different types of degradation.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -1
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• pp.46-49
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• 2000

An iterative deblocking algorithm for DCT-compressed images using two-dimensional FIR filters adapted for local directionality of each block, is proposed. First, we introduce a set of simple lowpass filters, which are adapted for edges of different angles. In conventional deblocking methods based on lowpass-filtering and convex projections, a single filter is applied to a whole image. In the proposed method, on the other hand, a suitable filter is chosen out of the directional filters designed previously in every subimage (typically $8{\times}8$ block). Experimental results indicate that adaptive filtering improves PSNR at each iteration.

• 한국게임학회 논문지
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• 제15권2호
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• pp.159-168
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• 2015

이 논문에서는 의료용 초음파 볼륨 데이터의 잡음을 효과적으로 제거하기 위한 방법을 제안한다. 초음파 영상은 잡음이 심하여 필터링이 필요하다. 기존의 2차원 필터링은 인접한 슬라이스 간 정보를 무시하고 기존의 3차원 필터링은 속도가 느리거나 잡음 제거 효과가 떨어지는 필터를 적용하였고 또한 초음파 데이터의 샘플링 특성을 고려치 않아 균등하게 필터링 하지 않았다. 이를 해결하기 위해 잡음제거에 효과적인 양방향 필터를 병렬로 빠르게 처리하고 필터 영역에 따라 윈도우 크기를 달리하는 기법을 제안한다. 공간 필터의 합산영역 테이블을 이용하여 병렬로 빠르게 필터링하고 윈도우 크기는 필터 영역에 따라 비례적으로 결정한다. 실험은 평균 필터와 양방향 필터, 양방향 적응 필터를 적용한 초음파 볼륨 렌더링 영상에서 잡음 제거와 원본 손실 정도를 비교한다. 이렇게 하여 양방향 필터링을 빠르게 수행하면서 기존 보다 균등하게 필터링하여 잡음을 효과적으로 정확하게 제거할 수 있다.

• 한국멀티미디어학회논문지
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• 제9권8호
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• pp.1000-1009
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• 2006

본 논문에서는 부화소 단위의 적응적인 선형 보간법을 제안한다. 보통의 선형 보간법에 화소 마다 매개변수가 도입되고 이 매개 변수를 최적으로 구하기 위해서 저역 필터와 MMSE (minimum mean square error) 방법을 이용한 일반적인 보간 구조를 제안한다. 또한 제안된 일반적인 적응 선형 보간 구조에서 복잡도를 최소화한 방법을 유도하여 간단한 닫힌 형태의 식으로 제시한다. 기존 방법인 보통의 선형 보간법, 3차 컨볼루션 보간법에 비교하여 주관적으로나 객관적으로 제안된 방법의 우수함을 실험 결과로 알 수 있을 뿐만 아니라 왜곡 거리 선형 보간법(warped distance linear interpolation), 이동 선형 보간법(shifted linear interpolation) 등의 최근 기술과 비교하여도 우수함을 실험결과는 보여준다.

• 융합신호처리학회논문지
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• 제12권2호
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• pp.128-132
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• 2011

LMS(Least mean square) 적응 알고리즘은 radar, sonar, 음성처리, 이동통신 분야 등에서 중요한 역할을 하고 있다. 이동통신 분야에서는 LMS 적응 알고리즘의 빠른 수렴속도가 더욱 중요하다. 하지만 LMS 알고리즘은 수렴속도가 느리고 일정치 않은 수렴을 하는 문제점을 가지고 있다. 이러한 문제점을 해결하기 위하여 다양한 가변 스텝 LMS 적응 알고리즘들이 최근에 많이 연구되어왔다. 연구된 많은 LMS 알고리즘들은 빠른 수렴속도를 얻기 위하여 복잡한 가변스텝방식을 사용하는데 이는 많은 계산량을 필요로 한다. 따라서 LMS 알고리즘의 최대 장점인 단순성과 강인성을 약화시킨다. 제안하는 결정함수 가변스텝 LMS 알고리즘은 스텝 값을 간단한 결정함수에 따라 결정하므로 단순성을 최대한 강화하면서 빠른 수렴속도를 얻도록 한다.