• 한국인터넷방송통신학회논문지
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• 제18권6호
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• pp.113-119
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• 2018

본 논문은 NM-MMA (Novel Mixed-Multi Modulus Algorithm) 알고리즘에서 고정 modulus 대신 adaptive modulus를 이용한 적응 등화 성능을 개선시킨 AM-NM-MMA (Adaptive Modulus-NM-MMA)에 관한 것이다. NM-MMA는 MMA의 정상 상태에서 적은 잔여량을 얻는 대신 수렴 속도가 느리며, SE-MMA는 수렴 속도가 빠르지만 잔여량이 증대되는 성능을 절충시키기 위해 등장하였다. 그러나 고정 modulus를 이용하므로 완전 등화 상태에서도 잔여량이 0이 되지 않아 등화 성능이 열화되므로 이를 개선하기 위하여 논문에서는 adaptive modulus를 적용하였으며, 이의 개선된 성능을 시뮬레이션을 통해 확인하였다. 이를 위하여 등화 성능 지수로 등화기 출력 성상도, 잔류 isi, MD, MSE 및 SER 성능을 적용하였다. 컴퓨터 시뮬레이션의 결과 AM-NM-MMA는 NM-MMA보다 등화 출력 신호의 성상도, 잔류 isi, MD, MSE에서 수렴 속도와 잔여량에서는 우월하였으나, SER 성능에서는 열화됨을 확인하였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 추계종합학술대회 논문집(4)
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• pp.57-60
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• 2000

This paper presents a new adaptive fast motion estimation algorithm along with its architecture. The conventional algorithm such as full - search algorithm, three step algorithm have some disadvantages which are related to the amount of computation, the quality of image and the implementation of hardware, the proposed algorithm uses spatial correlation and a slope of motion vector in order to reduce the amount of computation and preserve good image quality, The proposed algorithm is better than the conventional Block Matching Algorithm(BMA) with regard to the amount of computation and image quality. Also, we propose an efficient at chitecture to implement the proposed algorithm. It is suitable for real time processing application.

• 한국공작기계학회논문집
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• 제10권2호
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• pp.38-47
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• 2001

In this paper, a new scheme of adaptive-neuro control system is presented to implement real-time control of robot manipulator using Digital Signal Processors. Digital signal processors, DSPs, are micro-processors that are particularly developed for fast numerical computations involving sums and products of measured variables, thus it can be programmed and executed through DSPs. In addition, DSPs are as fast in computation as most 32-bit micro-processors and yet at a fraction of therir prices. These features make DSPs a viable computational tool in digital implementation of sophisticated controllers. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust perfor-mance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method.The proposed adaptive-neuro control scheme is illustrated to be a efficient control scheme for the implementation of real-time control of robot system by the simulation and experi-ment.

• 한국전자파학회:학술대회논문집
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• 한국전자파학회 2001년도 종합학술발표회 논문집 Vol.11 No.1
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• pp.140-144
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• 2001

This paper describes to extend the MLFMA(Multi-Level Fast Multipole Algorithm) for three-dimensional capacitance computation in the case of conductors embedded in an arbitrary dielectric medium. The triangular meshes are used and refined in the area which has heavy charge density. This technique is applied to the capacitance extraction of three-dimensional structures with multiple dielectrics. The results show good convergence with the comparable accuracy, and this adaptive technique coupled with MLFMA is useful to reduce computing time and the number of elements without additional computational efforts in large three dimensional problems.

• 한국통신학회논문지
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• 제35권9C호
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• pp.743-747
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• 2010

본 논문은 빠른 연산(수렴)을 위한 적응 반복 하이브리드 영상 복원 알고리즘을 제안한다. 공간 영역의 국부제약 정보 설정을 위해 국부 영역의 분산, 평균, 국부 최대값을 이용하였다. 반복 기법을 이용하여 매 반복 해에서 얻어진 복원 영상으로부터 상기 제약 정보를 설정하고, 국부 완화도 결정을 위해 사용된다. 제안된 방식은 일반적인 RCLS(Regularized Constrained Least Squares) 방식에 비해 빠른 수렴속도와 더 좋은 성능을 얻을 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권5호
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• pp.2400-2413
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• 2019

Doubly-selective (DS) fading channel is often occurred in many orthogonal frequency division multiplexing (OFDM) communication systems, such as high-speed rail communication systems and underwater acoustic (UWA) wireless networks. It is challenging to provide an accurate and fast estimation over the doubly-selective channel, due to the strong Doppler shift. This paper addresses the doubly selective channel estimation problem based on complex exponential basis expansion model (CE-BEM) in OFDM systems from the perspective of distributed compressive sensing (DCS). We propose a novel DCS-based improved sparsity adaptive matching pursuit (DCS-IMSAMP) algorithm. The advantage of the proposed algorithm is that it can exploit the joint channel sparsity information using dynamic threshold, variable step size and tailoring mechanism. Simulation results show that the proposed algorithm achieves 5dB performance gain with faster operation speed, in comparison with traditional DCS-based sparsity adaptive matching pursuit (DCS-SAMP) algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.215-218
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• 1997

A dynamic back-propagation neural network is addressed for adaptive neural control system to approximate non-linear control system rather than static networks. It has the capability to represent the approximation of nonlinear system without mathematical analysis and to carry out the on-line learning algorithm for real time application. The simulated results show fast tracking capability and adaptive response by using dynamic back-propagation neurons.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.125.4-125
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• 2001

The problem of recongurable ight control is investigated, focusing on model reference adaptive control(MRAC) through imprecise fault diagnosis. The method integrates the fault detection and isolation(FDI) scheme with the model reference adaptive control, and can be implemented on-line and in real-time. The algorithm can cope with the fast varying parameters. The Simulation results demonstrate the ability of reconguration to maintain the stability and acceptable performance after a failure.

• 전기학회논문지
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• 제67권2호
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• pp.239-247
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• 2018

Adaptive Beamforming (ABF) algorithm, which is a typical jammer suppression algorithm, guarantees the performance on the assumption that the jamming characteristics of the TDS (Training Data Sample) are stationary, which are obtained immediately before and after transmitting the pulse signal. Therefore, effective jammer suppression can not be expected when the jamming characteristics are non-stationary. In this paper, we propose a new jammer suppression algorithm, of which power spectrum fluctuates fast. In this case, we assume that the location of the jammer station is fixed during the processing time. By applying the MPM (Matrix Pencil Method) to the jamming signal in TDS, we can estimate jammer parameters such as power and incident angle, of which the power will vary fast in time or range bins after TDS. Though we assume that the jammer station is fixed, the estimated jammer's incident angle has an error due to the noise, which degrades the performance of the jammer suppression as the jammer power increases fast. Therefore, the jammer's incident angle should be re-estimated at each range bin after TDS. By using the re-estimated jammer's incident angle, we can construct new covariance matrix under the non-stationary jamming environment. Then, the optimum weight for the jammer suppression is obtained by inversing matrix estimation method based on the matrix projection with the estimated jammer parameters as variables. To verify the performance of the proposed algorithm, the SINR (signal-to-interference plus noise ratio) loss of the proposed algorithm is compared with that of the conventional ABF algorithm.

• 한국정보과학회논문지:소프트웨어및응용
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• 제32권10호
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• pp.949-955
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• 2005

본 논문에서는 기존의 전영역 탐색 방식의 계산량을 현저히 줄임과 동시에 동일한 예측 화질을 얻기 위해, 기준 블록의 복잡도 순서와 정방형 서브블럭을 가지고 복잡한 영역 세분화를 통한 고속 블록 매칭(block matching) 알고리즘을 제안하였다. 매칭 에러가 기준 블록 기울기 크기에 비례한다는 것을 이용하여 종래의 순차적인 매칭 스캔(matching scan) 과 행/열 기반의 적응 매칭 스캔 대신, 복잡도에 기초한 정방형 서브 블록(sub-block) 적응 매칭 스캔을 가지고 불필요한 계산을 효율적으로 줄였다. 제안된 알고리즘은 예측 화질의 저하 없이 기존의 PDE(partial distortion elimination) 알고리즘을 이용한 전영역 탐색 방법에 비해 $30\%$의 계산량을 줄였으며, MPEG-2 및 MPEG-4 AVC를 이용하는 비디오 압축 응용분야에 유용하게 사용될 수 있을 것이다.