• 한국음향학회지
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• 제6권2호
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• pp.15-18
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• 1987

승산을 요하지 않는 적응 디지탈 필터링 알고리즘이 논의되었다. 제안된 알고리즘은 델타 변조 디지탈 필터를 사용하였으며 승산없이 적응 디지탈 필터를 실현하기 위하여 필터계수는 SIGN 알고리즘으로 새로이 재조정된다. 결과적으로, 제안된 알고리즘은 단순히 UP/DOWN 계수동작으로 실현될 수 있음을 보였다. 제안된 적응 디지탈 필터링 알고리즘과 다른 알고리즘을 시스템 Identification문제에 적용하여 수렴특성을 조사하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.970-973
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• 1996

In this paper, Modified GPS Kalman filter algorithms which allow user to estimate its position when the number of visible GPS satellites becomes less than four are presented. They are derived using the previous estimation of altitude and clock bias. Thus, it is possible to estimate 3-dimensional user position even when only two GPS satellites are visible. The algorithms are ideally suited to car navigation in urban areas where lack of GPS visibility is the major problem because of the frequent blockage of the GPS signals by tall buildings and other structures. Simulation results in this paper show that modified GPS Kalman filter provide better performances than a general GPS Kalman filter or any other instantaneous GPS solution algorithm, especially in the case which the number of visible GPS satellites becomes less than four.

• 한국멀티미디어학회논문지
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• 제3권2호
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• pp.184-191
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• 2000

본 논문에서는 선행 연구한 $\Delta$-형 필터를 토대로 하여 이의 특성을 종합적으로 비교 분석하였다. 먼저 화면 확장을 위한 $\Delta$-형 필터의 알고리즘에 대해서 논하였고, 이의 특성, 즉 $\Delta$-형 필터의 에지보존특성과 알고리즘에 근거하여 기존 방식들과의 연산량을 비교하였다. 그리고 제안한 방식과 기존의 알고리즘을 PSNR을 도입하여 정량적으로 비교하였으며, Synopsys VHDL에 의한 구현을 통하여 하드웨어의 복잡성을 비교하였다. 마지막으로 $\Delta$-형 필터의 특징과 trade off에 대해서 논하였다.

• 전자공학회논문지B
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• 제33B권12호
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• pp.62-70
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• 1996

Image restoration is the process which estimates the original image form the blurred image observed by the non-ideal imaging system with additivenoise. According to the regularized approach, the resotred image can be obtained by iterative methods or the constrained least square error(CLS) filter. Among those retoratin methods, despite of many advantages, iterative iamge restoration is limited in use because of slow convergence. In the present paper, fast iterative image restoration algorithms based on preconditoning are proposed. The preconditioner can be obtained by using the characteristics finite impulse response (FIR) filter structure.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2000년도 추계학술대회논문집A
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• pp.647-652
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• 2000

This paper proposes a collision warning/avoidance algorithm using a trajectory prediction method. This algorithm is based on 2-dimensional kinematics and the Kalman filter has been used to obtain the information of the object vehicle. This algorithm has been investigated via computer simulation and showed a good trajectory prediction performance. The proposed collision warning/avoidance algorithm would enhanced driver acceptance for a collision warning/avoidance system.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1986년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 17-18 Oct. 1986
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• pp.510-513
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• 1986

In recent years the Kalman filter(extended Kalman filter) have been applied to a wide variety of tracking moving targets, because of its properties. For such a reason, in this paper we attempt to study on adaptive filter algorithms which estimate unknown bias maneuvering inputs.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2011년도 정기총회 및 추계학술대회 논문집
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• pp.1493-1496
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• 2011

Research results for LMS-based algorithms performances using real records of the traffic noise are discussed. The various algorithms based on LMS method are studied regarding their convergence speed and noise reduction index. Most effective algorithms are chosen for implementation in the active noise control barriers. The optimal step size, and number of adaptive filter taps are addressed during parametric study of the algorithms.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.211-211
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• 2000

The multiple targets tracking problem has been one of main issues in the radar applications area in the last decade. Besides the standard Kalman filtering, various methods including the variable dimension filter, input estimation filter, interacting multiple model (IMM) filter, federated variable dimension filter with input estimation, probable data association (PDA) filter etc. have been proposed to address the tracking and sensor fusion issues. In this paper, two existing tracking algorithms, i.e. the IMMPDA filter and the variable dimension filter with input estimation (VDIE), are combined for the purpose of improving the tracking performance of maneuvering targets in clutter. To evaluate the tracking performance of the proposed algorithm, three typical maneuvering patterns i.e. Waver, Pop-Up, and High-Diver motions, are defined and are applied to the modified IMMPDA filter considered as well as the standard IMM filter. The smaller RMS tracking errors, in position and velocity, of the modified IMMPDA filter than the standard IMM filter are demonstrated through computer simulations.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -2
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• pp.753-756
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• 2000

In this paper we present and compare two different spatio-temporal decorrelation learning algorithms for updating the weights of a linear feedforward network with FIR synapses (MIMO FIR filter). Both standard gradient and the natural gradient are employed to derive the spatio-temporal decorrelation algorithms. These two algorithms are applied to multichannel blind deconvolution task and their performance is compared. The rigorous derivation of algorithms and computer simulation results are presented.