• Journal of Power Electronics
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• 제15권6호
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• pp.1619-1627
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• 2015

This paper presents a power system harmonic elimination using the mixed adaptive linear neural network and variable step-size leaky least mean square (ADALINE-VSSLLMS) control algorithm based active power filter (APF). The weight vector of ADALINE along with the variable step-size parameter and leakage coefficient of the VSSLLMS algorithm are automatically adjusted to eliminate harmonics from the distorted load current. For all iteration, the VSSLLMS algorithm selects a new rate of convergence for searching and runs the computations. The adopted shunt-hybrid APF (SHAPF) consists of an APF and a series of 7^th tuned passive filter connected to each phase. The performance of the proposed ADALINE-VSSLLMS control algorithm employed for SHAPF is analyzed through a simulation in a MATLAB/Simulink environment. Experimental results of a real-time prototype validate the efficacy of the proposed control algorithm.

• 한국멀티미디어학회논문지
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• 제12권1호
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• pp.26-30
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• 2009

본 논문에서는 로버스트 통계학의 순위 추정을 기반으로 하고 순서통계학의 L-추정자를 이용한 적응 순환 최소 순위(RLR) L-필터를 제안한다. 제안한 RLR-L 필터는 비선형 적응알고리즘을 가진 비선형 적응 필터로서 오차의 분산측정을 최소화하는 관점의 최적 필터로 가변적인 스텝 크기를 가지며 적응한다. 제안한 필터는 영상신호와 같은 비정체 신호나 가우시안 잡음 또는 임펄스 잡음과 같은 비선형 채널에 적합하다.

• 대한전자공학회논문지
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• 제25권3호
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• pp.322-326
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• 1988

The sigma filter is a nonlinear filter of modifying average filter to develop edge-preserving characteristics. However, this filter is yet weak to the impulsive noise such as BSC noise. Therefore it has not been used so highly in the image restoration area. In this paper, We propose an adaptive image restoration algorithm using the local statistic and the characteristic of human eyes in order to compensate its drawback and to improve its performance. The performance of the proposed algorithm and the vonventional ones are compared for images degraded by BSC noise. The proposed algorithm shows better performance than the median filter and yields 5 dB performance improvement over the convertional K-sigma filter on SNR gain.

• 제어로봇시스템학회논문지
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• 제7권11호
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• pp.944-952
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• 2001

Inertial navigation system(INS) errors increase with time due to inertial sensor errors, and therefore it is desired to combine INS with external aids such as GPS. However GPS informations have a randomly abrupt jump due to a sudden corruption of the received satellite signals and environment, and moreover GPS can\`t provide navigation solutions. In this paper, smoothing and prediction schemes are proposed for GPS`s jump or unavailable GPS. The smoothing algorithm which is designed as a scalar adaptive filter, smooths abrupt jump. The prediction algorithm which is proved by Schuler error model of INS, estimates INS error in appropriate time. The outputs of proposed algorithm apply stable measurements to GPS aided INS Kalman filter. Simulations show that the proposed algorithm can effectively remove measurement jump and predict INS error.

• 한국통신학회논문지
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• 제29권2C호
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• pp.222-228
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• 2004

본 논문은 적응 필터에서 소요되는 계산량을 감소시키기 위해 새롭게 제안하는 적응 알고리즘에 대하여 논하고 있다. 새로운 적응 알고리즘은 필터의 계수를 조정함에 있어서 정규화 입력신호의 크기 대신 입력신호의 부호만을 사용하는 것인데, 이렇게 함으로써 많은 계산량을 차지하는 승산과 제산 연산이 필요없게 된다. 제안한 알고리즘의 수렴특성을 분석하기 위하여 수렴조건 및 수렴속도 등을 수학적으로 유도하였다. 또한 본 알고리즘을 반향제거기에 적용하여 시뮬레이션을 수행하였고, 다른 알고리즘을 적용한 경우의 수렴성능과 비교하였다. 시뮬레이션 결과, 본 알고리즘을 적용한 반향제거기는 NLMS 알고리즘을 적용한 반향제거기와 거의 동일한 수렴성능을 나타내는 것으로 확인되었다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.993-995
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• 1996

This paper proposes an adaptive Filtered-X LMS algorithm with robustness. The proposed system updates filter parameters to keep the performance even if the conventional Active Noise Control (ANC) system well does not work. As a result of the computer simulation, the proposed system has all the advantage of the system using the conventional Filtered-X LMS algorithm. Also some results from the proposed algorithm present that the system is stable when the Adaptive filter does not work. Therefore, the proposed system using the Adaptive Filtered-X LMS algorithm must have much advantage than the system using the conventional algorithm in the side of the stability and performance.

• 대한의용생체공학회:의공학회지
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• 제13권2호
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• pp.107-114
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• 1992

An adaptive filter for noise cancellation of ECG Is proposed. An adaptive noise canceller using the least mean squares algorithm Is used to reduce unwanted noise. An adaptive filter for nolse cancella lion minimizes the mean-square error between a primary input and a reference input. A primary input is the noisy ECG, and a reference input is a noise that Is correlated in some way with the noise in the primary input or a signal that is correlated only with ECG in the primary input.

• 한국통신학회논문지
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• 제22권4호
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• pp.706-713
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• 1997

In this paper, we propose a band stop filter(BSF) for reducing drag-like effect of the low pass filter(LPF), a block by block adaptive filtering method, and a motion adaptive filtering method, which show better results in terms of PSNR or human visual perception compared to the conventional method using LPF. The BSF improves the draglike effects of the low pass filter by passing temporal high frequency components of video sequences which correspond to objects with large motion. The proposed adaptive methods also improve the conventional adaptive filtering by modifying the conventional algorithm and applying the algorithms for small blocks. The simulation results show that the proposed filtering methods show better results in terms of PSNR and subjective tests in most cases. Also in case of block by block adaptive filtering, it is verified that the application of the algorithm for smaller block gives better results.

• 전기학회논문지
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• 제62권1호
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• pp.133-139
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• 2013

Convex combination of two adaptive filters is an efficient method to improve adaptive filter performances. In this paper, a subband convex combination method of two adaptive filters for fast convergence rate in the transient state and low steady state error is presented. The cost function of mixing parameter for a subband convex combination is defined, and from this, the coefficient update equation is derived. Steady state analysis is used to prove the stability of the subband convex combination. Some simulation examples in system identification scenario show the validity of the subband convex combination schemes.

• 전자공학회논문지B
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• 제30B권12호
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• pp.12-20
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• 1993

In a conventional adaptive echo canceller, an ADF(Adaptive Digital Filter) with TDL(Tapped-Delay Line) structure modelling the echo path uses the LMS(Least Mean Square) algorithm to compute the coefficients, and NET detector using energy comparison method prevents the ADF to update the coefficients during the periods of the NET signal presence. The convergence speed of the LMS algorithm depends on the eigenvalue spread ratio of the reference signal and NET detector using the energy comparison method yields poor detection performance if the magnitude of the NET signal is small. This paper presents a new adaptive echo canceller which uses the pre-whitening filter to improve the convergence speed of the LMS algorithm. The pre-whitening filter is realized by using a low-order lattice predictor. Also, a new NET signal detection algorithm is presented, where the start point of the NET signal is detected by computing the cross-correlation coefficient between the primary input and the ADF output while the end point is detected by using the energy comparison method. The simulation results show that the convergence speed of the proposed adaptive echo canceller is faster than that of the conventional echo canceller and the cross-correlation coefficient yields more accurate detection of the start point of the NET signal.