• ETRI Journal
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• 제27권3호
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• pp.257-266
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• 2005

Many multi-modulus blind equalization algorithms (MMA) have been presented in the past to overcome the undesirable high misadjustment exhibited by the well-known constant modulus algorithm. Some of these MMA schemes, specifically tailored for quadrature amplitude modulation (QAM) constellations, have also been proved to fix the phase offset error without needing any rotator at the end of the equalizer stage. In this paper, a new multi-modulus algorithm is presented for QAM signals. The contribution lies in the technique to incorporate the sliced symbols (outcomes of decision device) in the multi-modulus-based weight adaptation process. The convergence characteristics of the proposed sliced multi-modulus algorithm (S-MMA) is demonstrated by way of simulations, and it is shown that it gives better steady-state performance in terms of residual inter-symbol interference and symbol-error rate. It has also been shown that the proposed algorithm exhibits lesser steady-state misadjustment compared to the best reported MMA.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 제14회 신호처리 합동 학술대회 논문집
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• pp.99-102
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• 2001

The brief proposes to reduce the misadjustment of the adaptive filter coefficients that trace the interference signal in the sidelobe. The proposed sidelobe canceller that has the form of Griffiths-Jim sidelobe canceller with an adaptive compensator that reduces the misadjustment. The proposed sidelobe canceller updates the filter coefficients by the error Signet of the adaptive compensator instead of the output signal. This brief shows the Improvement of the performance by comparing the computer simulation of the output signal of the Griffiths-Jim sidelobe canceller to the output signal of the proposed sidelobe canceller.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 제14회 신호처리 합동 학술대회 논문집
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• pp.91-94
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• 2001

Recently a constant-norm constraint equation-error method was proposed to solve the bias problem in adaptive IIR filtering. However, the method adopts a fixed step-size and thus results in slow convergence for a small step-size and significant misadjustment error for a largestep-size. In this paper, we propose a variable step-size (VSS) algorithm that greatly improves convergence properties of the constant-norm constraint equation-error method. The analysis and the simulation results show that the proposed method indeed achieves both fast convergence and small misadjustment error.

• 한국통신학회논문지
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• 제21권5호
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• pp.1172-1179
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• 1996

General adaptive noise canceller(ANC) suffers from the misadjustment of adaptive filter weights, because of the gradient-estimate noise at steady state. In this paper, an adaptive noise cancellation algorithm with speech detector which is distinguishing speech from silence and adaptation-transient region is proposed. The speech detector uses property of adaptive prediction-error filter which can filter the highly correlated speech. To detect speech region, estimation error which is the output of the adaptive filter is applied to the adaptive prediction-error filter. When speech signal apears at the input of the adaptive prediction-error filter. The ratio of input and output energy of adaptive prediction-error filter becomes relatively lower. The ratio becomes large when the white noise appears at the input. So the region of speech is detected by the ratio. Sign algorithm is applied at speech region to prevent the weights from perturbing by output speech of ANC. As results of computer simulation, the proposed algorithm improves segmental SNR and SNR up to about 4 dBand 11 dB, respectively.

• Journal of Power Electronics
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• 제14권1호
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• pp.175-182
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• 2014

Tracking harmonic current quickly and precisely is one of the keys to designing active power filters (APF). In the past, the current state feedback decoupling PI control was an effective means for three-phase systems in the current control of constant voltage constant frequency inverters and high frequency PWM reversible rectifiers. This paper analyzes in detail the limitation of the conventional PI conditioner in the APF application field and presents a novel PI control method. Canceling the delay of one sampling period and the misadjustment for tracking the harmonic current is the key problem of this PI control. In this PI control, the predictive output current value is obtained by a state observer. The delay of one sampling period is remedied in this digital control system by the state observer. The predictive harmonic command current value is obtained by a repetitive predictor synchronously. The repetitive predictor can achieve better predictions of the harmonic current. By this means, the misadjustment of the conventional PI control for tracking the harmonic current is cancelled. The experiment results with a three-level NPC APF indicate that the steady-state accuracy and dynamic response of this method are satisfying when the proposed control scheme is implemented.

• 자연과학논문집
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• 제8권2호
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• pp.63-67
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• 1996

LVCMS나 LMF와 같이 고차의 통계에 근거한 적응 신호 알고리즘들은 입력신호에 꼬리가 두툼한 확률밀도를 같는 잡음이 섞여있는 경우 현저한 성능 저하를 보여준다. 일반적인 알고리즘 분석 방법에서는 순환식에서 2차 보다 큰 power를 갖는 항들을 모두 무시하기 때문에 정확한 알고리즘의 성능을 예측하지 못할 수도 있다. 이 논문에서는 새로운 분석방법을 통하여 무시된 항들의 영향이 무엇인가를 알아본다. 분석 결과 무시된 항들은 스텝 크기의 상한선에는 영향을 미치지 못하나 misadjustment를 증가시킬 수 있는 것으로 나타났다. 그러나 그 영향은 스텝 크기의 제곱에 비례하여 감소한다.

• 한국인터넷방송통신학회논문지
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• 제19권1호
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• pp.51-56
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• 2019

본 논문은 nonconstant modulus 특성의 높은 스펙트럼 효율을 갖는 16-QAM 신호 전송 시 채널에 의한 부호간 간섭을 줄이기 위한 CCA (Compact Constellation Algorithm)와 RMMA (Region-based MMA) 블라인드 적응 등화 알고리즘의 성능 비교에 관한 것이다. CCA는 결정 장치의 출력인 sliced symbol과 16개의 모든 신호점들을 compact화한 통계적 심볼을 이용하여 탭 계수 갱신을 위한 오차 신호의 분산을 줄여 초기 수렴과 misadjustment를 개선하지만 연산량이 증대되며, RMMA는 신호점이 속하는 영역을 기준으로 4개의 constant modulus 신호로 변환한 후 오차 신호를 얻으므로 빠른 수렴속도와 misadjustment 및 채널 추적 능력이 연산량 증가없이 개선되는 효과를 얻을 수 있다. 논문에서는 동일한 채널에서 이들 알고리즘을 구현한 후 블라인드 적응 등화 성능을 등화기 출력 신호의 성상도, 잔류 isi양, MSE 및 SER을 적용하여 비교하였다. 시뮬레이션의 결과 출력 신호 성상도, 잔류 isi 및 MSE에서는 RMMA가 CCA보다 우월하였지만 수렴 속도는 약1.3배 정도 늦어짐을 알 수 있었다. 또한 잡음에 대한 robustness를 나타내는 SER 성능에서는 SNR이 적을때는 CCA가 우월하지만 6dB 이상에서는 RMMA가 우월하였다.

• The Journal of the Acoustical Society of Korea
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• 제27권2E호
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• pp.64-68
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• 2008

This paper investigates noise reduction performance and performs convergence analysis of a Variable Error Data Normalized Step-Size Least Mean Square(VEDNSS LMS) algorithm. Adopting VEDNSS LMS results in higher system complexity, but noise is reduced providing fast convergence speed Mathematical analysis demonstrates that tap coefficient misadjustment converges. This is confirmed by computer simulation with the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.224-227
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• 1993

In this paper, a new LMS algorithm with a variable step size (VVS LMS) is presented. The change of step size .mu. at each iteration, which increases or decreases according to the misadaptation degree, is computed by a proportional fuzzy logic controller. As a result the algorithm has very good convergence speed and low steady-state misadjustment. The norm of the cross correlation between the estimation error and input signal is used. As a measure of the misadaptation degree. Simulation results are presented to compare the performance of the VSS LMS algorithm with the normalized LMS algorithm.

• 산업기술연구
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• 제13권
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• pp.33-41
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• 1993

In this paper, a new LMS algorithm with a fuzzy variable step size (FVS LMS) is presented. The change of step size ${\mu}$, at each iteration which is increases or decreases according to the misadaptation degree, is computed by a proportional fuzzy logic controller. As a result the algorithm has very good convergence speed and low steady-state misadjustment. As a measure of the misadaptation degree, the norm of the cross correlation between the estimation error and input signal is used. Simulation results are presented to compare the performance of the FVSS LMS algorithm with the normalized LMS algorithm.