• 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.

• 소음진동
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• 제9권2호
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• pp.265-272
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• 1999

A LMS algorithms has been widely used for an adaptive filter algorithm in active noise control systems. But this algorithm has poor convergence and it is very difficult to select optimal convergence parameters in this algorithm. In this paper, a fuzzy LMS algorithm where the convergence parameters are computed using a fuzzy logic controller was proposed. A proposed algorithm was applied to active noise control system in HVAC(central Heating Ventilation and Air Conditioning) ducts. The experimental ducts and experimental apparatus were designed and manufactured for experiments, and the modelling of the experimental ducts was also performed for computer simulations. Computer simulations and experiments were performed to show the effectiveness of a proposed algorithm.

• 전기학회논문지
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• 제60권1호
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• pp.150-155
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• 2011

In an active noise control systems, an IIR filter may cause a problem in stability beacause of its poles. For IIR filter, its poles goes sometimes out of a unit circle in a z-plane in the transition state, where the adaptive algorithm converges to the optimum value, which causes the system to diverge. Fuzzy LMS algorithm has a better convergence property than conventional LMS algorithms, but is not applicable to IIR filter because of the reasons. Stabilized adaptive algorithm could be improves stability by moving the pole of IIR filer toward the origin forcibly in the transient state, and by introducing forgetting factor to maintain the optimum convergence when it reaches to the steady state. In this paper, We proposed stabilized adaptive fuzzy LMS algorithms with IIR filter structures, for single channel active noise control with ill conditioned signal case. Computer simulations were performed to show the effectiveness of a proposed algorithm.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2002년도 춘계종합학술대회
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• pp.518-522
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• 2002

This paper proposes a new application of Fuzzy logic to Variable Step Size Least Mean Square (VS-LMS) adaptive beamforming algorithm in CDMA systems. The proposed algorithm adjusts the step size of the Least Mean Square (LMS) by using the application of Fuzzy logic in which the increase or decrease of step size depends on the fuzzy inference results of the Mean Square Error (MSE). Computer simulation results show that the proposed algorithm has a better capacity of tracking compared with the conventional LMS algorithms and other variable step size LMS algorithms.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1994년도 추계학술대회 논문집 학회본부
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• pp.373-375
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• 1994

In this paper, the fuzzy LMS algorithm where the convergence coefficient is computed by a fuzzy logic controller was proposed. The proposed fuzzy LMS algorithm showed better convergence property and stability than conventional LMS algorithms. The estimation error and misadaptation degree were used for Input of the fuzzy logic controller. In a airconditioning duct case, various conditions were investigated to design active noise controllers. A case with acoustic feedback, the proposed algorithm showed good performances through computer simulations.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 B
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• pp.692-694
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• 1995

Multi-channel adaptive algorithms have poor convergence behaviors because of difficulties in selection of convergence coefficients. In this paper, a MCFLMS(Multi-Channel Fuzzy LMS) algorithm, where the convergence coefficients are updated by a fuzzy inference engine, was proposed. A proposed algorithm showed better convergence characteristics than conventional MCLMS(Multi-Channel LMS) algorithms in computer simulations.

• 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.

• 한국자동차공학회논문집
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• 제19권4호
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• pp.84-90
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• 2011

In active noise control filter, LMS algorithms which used for control filter, assure the convergence property, and computational burden of these algorithms are proportionate to the filter taps. The convergence speed of LMS algorithms is mainly determined by value of the convergence coefficient, so optimal selection of the value of convergence coefficient is very important. In this paper, We proposed novel adaptive fuzzy logic LMS algorithms with FIR filter structure which has better convergence speed and less computational burden than conventional LMS algorithms, for single channel active noise control with ill conditioned signal case. Computer simulations were performed to show the effectiveness of a proposed algorithms.

• 한국산학기술학회논문지
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• 제13권8호
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• pp.3647-3653
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• 2012

능동 소음제어 시스템에 사용되는 IIR 필터 구조는 구조적으로 안정성이 보장되어야 하며 이는 분모 전달 함수의 근이 단위원 내부에 존재하여야 한다. 따라서 이를 결정하는 제어 필터의 계수의 적절한 조정이 중요해 진다. 본 논문에서는 적응과정에서 불안정할 우려가 있는 IIR 필터 구조를 가지는 Filtered_U LMS 알고리즘에 안정화 알고리즘과 수렴속도 향상을 위한 퍼지논리를 이용한 수렴계수 계산 알고리즘을 제안하였다. 제안한 알고리즘이 FIR 필터 구조 알고리즘보다 계산량이 적고 수렴특성이 우수함을 시뮬레이션을 통하여 보였다.

• 한국통신학회논문지
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• 제21권10호
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• pp.2579-2585
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• 1996

In this paper, a complex fuzzy adaptive decision feedback equalizer(CFADFE) based on the LMS algorithm is proposed. The propoed equalizer is based on the complex fuzzy adaptive equalizer. The CFADFE isconstructed from a set of changeable complex fuzzy IF-THEN rules, where the 'IF' part of the rule is characterized by the state from a set of changealble complex fuzzy IF-THEN rules, where the 'IF' part of the rule is characterized by the state of the desision feedback. the role of decision feedback is to reduce the computational complexity. Computer simulation of the decision feedback. The role of decision feedback is to reduce the computational complexity. Computer simulation shosw that the CFADFE notonly reduces the computational complexity but also improves the performance compared with the conventional complex fuzzy adaptive equalizers. We also show that the adaptation speed is greatly improved by incorporating some linguistic information about the channel into the equalzer. It is applied to M-ary QAM digital communication system with linear and nonlinear complex channel characteristics.