• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.98.5-98
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• 2001

An efficient adaptive nonlinear compensator, based on a wavelet transform domain adaptive Volterra filter along with a modified escalator algorithm, is proposed to speed up the convergence rate of an adaptive LMS algorithm. In particular, it is well known that the e.g., slow convergence speed of an adaptive LMS algorithm depends on the statistical characteristics (e.g., large eigenvalue spread) of the corresponding auto-correlation matrix of the input vector. To solve such a convergence problem, the proposed approach utilizes a modified escalator algorithm and a wavelet transform domain adaptive LMS Volterra filtering technique, which leads to diagonalization of the auto-correlation matrix of the ...

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.176-181
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• 1992

In this paper, an adaptive generalized predictive control(GPC) algorithm which minimizes a N-stage cost function is proposed. The resulting controller is based on GPC algorithm and can be used in unknown plant parameters as the parameters of one step ahead predictor are estimated by recursive least squares method. The estimated parameters are extended to G,P, and F amtrix which contain the parameters of N step ahead predictors. And the minimization of cost function assuming no constraints on future controls results in the projected control increment vector. Hence this adaptive GPC algorithm can be used for either unknown system or varing system parameters, and it is also shown through simulations that the algorithm is robust to the variation of system parameters. This adaptive GPC scheme is shown to have the same stability properties as the deterministic GPC, and requires small amount of calculation compared to other adaptive algorithms which minimize N-stage cost function. Especially, in case that the maximum output horizon is 1, the proposed algorithm can be applicable to direct adaptive GPC.

• 대한전기학회논문지:전력기술부문A
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• 제52권12호
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• pp.698-704
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• 2003

Autoreclosure provides a mean of improving power transmitting ability and system stability. The conventional reclosure adopts the fixed dead time interval strategy, that is, the reclosure is activated after a time delay to restore the system to normal as quickly as possible without regard to the system conditions, however, these simple techniques cannot give the optimal operating performance. For this reason, various adaptive reclosure algorithms have been proposed recently, This paper presents an adaptive autoreclosure algorithm including the variable dead time, optimal reclosure, sequential reclosure and emergency extended equal-area criterion (EEAC) algorithm in order to improve the system stability. The reclosure algorithm performs out the operations that are attuned to the power system conditions. The proposed adaptive reclosure algorithm is verified and tested by using EMTP MODELS, and the simulation results show that the system oscillations are reduced and the transient stability is enhanced by employing the proposed adaptive reclosure algorithm.

• International Journal of Internet, Broadcasting and Communication
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• 제11권1호
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• pp.39-46
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• 2019

This paper proposes an adaptive threshold watershed algorithm, which is the method used for image segmentation and boundary detection, which extends the region on the basis of regional minimum point. First, apply adaptive thresholds to determine regional minimum points. Second, it extends the region by applying adaptive thresholds based on determined regional minimum points. Traditional watershed algorithms create over-segmentation, resulting in the disadvantages of breaking boundaries between regions. These segmentation results mainly from the boundary of the object, creating an inaccurate region. To solve these problems, this paper applies an improved watershed algorithm applied with adaptive threshold in regional minimum point search and region expansion in order to reduce over-segmentation and breaking the boundary of region. This resulted in over-segmentation suppression and the result of having the boundary of precisely divided regions. The experimental results show that the proposed algorithm can apply adaptive thresholds to reduce the number of segmented regions and see that the segmented boundary parts are correct.

• 대한전자공학회논문지
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• 제23권4호
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• pp.578-585
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• 1986

This paper describes a new two-dimensional adaptive lattice algorithm which determines reflection coefficients recursively by applying the gradient search technique to a two-dimensional lattice filter proposed by Parker and Kayran. The convergence characteristics of the proposed algorithm are also described. A new tow-dimensional adaptive lattice \ulcorneralgorithm has been obtained through the application of the \ulcorneralgorithm to the two-dimention adaptive lattice algorithm. Computer simulation proves that the convergence speed of the two-dimension adaptive lattice \ulcorneralgorithm is reladtively higher than that of the conventional adaptive lattice algorithm when \ulcornerhas a small value.

• 대한전기학회논문지:전력기술부문A
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• 제55권9호
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• pp.365-375
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• 2006

This paper is presented by the application of parallel adaptive evolutionary algorithm(PAEA) to search an optimal solution of a thermal unit commitment problem. The adaptive evolutionary algorithm(AEA) takes the merits of both a genetic algorithm(GA) and an evolution strategy(ES) in an adaptive manner to use the global search capability of GA and the local search capability of ES. To reduce the execution time of AEA, the developed algorithm is implemented on an parallel computer which is composed of 16 processors. To handle the constraints efficiently and to apply to Parallel adaptive evolutionary algorithm(PAEA), the states of thermal unit are represented by means of real-valued strings that display continuous terms of on/off state of generating units and are involved in their minimum up and down time constraints. And the violation of other constraints are handled by repairing operator. The procedure is applied to the $10{\sim}100$ thermal unit systems, and the results show capabilities of the PAEA.

• 한국음향학회지
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• 제33권5호
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• pp.309-315
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• 2014

본 논문은 능동 소음 제어 시스템에 적합한 새로운 가변 수렴 상수 filtered-x gradient adaptive lattice(NVSS-FxGAL) 알고리즘을 제안한다. Gradient adaptive lattice(GAL) 알고리즘은 협대역 특성을 가지는 소음을 효과적으로 제어할 수 있다. GAL 알고리즘의 수렴 성능을 개선하기 위한 가변 격자 필터의 각 단계에 동일하게 적용하면 입력 신호의 특성 변화에 강인하게 대처하지 못한다. 제안 알고리즘은 격자 필터의 각 단계에 적합한 로컬 가변 수렴상수를 이용하여 안정적이고 일관성 있는 수렴 성능을 보장한다. 실험을 통해 제안 알고리즘은 빠른 수렴 속도와 낮은 정상 상태를 보임을 확인하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.331-334
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• 1996

It is a well-known problem that the adaptive control has a poor transient response. In order to improve this problem, the scheme that model-reference adaptive control (MRAC) uses the genetic algorithm (GA) in the search for parameters is proposed. Use genetic algorithm (GA) in the searching for controller's parameters set and conventional gradient method for fine tuning. And show the reduction of the oscillations in transient response comparing with the conventional MRAC.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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• pp.2459-2462
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• 2003

In this paper, we Propose a wavelet based adaptive algorithm which improves the convergence speed and reduces computational complexity using the fast running FIR filtering efficiently. We compared the performance of the proposed algorithm with time and frequence domain adaptive algorithm using computer simulation of adaptive noise canceler based on synthesis speech.

• 한국음향학회:학술대회논문집
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• 한국음향학회 1991년도 학술발표회 논문집
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• pp.38-41
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• 1991

RLS algorithms are required for applications to adaptive line enhancers, adaptive equalizers for voiceband telephone and HF modems, and wide-badn digital spectrum mobile raio in which their convergence time and tracking speed are significant. The fast QR RLS algorithm satisfies above the requirements. Its computational complexity is linearly proportional to the tap number of a filter, N and its performance remains numerically stable. From the result of simumulation, the fast QR RLS algorithm represented Cioffi is better than gradient based algorithm in its initial performance when being applied to an adaptive line enhancer for cancelling noise.