• The Journal of the Acoustical Society of Korea
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• 제27권3E호
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• pp.95-103
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• 2008

In this paper, the new hybrid adaptive Volterra filter was proposed to be applied for compensating the nonlinear distortion of memoryless nonlinear systems with saturation characteristics. Through computer simulations as well as the analytical analysis, it could be shown that it is possible for both conventional Volterra filter and proposed hybrid Volterra filter, to be applied for linearizing the memoryless nonlinear system with nonlinear distortion. Also, the simulations results demonstrated that the proposed hybrid filter may have faster convergence speed and better capability of compensating the nonlinear distortion than the conventional Volterra filter.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1987년도 전기.전자공학 학술대회 논문집(II)
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• pp.1379-1382
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• 1987

IN ADAPTIVE LINEAR PREDICTION, AN ADAPTIVE CAPABILITY IS BUILT INTO THE PROCESSOR SUCH THAT AS THE IMAGE STATISTICS CHANGE, THE PREDICTION FILTER COEFFICIENTS THEMSELVES CHANGE, PRODUCING A NEW FILTER MORE CLOSELY OPTIMIZED TO THE NEW SET OF IMAGES STATISTICS. THE LMS ALGORITHM MAY BE USED TO ADAPT THE COEFFICIENT OF AN ADAPTIVE PREDICTION FILTER FOR IMAGE SOURCE ENCODING. IN THIS PAPER, TWO CODING SYSTEMS USING DPCM AND LMS ALGORITHMS RESPECTIVELY FOR OBTAINING THE FIRST TRANSFORMED COEFFICIENT IN HYBRID CODING ARE COMPARED.

• 한국통신학회논문지
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• 제22권1호
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• pp.193-204
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• 1997

In this research we propose the design of the Order Statistic-Adaptive Weighted Average Hybrid(OS-AWAH) filter which can suppress noise from the corrupted image sequence effectively while preserving the image structure. The proposed filter combines the desirable properties of the order static based spatial filter which can preserve the image structure while reducing noise and the adaptive weighted average based temporal filter which can adapt the filtering weights according to the amount of motion without motion estimation. Performance characteristics of the OS-AWAH filter in noisy sequences containing moving step edges are investigated throuth computer simulations and compared with the median based filters such as 3-D WM(weighted median) filter, MMF (multistage median filter), ADCWM(adaptive directional center weighted median) filter. The visual evaluations are also carried out by applyin gthe filters to the real images. The statistical analysis and experimental reslts show that the OS-AWAH filter is effective in preserving image structures while suppressing noise effectively without motion compensation preprocessing.

• 한국ITS학회 논문지
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• 제12권4호
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• pp.76-86
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• 2013

기존의 와이파이 기반 측위 시스템에서 주로 사용되는 칼만필터와 파티클 필터는 실내공간의 구조적 특성을 반영하지 못해 정확도가 낮고, 계산 부하 또한 높기 때문에 휴대기기를 이용한 실내 측위에 적용하는데 한계를 지닌다. 이러한 한계를 극복하고자 본 논문은 와이파이 기반 측위 시스템을 위한 적응형 혼합필터를 제안한다. 제안된 필터는 칼만 필터의 일반적인 적용 체계를 활용하였으며, 적은 수의 파티클을 사용한 파티클 필터의 개념 또한 추가되었다. 제안된 필터는 일반 칼만 필터와는 달리 예측 가중치를 동적으로 변화시켜 동작하며, 위치 예측을 위한 파티클을 실내공간의 경로 네트워크상에 한정하는 특징을 지닌다. 검증결과 적응형 혼합 필터는 일반 칼만 필터에 비해 높은 정확도를 보이며, 일반 파티클 필터에 비해서도 정확도 및 계산시간의 측면에서 유의할만한 성능향상을 보였다.

• Journal of Mechanical Science and Technology
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• 제16권3호
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• pp.310-319
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• 2002

This paper deals with the analytical modeling, and the experimental verification of the strain rate self-sensing method using a hybrid adaptive filter for a cantilevered piezoelectric beam. The piezoelectric beam consists of two laminated lead zirconium titanates (PZT) on a metal shim. A mathematical model of the beam dynamics is derived by Hamilton's principle and the accuracy of the modeling is verified through the comparison with experimental results. For the strain rate estimation of the cantilevered piezoelectric beam, a self-sensing mechanism using a hybrid adaptive filter is considered. The discrete parts of this mechanism are realized by the DS1103 DSP board manufactured by dSPACE$\^$TM/. The efficacy of this method is investigated through the comparison of experimental results with the predictions from the derived analytical model.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1669-1674
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• 2004

In this paper, a nonlinear information filter (IF) for curvilinear motions in an interacting multiple model (IMM) algorithm to track a maneuvering vehicle on a road is investigated. Driving patterns of vehicles on a road are modeled as stochastic hybrid systems. In order to track the maneuvering vehicles, two kinematic models are derived: A constant velocity model for linear motions and a constant-speed turn model for curvilinear motions. For the constant-speed turn model, a nonlinear IF is used in place of the extended Kalman filter in nonlinear systems. The suggested algorithm reduces the root mean squares error for linear motions and rapidly detects possible turning motions.

• 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.

• International Journal of Control, Automation, and Systems
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• 제2권3호
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• pp.310-318
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• 2004

In this paper, an unscented Kalman filter (UKF) for curvilinear motions in an interacting multiple model (IMM) algorithm to track a maneuvering vehicle on a road is investigated. Driving patterns of vehicles on a road are modeled as stochastic hybrid systems. In order to track the maneuvering vehicles, two kinematic models are derived: A constant velocity model for linear motions and a constant-speed turn model for curvilinear motions. For the constant-speed turn model, an UKF is used because of the drawbacks of the extended Kalman filter in nonlinear systems. The suggested algorithm reduces the root mean squares error for linear motions and rapidly detects possible turning motions.

• Smart Structures and Systems
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• 제31권5호
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• pp.437-454
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• 2023

Real-time hybrid simulation (RTHS), which has the advantages of a substructure pseudo-dynamic test, is widely used to investigate the rate-dependent mechanical response of structures under earthquake excitation. However, time delay in RTHS can cause inaccurate results and experimental instabilities. Thus, this study proposes a model-based adaptive control strategy using a Kalman filter (KF) to minimize the time delay and improve RTHS stability and accuracy. In this method, the adaptive control strategy consists of three parts-a feedforward controller based on the discrete inverse model of a servohydraulic actuator and physical specimen, a parameter estimator using the KF, and a feedback controller. The KF with the feedforward controller can significantly reduce the variable time delay due to its fast convergence and high sensitivity to the error between the desired displacement and the measured one. The feedback control can remedy the residual time delay and minimize the method's dependence on the inverse model, thereby improving the robustness of the proposed control method. The tracking performance and parametric studies are conducted using the benchmark problem in RTHS. The results reveal that better tracking performance can be obtained, and the KF's initial settings have limited influence on the proposed strategy. Virtual RTHSs are conducted with linear and nonlinear physical substructures, respectively, and the results indicate brilliant tracking performance and superb robustness of the proposed method.

• 조명전기설비학회논문지
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• 제14권1호
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• pp.94-101
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• 2000

본 논문에서는 서브밴드 기법을 이용한 다중채널 능동소음제어 알고리즘을 제안하였다. 제안된 서브밴드 제어 기법은 3차원 폐공간에서의 능동소음제어서 가장 문제가 되는 계산량을 줄이고 성능올 향상시키기 위한 방법으로, 소음신호를 여러 개의 주파수 밴드로 분할하여 병렬 처리함으로서 원하는 주파수 범위의 소음을 효과적으로 제거할 수 있어 기존의 알고리즘 보다 낮은 차수의 적웅필터를 사용할 수 있다. 적용필터 알고리즘으로 서브밴드로 나펀 기준입력 대신에 오차신호를 perfiltering하는 adjoint LMS 알고리즘을 적용하여 전체적인 계산량의 감소를 이룰 수 있었으며, 성능 향상올 위하여 기존의 하이브리드 제어기법을 변형하여 전향제어기와 궤환제어기의 특성을 가중적으로 갖는 하이브리드 제어기법올 광대역 소음제어 시스템에 적용하여 우수한 소음제거특성과 시스템의 높은 안정성올 얻었다. 제안된 알고리즘의 성능을 평가하기 위해서 컴퓨터 시뮬레이션을 통해 기존의 알고리즘과 비교하였다.