• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.12
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• pp.106-113
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• 1997

While driving, the low frequency interior noise below 200Hz causes the main component that irritates the auditory acoustic sense. But these passive control methods bring out increment in cost and weight of the vehicle and result in low efficiency. Recently, various ANC(Active Noise Control) methos to suppress the low frequency noise began to launch into application. In this study, we implemented the active noise control system for passenger vehicle to cancel the engine booming noise using DSP-based control unit, 4 micorphones, and 2 speakers. We used MEFX-LMS (Multiple Error Filtered X-Least Mean Square) algorithm since it can be easily implemented in real time. Also, MEFX-RLS algorithm was taken to enhance the suppression of the harmonic components of the engine booming noise inspite of its computational complexity. The performance of two adaptive algorithms were analyzed with experimental resutls.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.13 no.5
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• pp.475-483
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• 2002

The new architecture for the stabilization of an adaptive linearizer using the RLS algorithm is presented. The delay lock loop is apl)lied to compensate the feedback loop delay of the nonlinear amplifier output, and the Yang's algorithm is used to mitigate the numerical unstability of the RLS algorithm. This method is applied to the linearizer using the polynomial predistorter, and it's efficacy is verified by the simulation of the proposed structure.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.131-137
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• 2007

본 연구에서는 RLS(Rescursive Least Square) 추정 알고리즘을 이용하여 정전용량형 센서를 사용한 원격 RF 센서 시스템을 구현하고자 한다. IC 칩 형태의 원격 RF 센서 시스템이 가지는 구성의 복잡성 그리고 전력소모 문제를 해결하기 위해 보다 간단한 유도결합모델이 제안된다. 원격 RF 시스템은 페이저법을 이용하여 수학적으로 모델링되며, 모델기반의 RLS 알고리즘을 적용하기위해 시스템의 파라메타를 재배열한다. 오차 제곱합의 수렴특성을 가진 RLS 알고리즘을 이용하여 정전용량 파라메타를 추정한다. 실제 위상차를 측정하기 위해 Exclusive OR를 이용한 위상차 감지 장치를 제안한다. 센서로는 각종 환경 측정-습도, 압력 등-에 실제 활용되고 있는 정전용량형 센서를 채택한다. 잡음을 내포한 측정 데이터에 대한 추정 성능을 확인함으로써 그 유효성을 검증하고자 한다.

• The Journal of the Acoustical Society of Korea
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• v.12 no.1E
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• pp.56-64
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• 1993

본 논문은 공간적으로 변하는 스펙트럼을 추정하는 새로운 적응 방법을 제안한다. 제안한 방법에서는 오래된 upstream의 데이터를 망각함으로서 신호의 nonstationarity를 고려해주는 시변망각인자의 개념을 recursive least square(RLS) 알고리즘에 도입하였으며, 관심이 있는 공간영역에서 탐사침을 천천히 움직여 얻은 하나의 데이터 군으로부터 downstream 스펙트럼을 추정하였다. 제시한 방법의 실현 가능성은 실제 실험(wind tunnel 이용)을 통해서 얻은 공간적으로 변하는 nonstatonary 신호의 스펙트럼을 추정하는 과정에서 입증되며 또한 기존의 방법들과 비교함으로서 그 우수성을 보인다.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.56-58
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• 2004

In this paper, we propose an adaptive beamforming algorithm for array antenna. The proposed beamforming algorithm is based on EDS (Euclidean Direction Search) algorithm. Generally LMS algorithm has a much slower rate of convergence, but its low computational complexity and robustness make it a representative method of adaptive beamforming. Although the RLS algorithm is known for its fast convergence to the optimal Wiener solution, it still suffers from high computational complexity and poor performance. The proposed EDS algorithm has a rapid convergence better than LMS algorithm, and has a computational more simple complexity than RLS algorithm. In this paper we compared the efficiency of the EDS algorithm with a standard LMS algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.893-898
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• 2005

Due to the merits that only a small amount of computation is needed for solutions and stochastic policies can be handled explicitly, the actor-critic algorithm, which is a class of reinforcement learning methods, has recently attracted a lot of interests in the area of artificial intelligence. The actor-critic network composes of tile actor network for selecting control inputs and the critic network for estimating value functions, and in its training stage, the actor and critic networks take the strategy, of changing their parameters adaptively in order to select excellent control inputs and yield accurate approximation for value functions as fast as possible. In this paper, we consider a new actor-critic algorithm employing an RLS(Recursive Least Square) method for critic learning, and policy gradients for actor learning. The applicability of the considered algorithm is illustrated with experiments on the two linked robot arm.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.785-787
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• 1999

In this paper, recursive least square algorithm is presented to estimate the parameters of step motor under low-speed operation. Parameter estimation is important for compensating the input current by calculating the ratio of the motor torque constant and detent torque constant that causes torque-ripple in low-speed applications. On-line parameter estimation process is a preliminary procedure to apply step motor to adaptive control. Computer simulation shows that the estimated parameters converge in finite time.

• Proceedings of the IEEK Conference
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• 2002.06a
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• pp.61-64
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• 2002

In this paper, various equalizers are considered to improve the performance of Home Phoneline Networking Alliance (HomePNA) 2.0 system under dispersive channel with intersymbol interference. We evaluate and compare the performances of Recursive Least Squares (RLS) and Least Mean Squares (LMS) adaptation algorithms. Computer simulations show that the equalizers utilizing tile RLS algorithm outperforms the LMS algorithm, especially for the system of high symbol rate and complex constellation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.6
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• pp.1447-1452
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• 1996

In this papre, a complex fuzzy adaptive decision feedback equalizer using the RLS algorithm is proposed. The proposed equalizer is based on the complex fuzzy adaptive equalizer. The 'IF'-part of the complex fuzzy adaptive decision feedback equalizer has membership functions which are characterized by the sate of decision feedback. The role of decision feedback is to reduce the computational complexity. Computer simulation shows that the proposed equalizer not only reduces the computational complexity but also improves the performance compared with the conventional complex fuzzy adaptive equalizers under the assumption of perfect knowledge of the linear and nonlinear channels. The effects of error propagation due to wrong decision feedback is also shown.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1680-1681
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• 2007

This paper deals with RLS algorithm using Newton-Raphson method based adaptive forgetting factor for a passive telemetry RF sensor system in order to estimate the time variant parameter to be included in RF sensor model.