• 제목/요약/키워드: adaptive gain control

검색결과 267건 처리시간 0.029초

순시 이득을 이용한 적응잡음제거기 구현 (Implementation of Adaptive Noise Canceller with Instantaneous Gain)

  • 이재균;김춘식;이채욱
    • 한국통신학회논문지
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    • 제34권8C호
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    • pp.756-763
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    • 2009
  • LMS알고리즘은 잡음이 섞인 신호로부터 원 신호를 복원하는데 자주 사용된다. 이 LMS알고리즘의 주된 결점은 음성 신호 파워에 따라 선형적으로 EMSE(Excess Mean Square Error)가 증가한다. 그 결과 최적의 값에서 큰 EMSE 때문에 성능의 효율성이 떨어진다. 이러한 결점은 적은 스텝사이즈를 선택함으로서 해결 할 수 있지만, 수렴율이 늦어지는 단점이 있어, 빠른 수렴율과 낮은 EMSE를 동시에 만족할 수 있는 값이 필요하다. 본 논문에서는 IGC(lnstantaneous Gain Control) 알고리즘을 음성신호가 존재하는 경우에서 제안한다. 시뮬레이션은 음성신호와 가우시안 잡음을 이용하여 수행하였고, 수렴율, 잡음제거, 그리고 EMSE에서 LMS알고리즘보다 IGC알고리즘이 우수하다는 것을 보인다.

흉부 심음을 기반한 u-헬스케어용 RF-Tag설계 (Design of u-Healthcare RF-Tag Based on Heart Sounds of Chest)

  • 이주원;이병로
    • 한국정보통신학회논문지
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    • 제13권4호
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    • pp.753-758
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    • 2009
  • 본 논문은 유비쿼터스 헬스케어 시스템을 위하여 생체 정보 단말기 개발에 있어 심음 신호를 기반한 RF-Tag의 하드웨어 구조와 신호처리 방법을 제안한 것이다. 본 연구에서의 RF-Tag는 체온 센서와 심음 검출을 위한 다이나믹 마이크로폰, 측정된 헬스정보를 전송하기 위한 블루투스 통신, 적응 이득제어기로 이루어진 심박 주기 검출 알고리즘으로 구성되어 있다. RF-Tag의 성능 분석을 위해 잡음환경에서 실험하였으며, 그 결과 우수한 성능을 보였다. 본 연구에서 제안한 방법을 u-헬스케어 단말기에 적용한다면, 모바일 환경에서도 실시간적으로 정확한 헬스 정보를 얻을 수 있을 것이라 사료된다.

태양광 시스템을 위한 가변 조정계수 기반의 적응형 MPPT 제어 기법 (An Adaptive Maximum Power Point Tracking Scheme Based on a Variable Scaling Factor for Photovoltaic Systems)

  • 이귀준;김래영;현동석;임춘호;김우철
    • 전력전자학회논문지
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    • 제17권5호
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    • pp.423-430
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    • 2012
  • An adaptive maximum power point tracking (MPPT) scheme employing a variable scaling factor is presented. A MPPT control loop was constructed analytically and the magnitude variation in the MPPT loop gain according to the operating point of the PV array was identified due to the nonlinear characteristics of the PV array output. To make the crossover frequency of the MPPT loop gain consistent, the variable scaling factor was determined using an approximate curve-fitted polynomial equation about linear expression of the error. Therefore, a desirable dynamic response and the stability of the MPPT scheme were maintained across the entire MPPT voltage range. The simulation and experimental results obtained from a 3 KW rated prototype demonstrated the effectiveness of the proposed MPPT scheme.

Noise Estimation based on Standard Deviation and Sigmoid Function Using a Posteriori Signal to Noise Ratio in Nonstationary Noisy Environments

  • Lee, Soo-Jeong;Kim, Soon-Hyob
    • International Journal of Control, Automation, and Systems
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    • 제6권6호
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    • pp.818-827
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    • 2008
  • In this paper, we propose a new noise estimation and reduction algorithm for stationary and nonstationary noisy environments. This approach uses an algorithm that classifies the speech and noise signal contributions in time-frequency bins. It relies on the ratio of the normalized standard deviation of the noisy power spectrum in time-frequency bins to its average. If the ratio is greater than an adaptive estimator, speech is considered to be present. The propose method uses an auto control parameter for an adaptive estimator to work well in highly nonstationary noisy environments. The auto control parameter is controlled by a linear function using a posteriori signal to noise ratio(SNR) according to the increase or the decrease of the noise level. The estimated clean speech power spectrum is obtained by a modified gain function and the updated noisy power spectrum of the time-frequency bin. This new algorithm has the advantages of much more simplicity and light computational load for estimating the stationary and nonstationary noise environments. The proposed algorithm is superior to conventional methods. To evaluate the algorithm's performance, we test it using the NOIZEUS database, and use the segment signal-to-noise ratio(SNR) and ITU-T P.835 as evaluation criteria.

로보트 운동을 위한 신경회로망 제어구조의 설계 (A Design of Neural Network Control Architecture for Robot Motion)

  • 이윤섭;구영모;조시형;우광방
    • 대한전기학회논문지
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    • 제41권4호
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    • pp.400-410
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    • 1992
  • This paper deals with a design of neural network control architectures for robot motion. Three types of control architectures are designed as follows : 1) a neural network control architecture which has the same characteristics as computed torque method 2) a neural network control architecture for compensating the control error on computed torque method with fixed feedback gain 3) neural network adaptive control architecture. Computer simulation of PUMA manipulator with 6 links is conducted for robot motion in order to examine the proposed neural network control architectures.

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위상 검출기 출력을 이용한 백플레인용 5Gbps CMOS 적응형 피드포워드 이퀄라이저 (5Gbps CMOS Adaptive Feed-Forward Equalizer Using Phase Detector Output for Backplane Applications)

  • 이기혁;성창경;최우영
    • 대한전자공학회논문지SD
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    • 제44권5호
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    • pp.50-57
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    • 2007
  • 0.13${\mu}m$ CMOS 공정을 이용하여 백플레인 응용 분야를 위한 5Gbps 고속 적응형 피드포워드 이퀄라이저를 설계하였다. 설계된 이퀄라이저는 클럭 복원 회로의 위상 검출기 출력을 이용하여 인접 심벌간의 간섭 정도를 판단하고 이퀄라이저의 보상 이득을 조절하는 피드백 회로를 갖는다. 이를 통해 여러 길이의 백플레인 채널 환경에 적합한 보상 이득을 제공하는 적응 동작을 한다.

적응형 바이어스 조절 회로와 2차 고조파 종단 회로를 이용한 고선형성 고효율 DMB CMOS 전력증폭기 (A Highly Linear and Efficient DMB CMOS Power Amplifier with Adaptive Bias Control and 2nd Harmonic Termination circuit)

  • 최재원;서철헌
    • 대한전자공학회논문지TC
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    • 제44권1호
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    • pp.32-37
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    • 2007
  • 고효율과 고선형성을 갖는 DMB CMOS 전력증폭기가 제안되어 있다. 이 논문에서는 0.13-um 표준 CMOS 공정이 적용되어졌고 제안된 전력증폭기의 모든 구성 소자는 출력 정합 회로망과 적응형 바이어스 조절 회로를 포함하여 하나의 칩속에 완전히 집적되어졌다. 효율과 선형성을 동시에 개선시키기 위하여 적응형 바이어스 조절 회로가 드레인 노드에 위치한 2차 고조파 종단 회로와 함께 적용되어졌다. 전력증폭기는 각각 16.64 dBm의 $P_{1dB}$, 38.31 %의 효율 (PAE), 그리고 24.64 dB의 출력 이득을 보였다. 3차 혼변조왜곡 (IMD3)과 5차 혼변조왜곡 (IMD5)은 각각 -24.122 dBc, -37.156 dBc 이다.

Robust NN Controller for Autonomous Diving Control of an AUV

  • Li, Ji-Hong;Lee, Pan-Mook
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.107-112
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    • 2003
  • In general, the dynamics of autonomous underwater vehicles(AUVs) are highly nonlinear and time-varying, and the hydrodynamic coefficients of vehicles are hard to estimate accurately because of the variations of these coefficients with different navigation conditions. For this reason, in this paper, the control gain function is assumed to be unknown and the exogenous input term is assumed to be unbounded, although it still satisfies certain restrict condition. And these two kinds of wild assumptions have been seldom handled simultaneously in one system because of the difficulty of stability analysis. Under the above two relaxed assumptions, a robust neural network control scheme is presented for autonomous diving control of an AUV, and can guarantee that all the signals in the closed-loop system are UUB (uniformly ultimately bounded). Some practical features of the proposed control law are also discussed.

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이동구간 예측제어 기법을 이용한 적응 제어기의 전기로 적용 (Application of adaptive controller using receding-horizon predictive control strategy to the electric furnace)

  • 김진환;허욱열
    • 제어로봇시스템학회논문지
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    • 제2권1호
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    • pp.60-66
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    • 1996
  • Model Based Predictive Control(MBPC) has been widely used in predictive control since 80's. GPC[1] which is the superset of many MBPC strategies a popular method, but GPC has some weakness, such as insufficient stability analysis, non-applicability to internally unstable systems. However, CRHPC[2] proposed in 1991 overcomes the above limitations. So we chose RHPC based on CRHPC for electric furnace control. An electric furnace which has nonlinear properties and large time delay is difficult to control by linear controller because it needs nearly perfect modelling and optimal gain in case of PID. As a result, those controls are very time-consuming. In this paper, we applied RHPC with equality constraint to electric furnace. The reults of experiments also include the case of RHPC with monotonic weighting improving the transient response and including unmodelled dynamics. So, This paper proved the practical aspect of RHPC for real processes.

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Nonlinear pH Control Using a Three Parameter Model

  • Lee, Jie-Tae;Park, Ho-Cheol
    • Transactions on Control, Automation and Systems Engineering
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    • 제2권2호
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    • pp.130-135
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    • 2000
  • A two parameter model of a single fictitious weak acid with unknown dissociation constant has been successfully applied to design a neutralization system for many multi-component acid streams. But there are some processes for which above two parameter model is not satisfactory due to poor approxmation of the nonlinearity of pH process. Here, for etter control of wide class of multi-component acid streams, a three parameter model of a strong acid and a weak acid with unknown dissociation constant is proposed. The model approximates effectively three types of largest gain variation nonlinearities. Based on this model a nonlinear pH control system is designed. Parameters can eeasily estimated since their combinations appear linearly in the model equations and nonlinear adaptive control system may also be constructed just as with the two parameter model.

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