• Title/Summary/Keyword: Noise estimation

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Sound Reduction of the high-speed railroad noise by the deck plate of the Bridge (고속철도에서 교량상판의 소음저감효과)

  • 김준엽;나희승
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2001.11a
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    • pp.139-144
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    • 2001
  • Railroad noise is one of the main causes of environmental impact. Whenever a new railroad line is planned or a housing project near an existing railroad is proposed, an estimate of the relevant noise levels is usually required. For this, it is necessary to quantify those parameters that affect the railroad noise. This paper deals with an estimation of railroad noise by the barrier and deck plate of the bridge.

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Appropriate Choice of Window Function for Noise Reduction (잡음 감소를 위한 창 함수의 선택에 관한 연구)

  • 백문열
    • Journal of the Korean Society of Safety
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    • v.12 no.4
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    • pp.3-8
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    • 1997
  • This paper shows a performance estimation of windowing a single tone with added Gaussian noise and uniform noise. Signal-to-noise ratio can be determined by the ratio of the output noisy signal variance to the input noisy signal variance of a window. Standard deviation of noise is reduced by windowing Signal-to-noise ratio of the noisy signal is reduced by the windowing operation. Thus, performance of window function can be determined by this filtering operation that improved the signal-to-noise ratio.

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Parameter Estimation of Dynamic System Based on UKF (UKF 기반한 동역학 시스템 파라미터의 추정)

  • Seung, Ji-Hoon;Chong, Kil-To
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.13 no.2
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    • pp.772-778
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    • 2012
  • In this paper, the states and the parameters in the dynamic system are simultaneously estimated by applying the UKF(Unscented Kalman Filter), which is widely used for estimating the state of non-linear systems. Estimating the parameter is very important in various fields, such as system control, modeling, analysis of performance, and prediction. Most of the dynamic systems which are dealt with in engineering have non-linearity as well as some noise. Therefore, the parameter estimation is difficult. This paper estimates the states and the parameters applying to the UKF, which is a non-linear filter and has strong noise. The augmented equation is used by including the addition of the parameter factors to the original state equation of the system. Moreover, it is simulated by applying to a 2-DOF(Degree of Freedom) dynamic system composed of the pendulum and the slide. The measurement noise of the dynamic equation is assumed to be a Gaussian distribution. As the simulation results show, the proposed parameter estimation performs better than the LSM(Least Square Method). Furthermore, the estimation errors and convergence time are within three percent and 0.1 second, respectively. Consequentially, the UKF is able to estimate the system states and the parameters for the system, despite having measurement data with noise.

DOA Estimation of Multiple Signal and Adaptive Beam-forming for Mobile Communication Environments (이동통신 환경에서 다중신호의 DOA 추정과 적응 빔성형)

  • Yang, Doo-Yeong;Lee, Min-Soo
    • The Journal of the Korea Contents Association
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    • v.10 no.12
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    • pp.34-42
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    • 2010
  • The DOA(direction of arrival), which is based on parametric and nonparametric estimation algorithm, and adaptive beamforming algorithm for mobile communication environments are researched and analyzed. In parametric estimation algorithm, eigenvalues of the signal component and the noise component are obtained from correlation matrix of received signal by array antenna and power spectrum of the received signal is discriminated from them. Otherwise, in nonparametric estimation algorithm, we minimize a regularized objective function for finding a estimate of the signal energy as a function of angle, using nonquadratic norm which leads to supper resolution and noise suppression. And then, DOA is estimated by the signal and noise spatial steering vector, and adaptive beam-forming pattern is improved by weight vectors obtained from the spatial vector. Therefore, the improved directional estimation algorithm with regularizing sparsity constraints offers super-resolution and noise suppression compared to other algorithms.

IMBE Model Based SNR Estimation of Continuous Speech Signals (연속음성신호에서 IMBE 모델을 이용한 SNR 추정 연구)

  • Park, Hyung-Woo;Bae, Myung-Jin
    • The Journal of the Acoustical Society of Korea
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    • v.29 no.2
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    • pp.148-153
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    • 2010
  • In speech signal processing, speech signal corrupted by noise should be enhanced to improve quality. Usually noise estimation methods need flexibility for variable environment. Noise profile is renewed on silence region to avoid effects of speech properties. So we have to preprocess finding voice region before noise estimation. However, if received signal does not have silence region, we cannot apply that method. In this paper, we proposed SNR estimation method for continuous speech signal. A Speech signal consists of Voice and Unvoiced Band in The MBE excitation model. And the energy of speech signal is mostly distributed on voiced region, so we can estimate SNR by the ratio of voiced region energy to unvoiced. We use the IMBE vocoder for the Voice or Unvoice band of segmented speech signal. Continuously we calculate the segmented SNR using that information and the energy of each band. And we estimate the SNR of continuous speech signal.

Characteristics of a direct system parameter estimation method (시스템 매개변수 직접추정법의 특성)

  • Ju, Young-Ho;Jo, Gwang-Hwan;Lee, Gun-Myung
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.21 no.9
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    • pp.1480-1490
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    • 1997
  • A method by which the system parameter matrices can be estimated from measured time data of excitation force and acceleration has been studied. The acceleration data are integrated numerically to obtain the velocities and displacements, and the systm parameters are estimated from these data by solving equations of motion. The characteristics of the method have been investigated through its application to simulated data of 1 DOF and 2 DOF systems and experimental data measured from a simple structure. It was found that the method is very sensitive to measurement noise and the accuracy of the estimated parameters can be improved by averaging the repeatedly measured data and removing the noise. One of the main advantages of the parameter estimation method is that no a priori information about the system under test is required. The method can be easily extended to non-linear parameter estimation.

SLNR-based Precoder Design in Multiuser Interference Channel with Channel Estimation Error

  • Seo, Bangwon
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.1
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    • pp.40-52
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    • 2020
  • In this paper, we consider a precoder design problem for multiuser interference channel. Most of the conventional schemes for precoder design utilize a signal-to-interference-plus-noise ratio (SINR) as a cost function. However, since the SINR metric of a desired transmitter-receiver pair is a function of precoding vectors of all transmitters in the multiuser interference channel, an analytic closed-form solution is not available for the precoding vector of a desired transmitter that maximizes the SINR metric. To eliminate coupling between the precoding vectors of all transmitters and to find a closed-form solution for the precoding vector of the desired transmitter, we use a signal-to-leakage-plus-noise ratio (SLNR) instead as a cost function because the SLNR at a transmitter is a function of the precoding vector of the desired transmitter only. In addition, channel estimation errors for undesired links are considered when designing the precoding vector because they are inevitable in a multiuser interference channel. In this case, we propose a design scheme for the precoding vector that is robust to the channel estimation error. In the proposed scheme, the precoding vector is designed to maximize the worst-case SLNR. Through computer simulation, we show that the proposed scheme has better performance than the conventional scheme in terms of SLNR, SINR, and sum rate of all users.

Prediction of Total Acoustic Radiation Power of the Submerged Circular Cylindrical Structures (수중 원통형 구조물의 총 음향방사파워 예측)

  • Han, Seungjin;Lee, Jongju;Kang, Myunghwan
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.24 no.11
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    • pp.876-882
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    • 2014
  • This study investigates an efficient method to estimate the total acoustic radiation power of submerged circular cylindrical structures. Since the acoustic radiation power of submerged vehicles can be changed during the operation, the estimation for its monitoring onboard is required to accomplish the missions. The total acoustic radiation power is estimated using the measured velocity and the calculated radiation efficiency of the surface which consists of submerged rectangular plate elements. Experiments are carried out to validate the estimation approach. Comparisons of the estimation results with the measurements show that they are in a good agreement for the mid-high frequency range and match well for the cases of different excitation locations which correspond to the different operation modes of underwater vehicles as well. Therefore, this estimation method can be applied effectively to the development of the radiated noise monitoring-system.

Time delay estimation by iterative Wiener filter based recursive total least squares algorithm (반복형 위너 필터 방법에 기반한 재귀적 완전 최소 제곱 방법을 사용한 시간 지연 추정 알고리즘)

  • Lim, Jun-Seok
    • The Journal of the Acoustical Society of Korea
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    • v.40 no.5
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    • pp.452-459
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    • 2021
  • Estimating the mutual time delay between two acoustic sensors is used in various fields such as tracking and estimating the location of a target in room acoustics and sonar. In the time delay estimation methods, there are a non-parametric method, such as Generalized Cross Correlation (GCC), and a parametric method based on system identification. In this paper, we propose a time delay estimation method based on the parametric method. In particular, we propose a method that considers the noise in each receiving acoustic sensor. Simulation confirms that the proposed algorithm is superior to the existing generalized cross-correlation and adaptive eigenvalue analysis methods in white noise and reverberation environments.

Selective Extended Kalman Filter based Attitude Estimation (선택적 확장 칼만 필터 방식의 자세 추정)

  • Yun, In-Yong;Shim, Jae-Ryong;Kim, Joong-Kyu
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.10a
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    • pp.973-975
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    • 2016
  • In this paper, we propose a selective extended Kalman filter based accurate pose estimation of the rigid body using a sensor fusion method. The pose of a rigid body can be estimated roughly by the Gauss-Newton method using the acceleration data and geomagnetic data, which can be refined with vision information and the gyro sensor information. However strong external interference noise makes the rough pose estimation difficult. In this paper, according to the measurement level of the external interference noise, the extended Kalman filter selectively uses mostly vision and gyro sensor information to increase the estimation credibility under strong interference noise environment.

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