• Title/Summary/Keyword: white-noise

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Stochastic Prediction of Rolling of Ships in Irregular Waves (불규칙 해상의 선박 횡요의 확률론적 예측)

  • Gwon, Sun-Hong;Kim, Dae-Ung
    • Journal of Ocean Engineering and Technology
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    • v.5 no.2
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    • pp.51-57
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    • 1991
  • 불규칙 해상에서 선박의 큰 횡요각의 예측이 중요한 과제로 대두 되고 있다. 본 논문에서는 통계적 해석에 의한 이의 예측 방법을 제시한다. 즉 주어진 비 선형 횡요운동 방정식으로 부터 배의 횡요각과 각속도의 결합 확률 밀도 함수를 구하는 방법을 도입하고 각종 계수들의 값의 변화에 따른 예측 결과를 다른 논문에서 제시한 시뮬레이션 결과와 비교하였다.

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A CLASS OF NONLINEAR STOCHASTIC DIFFERENTIAL EQUATIONS(SDES) WITH JUMPS DERIVED BY PARTICLE REPRESENTATIONS

  • KWON YOUNGMEE;KANG HYE-JEONG
    • Journal of the Korean Mathematical Society
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    • v.42 no.2
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    • pp.269-289
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    • 2005
  • An infinite system of stochastic differential equations (SDE)driven by Brownian motions and compensated Poisson random measures for the locations and weights of a collection of particles is considered. This is an analogue of the work by Kurtz and Xiong where compensated Poisson random measures are replaced by white noise. The particles interact through their weighted measure V, which is shown to be a solution of a stochastic differential equation. Also a limit theorem for system of SDE is proved when the corresponding Poisson random measures in SDE converge to white noise.

FINITE ELEMENT APPROXIMATIONS OF THE OPTIMAL CONTROL PROBLEMS FOR STOCHASTIC STOKES EQUATIONS

  • Choi, Youngmi;Kim, Soohyun;Lee, Hyung-Chun
    • Bulletin of the Korean Mathematical Society
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    • v.51 no.3
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    • pp.847-862
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    • 2014
  • Finite element approximation solutions of the optimal control problems for stochastic Stokes equations with the forcing term perturbed by white noise are considered. Error estimates are established for the fully coupled optimality system using Brezzi-Rappaz-Raviart theory. Numerical examples are also presented to examine our theoretical results.

Iterative Image Restoration Algorithm Using Power Spectral Density (전력밀도 스펙트럼을 이용한 반복적 영상 신호 복원 알고리즘)

  • 임영석;이문호
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.24 no.4
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    • pp.713-718
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    • 1987
  • In this paper, an iterative restoration algorithm from power spectral density with 1 bit sign information of real part of two dimensional Fourier transform of image corrupted by additive white Gaussian noise is proposed. This method is a modified version of image reconstruction algorithm from power spectral density. From the results of computer simulation with original 32 gray level imgae of 64x64 pixels, we can find that restorated image after each iteration converge to original image very fast, and SNR gain be at least 8[dB] after 10th iteration for corrupted image with additive white Gaussian noise.

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Ddenoising of a Positive Signal with White Gaussian Noise by Using Wavelet Transform

  • Koo, Ja-Yong
    • The Journal of the Acoustical Society of Korea
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    • v.17 no.1E
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    • pp.30-35
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    • 1998
  • Given a noisy sampled at equispaced points with white noise, we consider problems where the signal to be recovered is known to be positive; for example, images, chemical spectra or other measurements of intensities. Shrinking noisy wavelet coefficients via thresholding offers very attractive alternatives to existing methods of recovering signals from noisy data. In this paper, we propose a method of recovering the original signal from a corrupted noisy signal, guaranteeing the recovered signal positive. We first obtain wavelet coefficients by thresholding, and use a nonlinear optimization to find the denoised signal which must be positive. Numerical examples are used to illustrate the performance of the proposed algorithm.

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Prediction of Composition Ratio of DNA Solution from Measurement Data with White Noise Using Neural Network (잡음이 포함된 측정 자료에 대한 신경망의 DNA 용액 조성비 예측)

  • Gyeonghee Kang;Minji Kim;Hyomin Lee
    • Korean Chemical Engineering Research
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    • v.62 no.1
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    • pp.118-124
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    • 2024
  • A neural network is utilized for preprocessing of de-noizing in electrocardiogram signals, retinal images, seismic waves, etc. However, the de-noizing process could provoke increase of computational time and distortion of the original signals. In this study, we investigated a neural network architecture to analyze measurement data without additional de-noizing process. From the dynamical behaviors of DNA in aqueous solution, our neural network model aimed to predict the mole fraction of each DNA in the solution. By adding white noise to the dynamics data of DNA artificially, we investigated the effect of the noise to neural network's predictions. As a result, our model was able to predict the DNA mole fraction with an error of O(0.01) when signal-to-noise ratio was O(1). This work can be applied as a efficient artificial intelligence methodology for analyzing DNA related to genetic disease or cancer cells which would be sensitive to background measuring noise.

Direction Information Concerned Algorithm for Removing Gaussian Noise in Images

  • Gao, Yinyu;Kim, Nam-Ho
    • Journal of information and communication convergence engineering
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    • v.9 no.6
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    • pp.758-762
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    • 2011
  • In this paper an efficient algorithm is proposed to remove additive white Gaussian noise(AWGN) with edge preservation. A function is used to separate the filtering mask to two sets according to the direction information. Then, we calculate the mean and standard deviation of the pixels in each set. In order to preserve the details, we also compare standard deviations between the two sets to find out smaller one. Corrupted pixel is replaced by the mean of the filtering window's median value and the smaller set's mean value that the rate of change is faster than the other one. Experiment results show that the proposed algorithm outperforms with significant improvement in image quality than the conventional algorithms. The proposed method removes the Gaussian noise very effectively.

Active Vibration Control of Flexible Plate using Piezo Ceramic (피에조 세라믹을 이용한 유연한 평판의 능동진동제어)

  • 박수홍;김홍섭;홍진석;오재응
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 1997.04a
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    • pp.434-439
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    • 1997
  • This paper presents the active control of a flexible plate vibration. The plate was excited by white noise point force and the control was performed by one or two piezo ceramic actuator bonded to the surface of the plate. An adaptive controller based on filtered-x or multiple filtered-x LMS algorithm was used and the controller was defined by minimizing the square of the response of error sensor. In the experiment, PZT sensor was used as an error sensor while white noise was applied as a disturbance. In the case of multiple channel control, more than 22 dB of vibration reduction was achieved. Results indicate that the vibration of a flexible plate could be controlled effectively when the piezo ceramic actuator was used with multiple filtered-x LMS algorithm.

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A Study on the Modified Mean Filter Algorithm for Removal AWGN (AWGN 제거를 위한 변형된 평균 필터 알고리즘에 관한 연구)

  • Long, Xu;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2014.05a
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    • pp.792-794
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    • 2014
  • In the modern society where the communication technology has rapidly developed, image devices such as digital display, camera, etc., forms the center. However, during the transmission of image data, storing, and obtaining, a noise is added to the image due to various reasons and degrades the quality of the image. In this paper, an average filter algorithm modified in order to ease the effect of AWGN(additive white Gaussian noise) being added to the image was proposed. Also compare existing methods through the using PSNR.

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