• Korean Journal of Mathematics
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• v.24 no.3
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• pp.447-467
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• 2016

We prove the existence of random attractors for the continuous random dynamical systems generated by stochastic damped plate equations with linear memory and additive white noise when the nonlinearity has a critically growing exponent.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.1
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• pp.27-35
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• 2022

In this paper we propose white noise adding method to prevent missclassification of deep learning system by adversarial attacks. The proposed method is that adding white noise to input image that is benign or adversarial example. The experimental results are showing that the proposed method is robustness to 3 adversarial attacks such as FGSM attack, BIN attack and CW attack. The recognition accuracies of Resnet model with 18, 34, 50 and 101 layers are enhanced when white noise is added to test data set while it does not affect to classification of benign test dataset. The proposed model is applicable to defense to adversarial attacks and replace to time- consuming and high expensive defense method against adversarial attacks such as adversarial training method and deep learning replacing method.

• Advances in nano research
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• v.5 no.1
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• pp.13-25
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• 2017

We examine the total optical dielectric function (TODF) of impurity doped GaAs quantum dot (QD) from the viewpoint of anisotropy, position-dependent effective mass (PDEM) and position dependent dielectric screening function (PDDSF), both in presence and absence of noise. The dopant impurity potential is Gaussian in nature and noise employed is Gaussian white noise that has been applied to the doped system via two different modes; additive and multiplicative. A change from fixed effective mass and fixed dielectric constant to those which depend on the dopant coordinate manifestly affects TODF. Presence of noise and also its mode of application bring about more rich subtlety in the observed TODF profiles. The findings indicate promising scope of harnessing the TODF of doped QD systems through expedient control of site of dopant incorporation and application of noise in desired mode.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.5 no.1
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• pp.34-39
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• 1980

This paper discribes a effect of Radio signals in Noise and Interference for the Communication systems and Generation of diffusion Noise from the Solid state Devices, and in Jection it to the Radio Reciving systems for probability of Signal Detection. The error performance depends on level of the Noise spectral density by Random processes between average signal energy. This experimental result are given by the performance of the correlation receiver for detecting Completely known signals in additive white Gaussian Noise.

• Journal of Korean Ophthalmic Optics Society
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• v.17 no.2
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• pp.203-207
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• 2012

Purpose: Electroretinogram(ERG) signal noise as well as conducting other bio-signal measurement were generated. It was intened to enhance the accuracy of retinal-related diagnosis with removing signal noise. Methods: Sampling signal was made with generating 60 Hz noise and white noise. The noise were removed using wavelet transforms and bandpass filter. De-noising frequency was compared with Fourier transform spectrum. Removed noises were compared numerically using SNR(signal to noise ratio). Results: The result compared Fourier transform spectrum was showed that 60 Hz noise removed completely and most of white noise was removed by wavelet transforms. 60 Hz and the white noise remained using bandpass filters. The result compared SNR showed that wavelet transforms was 22.8638 and bandpass filter was 4.0961. Conclusions: Wavelet transform showed less signal distortion in removing noise. ERG signal is expected to improve the accuracy of retinal-related diagnosis.

• Nuclear Engineering and Technology
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• v.56 no.2
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• pp.715-727
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• 2024

During fast neutron imaging, besides the dark current noise and readout noise of the CCD camera, the main noise in fast neutron imaging comes from high-energy gamma rays generated by neutron nuclear reactions in and around the experimental setup. These high-energy gamma rays result in the presence of high-density gamma white spots (GWS) in the fast neutron image. Due to the microscopic quantum characteristics of the neutron beam itself and environmental scattering effects, fast neutron images typically exhibit a mixture of Gaussian noise. Existing denoising methods in neutron images are difficult to handle when dealing with a mixture of GWS and Gaussian noise. Herein we put forward a deep learning approach based on the Swin Transformer UNet (SUNet) model to remove high-density GWS-Gaussian mixture noise from fast neutron images. The improved denoising model utilizes a customized loss function for training, which combines perceptual loss and mean squared error loss to avoid grid-like artifacts caused by using a single perceptual loss. To address the high cost of acquiring real fast neutron images, this study introduces Monte Carlo method to simulate noise data with GWS characteristics by computing the interaction between gamma rays and sensors based on the principle of GWS generation. Ultimately, the experimental scenarios involving simulated neutron noise images and real fast neutron images demonstrate that the proposed method not only improves the quality and signal-to-noise ratio of fast neutron images but also preserves the details of the original images during denoising.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.4
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• pp.775-780
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• 2013

This paper proposes a speaker-dependent speech recognition algorithm which can classify the gender for male and female speakers in white noise and car noise, using a neural network. The proposed speech recognition algorithm is trained by the neural network to recognize the gender for male and female speakers, using LPC (Linear Predictive Coding) cepstrum coefficients. In the experiment results, the maximal improvement of total speech recognition rate is 96% for white noise and 88% for car noise, respectively, after trained a total of six neural networks. Finally, the proposed speech recognition algorithm is compared with the results of a conventional speech recognition algorithm in the background noisy environment.

• Journal of the Korean Mathematical Society
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• v.35 no.3
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• pp.559-574
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• 1998

Let the Gel'fand triple (E)$_{\beta}$/ ⊂ ( $L^2$) ⊂ (E)＊$_{\beta}$/ be the framework of white noise distribution theory constructed by Kon-dratiev and Streit. A new class of continuous multiplicative products on (E)$_{\beta}$/ is introduced and associated continuous derivations on (E)$_{\beta}$/ are discussed. Algebraic characterizations of first order differential operators on (E)$_{\beta}$/ are proved. Some applications are also discussed. $\beta$/ are proved. Some applications are also discussed.

• Journal of the Korean Statistical Society
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• v.35 no.4
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• pp.453-458
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• 2006

It is well known fact for the iid data that the limiting standard errors of sample autocorrelations are all unity for all time lags and they are asymptotically independent for different lags (Brockwell and Davis, 1991). It is also usual practice in time series modeling that this fact continues to be valid for white noise series which is a sequence of uncorrelated random variables. This paper contradicts this usual practice for white noise. We consider a sequence of martingale differences which belongs to white noise time series and derive exact joint asymptotic distributions of sample autocorrelations. Some implications of the result are illustrated for conditionally heteroscedastic time series.

• Journal of Korean Association for Spatial Structures
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• v.2 no.4 s.6
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• pp.29-36
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• 2002

The responses of composite laminated beams modeled with finite element and excited by stochastic loading are studied. The cantilevered laminated beam having a 5 ply configuration is considered. The beam is 1m long, 0.1m wide, and 0.02m thick, yielding a length to thickness ratio of L/h=50. The laminated beams was assumed to be made of Born Epoxy. The four nodes at the free end of the cantilever were loaded with identical zero-mean white noise excitations. Stress and failure analysis loaded with identical zero-mean white noise excitations is carried out. Along with the obtained results, comparison and discussion are presented for the cases of symmetric-ply, antisymmetric-ply, angle-ply, and cross-ply laminated beams.