• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1997.04a
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• pp.86-94
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• 1997

An investigation into the modal interaction of an autoparametric system under broad-band random excitation is made. The specific system examined is a spring-pendulum system with internal resonance, which is known to be a good model for a variety of engineering systems, including ship motions with nonlinear coupling between pitching and rolling motions. By means of the Gaussian closure method the dynamic moment equations explaining the random response of the system are reduced to a system of autonomous ordinanary differential equations of the first and second moments. In view of equilibrium solutions of this system and their stability we examine the system responses. The stabilizing effect of system damping is also examined.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.115-118
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• 2001

This paper presents dispersed-pulse and random codebook for CELP coder. This coder operates on speech frames of 20ms and generates an excitation vector by convoluting dispersion vectors with signed pulses in an algebraic codevector. The improvement of pulse-based fixed codebook is performed at a low bit rate. A high performance fixed-codebook consists of a partial algebraic codebook and a random codebook in unvoiced and stationary noise regions. The proposed CELP coder is quantized with 4kb/s and is compared with G.729 (Bkb/s CS-ACELP). Subjective testing shows better quality than reference coders under some background noise conditions

• JSTS:Journal of Semiconductor Technology and Science
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• v.14 no.4
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• pp.365-375
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• 2014

This paper proposes an abnormal V-shaped-error-free non-blind deconvolution technique featuring an adaptively segmented forward-problem based iterative deconvolution (ASDCN) process. Unlike the algebraic based inverse operations, this eliminates any operations of differential and division by zero to successfully circumvent the issue on the abnormal V-shaped error. This effectiveness has been demonstrated for the first time with applying to a real analysis for the effects of the Random Telegraph Noise (RTN) and/or Random Dopant Fluctuation (RDF) on the overall SRAM margin variations. It has been shown that the proposed ASDCN technique can reduce its relative errors of RTN deconvolution by $10^{13}$ to $10^{15}$ fold, which are good enough for avoiding the abnormal ringing errors in the RTN deconvolution process. This enables to suppress the cdf error of the convolution of the RTN with the RDF (i.e., fail-bit-count error) to $1/10^{10}$ error for the conventional algorithm.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.4
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• pp.216-225
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• 2013

This paper discusses the issues regarding an abnormal V-shaped error confronting algebraic-based deconvolution process. Deconvolution was applied to an analysis of the effects of the Random Telegraph Noise (RTN) and Random Dopant Fluctuation (RDF) on the overall SRAM margin variations. This paper proposes a technique to suppress the problematic phenomena in the algebraic-based RDF/RTN deconvolution process. The proposed technique can reduce its relative errors by $10^{10}$ to $10^{16}$ fold, which is a sufficient reduction for avoiding the abnormal ringing errors in the RTN deconvolution process. The proposed algebraic-based analyses allowed the following: (1) detection of the truncating point of the TD-MV distributions by the screening test, and (2) predicting the MV-shift-amount by the assisted circuit schemes needed to avoid the out of specs after shipment.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.11
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• pp.100-105
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• 2014

In this paper, Uninterruptible Power Supply(UPS) Inverter system using Carrier Frequency Modulated PWM (CFM-PWM) is proposed to reduced harmonics and electromagnetic noise. Power conversion of UPS system is executed by the ON-OFF operation of semiconductor switching devices. However, this switching operation causes the surge and EMI which deteriorate the reliability of the UPS system. This Problems improved by Random PWM switching method. The simulation results of the proposed system was compared with the system using conventional method using Matlab/Simulink. The results show that the output voltage and current harmonics of the proposed UPS system significantly decreased and spread into wide band area by the proposed Carrier Frequency Modulated PWM(CFM-PWM) method based on the Space Vector Modulation.

• Journal of the Korean Institute of Telematics and Electronics
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• v.12 no.3
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• pp.30-36
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• 1975

Distortions are analyzed and compared for two TDM channel expansion methods- periodic sample skipping and sampling frequency reduction. Signal is assumed to be stationary random signal with zero.mean. Channel noise and interference are not considered in the analysis. For speech signal, it is shown that the periodic sample skipping method could be a better choice under practical design constraints.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.747-750
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• 2004

After launching, spacecraft is exposed to extreme environments. So spacecraft should be tested after design/manufacture to verify whether components can be operated functionally. Acceleration transferred from launch vehicle to spacecraft produces quasi-static load, sine vibration and random vibration. Random vibration is also induced by acoustic vibrations transferred by surface of spacecraft. And shock vibration is produced when spacecraft is separated from launch vehicle. To verify operation of spacecraft under these launch environments, separation shock test, sine vibration test, acoustic vibration test and random vibration test should be performed. This paper describes these launch environment test requirements.

• Journal of the Korean Mathematical Society
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• v.59 no.2
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• pp.217-233
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• 2022

Although machine learning shows state-of-the-art performance in a variety of fields, it is short a theoretical understanding of how machine learning works. Recently, theoretical approaches are actively being studied, and there are results for one of them, margin and its distribution. In this paper, especially we focused on the role of margin in the perturbations of inputs and parameters. We show a generalization bound for two cases, a linear model for binary classification and neural networks for multi-classification, when the inputs have normal distributed random noises. The additional generalization term caused by random noises is related to margin and exponentially inversely proportional to the noise level for binary classification. And in neural networks, the additional generalization term depends on (input dimension) × (norms of input and weights). For these results, we used the PAC-Bayesian framework. This paper is considering random noises and margin together, and it will be helpful to a better understanding of model sensitivity and the construction of robust generalization.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.2
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• pp.185-190
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• 2016

A 70-${\AA}$ nanowire field-effect transistor (FET) for sub-10-nm CMOS technology is designed and simulated in order to investigate the impact of an oxide trap on random telegraph noise (RTN) in the device. It is observed that the drain current fluctuation (${\Delta}I_D/I_D$) increases up to a maximum of 78 % due to the single electron trapping. In addition, the effect of various trap positions on the RTN in the nanowire FET is thoroughly analyzed at various drain and gate voltages. As the drain voltage increases, the peak point for the ${\Delta}I_D/I_D$ shifts toward the source side. The distortion in the electron carrier density and the conduction band energy when the trap is filled with an electron at various positions in the device supports these results.

• Journal of Intelligence and Information Systems
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• v.13 no.3
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• pp.31-45
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• 2007

Large data handling is one of critical issues that the data mining community faces. This is particularly true for computationally intense tasks such as data clustering. Random sampling of instances is one possible means of achieving large data handling, but a pervasive problem with this approach is how to deal with the noise in the evaluation of the learning algorithm. This paper develops a new optimization based clustering approach using an algorithm specifically designed for noisy performance. Numerical results show this algorithm better than the other algorithms such as PAM and CLARA. Also with this algorithm substantial benefits can be achieved in terms of computational time without sacrificing solution quality using partial data.