• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.10a
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• pp.235-240
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• 2002

This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network, and back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.3
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• pp.629-635
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• 2017

In this paper, we proposed a nonlinear synthesis filter for noise reduction to reduce the effects of Gaussian noise and impulse noise. When the centralization of the local mask is judged to be Gaussian noise by the noise judgment, the weight value of the weight filter are applied differently according to the spatial weight filter and the pixel change by using the sample variance in the local mask. And if it is determined as the impulse noise, we proposed an algorithm that applies different weights of local histogram weight filter and standard median filter according to noise density of mask. In order to evaluate the performance of the proposed filter algorithm, we used PSNR(peak signal to noise ratio) and compared existing methods and proposed filter algorithm in the mixed noise environment with Gaussian noise, impulsive noise, and two noises mixed.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1530-1533
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• 2005

In this paper, we design a Linear Quadratic Gaussian controller for the active suspension. We can improve the inherent suspension problem, trade-off between the ride quality and the suspension travel by selecting appropriate weights in the LQ-objective function. Because any definite rules for selecting weights do not exist, we use an optimization-algorithm, Evolution Strategy (ES) to find the proper control gains for selected frequencies, which have major effects on the vibrations of the vehicle's state variables. The frequencies and proper control gains are used for the neural network data. During a vehicle running, the trained on-line neural network is activated and provides the proper gains for non-trained frequencies. For the full-state feedback control, Kalman filter observes the full states and Fourier transform is used to detect the frequency of the road.

• Journal of Welding and Joining
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• v.31 no.4
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• pp.23-27
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• 2013

Laser heat source was used for automotive interior and exterior parts to reduce weights. Typically, 900's nm wavelength of laser has been widely used for polymer joining, however, the transmittance of the laser beam thorough clear polymers such as PMMA or PC has been an issue to overcome. To solve this issue, 1,940nm laser was applied on the clear polymer for the better absorption and 900nm laser beam was used for main laser for the joining. Conventional Gaussian or Elliptical heat source approximation has limitation in polymer which had deeper skin depth where major laser beam absorbs. To accurately simulate the physical laser beam absorption and joining optical properties were experimentally measured for the computer FEM simulation. The simulation results showed close correlation between theoretical and experimental results. The developed laser process is expected to increase productivity and gap closing which can cause failure of joining in laser material processing.

• Journal of the Korean Mathematical Society
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• v.56 no.2
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• pp.523-537
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• 2019

We estimate the essential norms of Volterra-type integral operators $V_g$ and $I_g$, and multiplication operators $M_g$ with holomorphic symbols g on a large class of generalized Fock spaces on the complex plane ${\mathbb{C}}$. The weights defining these spaces are radial and subjected to a mild smoothness conditions. In addition, we assume that the weights decay faster than the classical Gaussian weight. Our main result estimates the essential norms of $V_g$ in terms of an asymptotic upper bound of a quantity involving the inducing symbol g and the weight function, while the essential norms of $M_g$ and $I_g$ are shown to be comparable to their operator norms. As a means to prove our main results, we first characterized the compact composition operators acting on the spaces which is interest of its own.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.5
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• pp.38-43
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• 1996

Windowing routines have as their purpose the reduction of the sidelobes of a spectral output of the FFT or DFT routines. Windowing routines accomplish this by forcing the beginning and end of any sequence to approach each other in value. Since they must work with any sequence they force the beginning and ending samples near zero. To make up for this reduction in power, windowing routines give extra weight to the values near the middle of the sequence. The difference between windows is the way in which they transition from the low weights near the edges to the higher weights neqr the middle of the sequence. Signal-to-noise ratio(SNR) 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. Thus, the windowing operation improved the SNR of the noisy signal. This paper shows a performance estimation of windowing on a single tone with added Gaussian noise and uniform noise.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.2
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• pp.259-264
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• 2017

Birth weight of a new born baby provides very important information in evaluating many clinical issues such as fetal growth restriction. This paper analyzes birth weight data of babies born in Korea from 2011 to 2013, and it shows that there is a biologically implausible distribution of birth weights in the data. This implies that some errors may be generated in the data collection process. In particular, this paper analyzes the relationship between gestational period and birth weight, and it is shown that the birth weight data mostly of gestational periods from 28 to 32 weeks have noticeable errors. Therefore, this paper employs the finite Gaussian mixture model to classify the collected data points into two classes: non-corrupted and corrupted. After the classification the paper removes data points that have been predicted to be corrupted. This adjustment scheme provides more natural and medically plausible percentile values of birth weights for all the gestational periods.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.11
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• pp.136-141
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• 1994

In this paper, we implemented an opto-electronical signal processing system for the edge detection using the diffusion neural network. The diffusion neural network performs a Gaussian and DOG operation efficiently by the diffusion process. The diffusion neural network is more efficient than the LOG masking method in hardware implementation because it has a few connections and the connection weights are fixed-valued. We implemented a diffusion neural network using the characteristics of the light intensity distribution function which is similar to the Gaussian function. We have shown that the system can detect the edge of an image exactly through the experimental results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.7
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• pp.1393-1398
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• 2004

Image is degraded by several causes such as the process of acquisition, storage and transmission. To restore those images, many researches have been continued. Centrally methods to restore degraded image by AWGN(additive white gaussian noise) a.e mean filter and wiener filter. Especially, mean filter is superior in noise reduction of area that is a small change of luminosity. But mean filter brings about the effect smoothing edge components of the image, because it does'nt consider characteristics of the image. So in this paper we propose an image restoration method compounding respective images adding established weights, after filtering with mean filter and powerful wiener filter in both improvement of contrast and preservation of edge components.

• The KIPS Transactions:PartC
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• v.12C no.7 s.103
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• pp.1025-1030
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• 2005

Cooperative communications among users in multiple access wireless environments is an efficient way to obtain the powerful benefits of multi-antenna systems without the demand for physical arrays. This paper proposes a solution to optimize the weights of partnering users' signals for the minimum error probability at the output of maximum likelihood (ML) detector under the transmit power constraints by taking advantage of channel state information (CSI) feedback from the receiver to the transmitter. Simulation programs are also established to evaluate the performance of the system under flat Rayleigh fading channel plus AWGN (Additive White Gaussian Noise).