• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.505-508
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• 2005

This paper presents the high speed noise reduction processing system using the MDFT on the frequency domain. The proposed system use the linear prediction coefficients of the AR method based on the SLMS(sign least mean square). The signals with a random noise tracking per-formance are examined through computer simu-lations. It is confirmed that the high speed adaptive noise reduction processing system is realized by the SLMS algorithms with rapid convergence on the FD(frequency domain).

• International Journal of Aeronautical and Space Sciences
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• v.2 no.2
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• pp.19-27
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• 2001

This research attempts to find an active control strategy which reduces acoustic power and acoustic energy in lightly-damped enclosed sound field such as a vehicle compartment or an operating room of heavy industrial machinery. An active control strategy, which takes into consideration of the acoustic radiation power of the source as a cost function, is formulated and examined to find capability of reducing noise. An adaptive filtering algorithm for sound power control is suggested and implemented to control lightly-damped sound field. To verify the method, sound power based active noise control algorithm was implemented on a rectangular box with lightly-damped wall, and popular acoustic energy based control with modal coupling reduction was performed to compare the noise reduction performance. It was shown that a total sound power based strategy provides a practical mean for global noise reduction for lightly damped sound field.

• 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.

• Journal of Communications and Networks
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• v.14 no.3
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• pp.273-279
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• 2012

In this paper, we propose an iterative interstream interference cancellation technique for system with frequency selective multiple-input multiple-output (MIMO) channel. Our method is inspired by the fact that the cancellation of the interstream interference can be regarded as a reduction in the magnitude of the interfering channel. We show that, as iteration goes on, the channel experienced by the equalizer gets close to the single input multiple output (SIMO) channel and, therefore, the proposed SIMO-like equalizer achieves improved equalization performance in terms of normalized mean square error. From simulations on downlink communications of $2{\times}2$ MIMO systems in high speed packet access universal mobile telecommunications system standard, we show that the proposed method provides substantial performance gain over the conventional receiver algorithms.

• Journal of the Korea Computer Industry Society
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• v.8 no.2
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• pp.81-88
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• 2007

The dissertation which it sees in communication the noise . it will be able to occur confirms the effect which it gives to this videotex and it the Nagao filter it will be able to reduce a noise in one original videotex which is possible and nearly it analyzes the Nagao filter of existing compared to compared to a different divided territory and for the efficiency which restores it sets the filter which is the possibility of reducing the MSE (Mean Square Error) it proposes simulation and the result it leads and the superiority of this method it confirms.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.1
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• pp.90-95
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• 2009

This paper presents a new feature extraction algorithm which can deal with the problems of linear discriminant analysis, widely used for linear dimensionality reduction. The scatter matrices included in linear discriminant analysis are defined by the distances between each datum and its class mean, and those between class means and mean of whole data. Use of these scatter matrices can cause computational problems and the limitation on the number of features. In addition, these definition assumes that the data distribution is unimodal and normal, for the cases not satisfying this assumption the appropriate features are not achieved. In this paper we define a new scatter matrix which is based on the differently weighted distances between individual data, and presents a feature extraction algorithm using this scatter matrix. With this new method. the mentioned problems of linear discriminant analysis can be avoided, and the features appropriate for discriminating data can be achieved. The performance of this new method is shown by experiments.

• 한국컴퓨터산업교육학회:학술대회논문집
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• 2003.11a
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• pp.87-94
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• 2003

Anisotropic diffusion is a selective smoothing technique that promotes smoothing within a region instead of smoothing across boundaries. In anisotropic diffusion, the rate of smoothing is controlled by the local value of the diffusion coefficient chosen to be a function of the local image gradient magnitude. El-Fallah and Gary E. Ford represented the image as a surface and proved that setting the inhomogeneous diffusion coefficient equal to the inverse of the magnitude of the surface normal results in surface evolving speed that is proportional to the mean curvature of the image surface. This model has the advantage of having the mean curvature diffusion (MCD) render invariant magnitude, thereby preserving structure and locality. In this paper, the proposed MCD model efficiently reduces diffusion coefficient at the thin edges using the smoothness of the surface.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.467-468
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• 1998

Impulsive noise appears as black and/or white spots in an image. It is usually caused by errors during the image acquisition or transmission through communication channels. This paper presents a study on the impulsive noise reduction filter of digital image. A much more effective method for removing impulse noise is weighted median filtering. But it loses some information by changing center value with no condition. We propose some new technique to change center value with some conditions. In this paper, the performance of conditional weighted median filter is compared to the commonly used median filter, mean filter, max/min filter, and weighted median filter. A quantitative comparison is performed on MSE (Mean Square Error), RMSE (Root Mean Square Error), and SNR (Signal to Noise Ratio). Proposed conditional weighted median filter can yield better performance than regular filters.

• Journal of the Korea Society for Simulation
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• v.8 no.2
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• pp.1-11
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• 1999

Advanced information communication processing system mainly consists of network access subsystems and a switching system. This paper provides performance analysis of a typical network access subsystem. The network access subsystem is modeled as a queueing network including a server providing polling services. The arrival process of messages to an input buffer is regarded as a Poisson process. Performance measures such as mean input buffer length and mean waiting time of meassages are obtained through simulation, for it is impossible to calculate the performance measures using an analytical method. Hybrid simulation is used to reduce the variance of estimators. The variance reduction effect on the mean waiting time is reported.

• Communications for Statistical Applications and Methods
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• v.28 no.4
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• pp.351-368
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• 2021

For a probabilistic model with positively skewed data, a lognormal distribution is one of the key distributions that play a critical role. Several lognormal models can be found in various areas, such as medical science, engineering, and finance. In this paper, we propose a new estimator for a lognormal mean and depict the performance of the proposed estimator in terms of the relative mean squared error (RMSE) compared with Shen's estimator (Shen et al., 2006), which is considered the best estimator among the existing methods. The proposed estimator includes a tuning parameter. By finding the optimal value of the tuning parameter, we can improve the average performance of the proposed estimator over the typical range of σ². The bias reduction of the proposed estimator tends to exceed the increased variance, and it results in a smaller RMSE than Shen's estimator. A numerical study reveals that the proposed estimator has performance comparable with Shen's estimator when σ² is small and exhibits a meaningful decrease in the RMSE under moderate and large σ² values.