• Journal of the Korea Society of Computer and Information
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• v.20 no.1
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• pp.103-110
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• 2015

In this paper, we propose a deblurring method using 1/4 selective filter. Deblurring methods require a lot of processing time for deblurring. In order to enhance execution speed, we propose a novel 1/4 selective filter. The proposed 1/4 selective filter restores major edge, but it distorts minor edge and texture. To solve this problem, we apply 1/4 selective filter to restore major edge and DOG(Difference of Gaussian) filter to restore minor edge and texture. Experimental results show that the proposed method removes the blur effectively.

• The Journal of the Korea Contents Association
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• v.19 no.7
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• pp.538-545
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• 2019

The purpose of this study was to analyze the change of body temperature and pain by application of Gaussian magnetic for the elderly delayed muscle pain. For the purpose, we selected 15 elderly women(age;$69.47{\pm}1.60$) and conducted repeated experiments. The Gaussian magnetic field area was divided into three areas (1000G, 1500G, 2000G). The applying arbitrarily manufactured magnetic field wristbands changes of body heat and pain before and after wearing Gaussian magnetic were measured and collected data were analyzed using SPSS 19.0. To examine the pre-and post-treatment differences by treatment areas, we conducted paired t-test. Group differences and interaction effects were analyzed using two-way ANOVA and Duncan post hoc tests. The significance level was set to ${\alpha}=.05$. The results are as follows. The change of body heat by the Gaussian magnetic field area showed significant differences in all three groups(P<.05). There were also significant differences in the results of group interactions and in the delayed muscle pain scale between groups(P<.05). The area with the largest difference appeared in the area of 1500G field. The 1000G-1500G Gauss field is considered to be the most ideal magnetic field for body heat and muscle pain changes. In conclusion, the Gaussian magnetic field of 1000G-1500G may affect body temperature and muscle pain in the elderly, and may have a significant impact on the quality of life in old age.

• Journal of the Korea Society of Computer and Information
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• v.18 no.11
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• pp.69-75
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• 2013

This paper introduces a touch recognition method for touch screen systems based on the SIFT(Scale Invariant Feature Transform) algorithm for stable touch recognition under strong noises. This method provides strong robustness against the noises and makes it possible to effectively extract the various size of touches due to the SIFT algorithm. In order to verify our algorithm we simulate it on the Matlab with the channel data obtained from a real touch screen. It was found from the simulations that our method could stably recognize the touches without regard to the size and direction of the touches. But, our algorithm implemented on a real touch screen system does not support the realtime feature because the DoG(Difference of Gaussian) of the SIFT algorithm needs too many computations. We solved the problem using the DoM(Difference of Mean) which is a fast approximation method of DoG.

• Speech Sciences
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• v.15 no.3
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• pp.7-15
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• 2008

This paper proposes the method to extract new feature vectors using the difference between the cepstrum for static characteristics and delta cepstrum for dynamic characteristics in speaker recognition (SR). The difference vector (DV) which it proposes from this paper is containing the static and the dynamic characteristics simultaneously at the intermediate characteristic vector which uses the deference between the static and the dynamic characteristics and as the characteristic vector which is new there is a possibility of doing. Compared to the conventional method, the proposed method can achieve new feature vector without increasing of new parameter, but only need the calculation process for the difference between the cepstrum and delta cepstrum. Experimental results show that the proposed method has a good performance more than 2.03%, on average, compared with conventional method in speaker identification (SI).

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.236-239
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• 1995

It is useful to simulate the human visual function for the purpose of image-processing. In this study, the hardware of the spatial filter with the sensitivity of lateral inhibition is realized by the combination of optical parts with electronic circuits. The diffused film with the characteristics of Gaussian type is prepared as a spatial filter. An object's image is convoluted with the spatial filter. From the difference of the convoluted images, the zero-cross position is detected at video rate. The edge of object is extracted in real-time by the use of this equipment. The resolution of edge changes with the value of the standard deviation of diffused film. In addition, it is possible to extract a directional edge selectively when the spatial filter with directional selectivity is used instead of Gaussian type of spatial filter.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.1
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• pp.90-98
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• 1993

A Gaussian is formed by diffusing a spot excitation. In this paper, a diffusion neural network model is derived from the diffusion equation. And it is shown that a difference of two Gaussians(DOG) may have the same shape as a Laplacian of Gaussian(LOG), A neural network model executing a DOG convolution by diffusing an external excitation is proposed. By this model intensity changes of image may be detected. This model may be implemented economically because each neuron has only four fixed-valued synapes.

• Proceedings of the IEEK Conference
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• 2004.06a
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• pp.27-30
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• 2004

This paper has been designed the TDMG(Time Delay Multiple Gaussian) pulse generator for UWB systems and analyzed the characteristics of UWB impulse. Composite two equal Gaussian pulses in a difference time lag, and then investigated TDMG pulse and modeled mathematically. Designed the TDMG pulse generator by ADS(Advanced Design System) to embody by using actual element with such mathematical model. As well as, this paper finally proved an excellence of the TDMG pulse generator by performing analysis through simulation.

• Journal of information and communication convergence engineering
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• v.9 no.3
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• pp.336-340
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• 2011

Many approaches to image restoration are aimed at removing either gauss or impulse noise. This is because both types of degradation processes are distinct in nature, and hence they are easier to manage when considered separately. Nevertheless, it is possible to find them operating on the same image, which produces a hard damage. This happens when an image, already contaminated by Gaussian noise in the image acquisition procedure, undergoes impulsive corruption during its digital transmission. Here we proposed an algorithm first judge the type of the noise according to the difference values of pixel's neighborhood region and impulse noise's characteristic. Then removes the gauss noise by modified weighted mean filter and removes the impulse noise by modified nonlinear filter. The result of computer simulation on test images indicates that the proposed method is superior to traditional filtering algorithms. The proposed method can not only remove mixed noise effectively, but also preserve image details.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.12C
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• pp.753-758
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• 2011

The constant modulus algorithm (CMA) widely used in blind equalization applications minimizes the averaged power of constant modulus error (CME) defined as the difference between an instant output power and a constant modulus. In this paper, a decision feedback version of the linear blind algorithm based on maximization of the zero-error probability for CME is proposed. The Gaussian kernel of the maximum zero-error criterion is analyzed to have the property to cut out excessive CMEs that may be induced from severely distorted channel characteristics. Decision feedback approach to the maximum zero-error criterion for CME is developed based on the characteristic that the Gaussian kernel suppresses the outliers and this prevents error propagation to some extent. Compared to the linear algorithm based on maximum zero-error probability for CME in the simulation of blind equalization environments, the proposed decision feedback version has superior performance enhancement particularly in cases of severe channel distortions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.10
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• pp.2303-2309
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• 1997

This paper presents a convergence analysis of the stocastic gradient adaptive algorithm based on the least mean absolute third (LMAT) error criteriohn. Under the assumption that the signals involved are zero-mean, wide-sense sateionaryand gaussian, a set of nonlinear difference equations that characterizes the mean and mean-squared behavior of the algorithm is derived. Computer simulation resutls show fairly good agreements between the theoetical and empirical behaviors of the algorithm.