• 한국음향학회지
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• 제19권8호
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• pp.26-34
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• 2000

This paper presents a new adaptive impulse noise cancelling technique based on the adaptive nonlinear suppressing function. The proposed "adaptive threshold algorithm (ATA)" is controlled by the normalized power prior input data term, and this adaptive threshold makes the cancelling system highly robust against additive impulse noise. For the performance evaluation, we have tested the proposed algorithm with the observed signals simulated in various impulsive noise environments and real EMG signals. As a result the proposed algorithm shows superior performance of 51.7% to the available techniques in the points of SNR and MSE.

• 전자공학회논문지A
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• 제33A권6호
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• pp.32-41
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• 1996

We propose the improved GMSK (gaussian-filtered minimum shift keying) quadrature modulator using the FIR(finite impulse response )filter whose coefficients are obtained form the differnce of phase response, and design its ASIC (applicaton specific integrated circuit) which can be used for GSM (global system for mobile communication) digital cellular system and DCS 1800 (digital cellular system at 1800MHz) personal communication system. Input data become quantized I and Q channel 10 bit signal through cosine and sine ROM mapping after being filtered by the FIR filter whose normalized bandwidth is 0.3 and designed by considering intersymbol interference as well as sampling ratio. These two signals become the GMSK modulated I and Q channel signal through DAC (digital-to-analog converter) and 7th order analog chebyshev LPF(low pass filter) respectively. The difference between the ideal analog signal and its digitized signal is analyzed in terms of sampling noise, quantization noise, truncation noise and coefficient noise. And the effect of the LPF following the DAC is considered. The ASIC design of the GMSK quadrature modulator is also confirmed by an experiment.

• 한국정보시스템학회지:정보시스템연구
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• 제8권2호
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• pp.91-110
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• 1999

Recently, searching agent systems to help purchase of products between business and customer have been actively studied in Electronic Commerce(EC). However, the most of comparative searching agent systems are only provided customers with searching results by the keyword-based search, and is not support the efficient decision models to be selected products considering the customer's requirements. This paper proposes the decision agent system applied decision model as well as searching functions based on the keyword-input to be selected useful products in EC. The proposed decision agent system is consist of the user interface, provider interface, decision model. Especially, as the example of the decision model, this paper is designed and implemented the prototype of decision agent system which is normalized the searching data and value of customer's preference weight as to each attribute, and orderly provided customers with computed results. This agent system is also carried out sensitive analysis according to the reflection ratio of the each attribute.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2006년도 하계종합학술대회
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• pp.423-424
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• 2006

This paper describes a 3D face recognition using different devices for 3D faces and input faces which include several different pose. Before the recognition stage, through the EC-SVD, all data have to be preprocessed and normalized. At recognition stage, we propose the multi-point signature method for measuring facial surface information. And we use the root mean square error for matching. From the experiment results, we have 92.5% recognition rate.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2003년도 가을 학술발표회 논문집
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• pp.479-486
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• 2003

The characteristics of harmonic phase angles and phase angle differences contained in earthquake ground motions such as El Centre 1940 NS, Taft1 1952 NS, Hachinohe 1968 NS and Mexico 1985 are figured, which have been mostly overlooked in contrast with the importance placed on harmonic amplitudes. Recently, performance based design method is used for seismic design and seismic retrofitting, which needs nonlinear response analysis, there must be earthquake ground accelerations which contain the phase angle, the phase angle difference and energy input spectrum characteristics of the zone considered to be constructed building structures. To make clear the importance of phase angle differences, responses of 4 recorded earthquake ground motions, 4-earthquake ground motions normalized by 110 gal and 4 artificial earthquake motions compatible to the seismic building code of Korea are compared.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2007년도 하계종합학술대회 논문집
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• pp.379-380
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• 2007

In this paper, we propose the fast hi-linear interpolation method for SR reconstruction. This method reconstructs the HR image rapidity by considering motion vector information for each LR input image. And its calculation used normalized deviation of image data. As using the motion vector information which is obtained at registration error checking process, this proposed can be achieved the fast and simple SR reconstructed image.

• Journal of information and communication convergence engineering
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• 제1권1호
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• pp.53-57
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• 2003

Chaos theory is a study researching the irregular, unpredictable behavior of deterministic and non-linear dynamical system. The interpretation using Chaos makes us evaluate characteristic existing in status space of system by tine series, so that the extraction of Chaos characteristic understanding and those characteristics enables us to do high precision interpretation. Therefore, This paper propose the new method which is adopted in extracting character features and recognizing characters using the Chaos Theory. Firstly, it gets features of mesh feature, projection feature and cross distance feature from input character images. And their feature is converted into time series data. Then using the modified Henon system suggested in this paper, it gets last features of character image after calculating Box-counting dimension, Natural Measure, information bit and information dimension which are meant fractal dimension. Finally, character recognition is performed by statistically finding out the each information bit showing the minimum difference against the normalized pattern database. An experimental result shows 99% character classification rates for 2,350 Korean characters (Hangul) using proposed method in this paper.

• 반도체디스플레이기술학회지
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• 제8권2호
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• pp.23-29
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• 2009

To increase the data capacity of one-dimensional symbology, 2D barcodes have been proposed a decade ago. In this paper, a new 2D barcode detection algorithm based on Local Binary Pattern is presented. To locate 2D barcode symbols, a texture analysis scheme based on the Local Binary Pattern is adopted, and a gray-scale projection with sub-pixel operation is utilized to separate the symbol precisely from the input image. Finally, the segmented symbol is normalized using the inverse perspective transformation for the decoding process. The proposed method ensures high performances under various lighting/printing conditions and strong perspective deformations. Experiments show that our method is very robust and efficient in detecting the symbol area for the various types of 2D barcodes.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.1249-1252
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• 2003

To analyse the cyclic variations in a test engine, the burn parameters are determined on a cycle-to-cycle basis through the analysis of the engine pressure data. Combustion analysis based on cylinder-pressure provides a mechanism through which a combustion researcher can understand the combustion process. The objective of this paper is to identify the most significant sources of cycle-to-cycle combustion variability in a spark ignition engine at idle. The burn rate analysis program was used and the burn parameters were used to determine the variations in the input parameter. In this study, the author investigated the relationship of indicated mean effective pressure, coefficient of variation of indicated mean effective pressure and burn angles, and lowest normalized value in a spark ignition engine for the cyclic variations.

• 한국정보통신학회논문지
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• 제13권9호
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• pp.1905-1912
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• 2009

FCM 알고리즘은 입력 벡터와 각 클러스터의 유클리드 거리를 이용하여 구해진 소속도만를 비교하여 데이터를 분류하기 때문에 클러스터링 된 공간에서의 데이터들의 분포에 따라 바람직하지 못한 클러스터링 결과를 보일 수 있다. 이러한 문제점을 개선하기 위해 대칭적 성질을 이용하는 대칭성 측도에 퍼지 이론을 적용하여 군집간의 거리에 따른 변화와 군집 중심의 위치, 그리고 군집 형태에 따라 영향을 덜 받는 개선된 FCM이 제안되었다. 본 논문에서는 효과적으로 패턴을 분류하기 위해 개선된 FCM 알고리즘을 적용한 개선된 하이브리드 네트워크를 제안한다. 제안된 하이브리드 네트워크는 개선된 FCM 알고리즘을 입력층과 중간층의 학습구조 적용하고 중간층과 출력층의 학습 구조는 일반화된 델타 학습법을 적용한다. 제안된 방법의 인식 성능을 평가하기 위해 2차원 좌표 평면 상의 데이터를 기존의 Max_Min 신경망을 이용한 FCM 기반 RBF 네트워크와 FCM 기반 RBF 네트워크, HCM 기반 네트워크와 제안된 방법 간의 학습 및 인식 성능을 비교 및 분석하였다.