• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.16 no.10 s.101
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• pp.1043-1049
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• 2005

In OFDM system suitable for high capacity high speed broadband transmission, ICI caused by phase noise degrades system performance seriously by destroying the orthogonality among subcarriers. In this paper, a new STFBC method combining ICI self cancellation scheme and antenna, time, frequency diversity is studied to reduce ICI effectively. CPE and ICI are analyzed by the phase noise linear approximation method in the proposed STFBC OFDM system. CIR, PICR and BER are discussed to compare the system performance degraded by phase noise of PLL. As results, STFBC method significantly reduces ICI. Furthermore, the SCI that usually happens in the traditional STBC, SFBC diversity coding method can be easily avoided.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.3C
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• pp.248-256
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• 2003

Space-time coding was designed for an efficient transmit diversity technique to improve performance of wireless communication. For the transmit diversity using space-time coding, the receiver requires to estimate channel parameters corresponding to each transmit antennas. In this paper, we propose an efficient channel estimation scheme based on trigonometric polynomial approximation in OFDM systems with transmit diversity using space-time coding. The proposed scheme is more efficient than the conventional scheme in terms of the computational complexity. For QAM modulation, when the size of FFH is 128, the conventional scheme with significant tap caching of 7 requires 9852 complex multiplications for TU, HT and BU channels. But the proposed scheme requires 2560, 7680 and 3584 complex multiplications for TU, HT and BU channels, respectively. Especially, for channels with smaller Doppler frequency and delay spreads, the proposed scheme has the improved BER performance and complexity. In addition, we evaluate the performance of maximum delay spread estimation in unknown channel. The performance of the proposed scheme is investigated by computer simulation in various multi-path fading environments.

• Journal of Digital Contents Society
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• v.11 no.4
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• pp.597-606
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• 2010

This paper describes a real-time camera tracking framework specifically designed to track a monocular camera in an AR workspace. Typically, the Kalman filter is often employed for the camera tracking. In general, however, tracking performances of conventional methods are seriously affected by unpredictable situations such as ambiguity in feature detection, occlusion of features and rapid camera shake. In this paper, a recursive Bayesian sampling framework which is also known as the particle filter is adopted for the camera pose estimation. In our system, the camera state is estimated on the basis of the Gaussian distribution without employing additional uncertainty model and sample weight computation. In addition, the camera state is directly computed based on new sample particles which are distributed according to the true posterior of system state. In order to verify the proposed system, we conduct several experiments for unstable situations in the desktop AR environments.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.77-84
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• 2022

In this paper, we propose a novel unsupervised feature selection method. Conventional unsupervised feature selection method defines virtual label and uses a regression analysis that projects the given data to this label. However, since virtual labels are generated from data, they can be formed similarly in the space. Thus, in the conventional method, the features can be selected in only restricted space. To solve this problem, in this paper, features are selected using orthogonal projections and low-rank approximations. To solve this problem, in this paper, a virtual label is projected to orthogonal space and the given data set is also projected to this space. Through this process, effective features can be selected. In addition, projection matrix is restricted low-rank to allow more effective features to be selected in low-dimensional space. To achieve these objectives, a cost function is designed and an efficient optimization method is proposed. Experimental results for six data sets demonstrate that the proposed method outperforms existing conventional unsupervised feature selection methods in most cases.

• The Journal of the Acoustical Society of Korea
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• v.28 no.4
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• pp.383-391
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• 2009

In speech signal processing, speech signal corrupted by noise should be enhanced to improve quality. Usually noise estimation methods need flexibility for variable environment. Noise profile is renewed on silence region to avoid effects of speech properties. So we have to preprocess finding voice region before noise estimation. However, if received signal does not have silence region, we cannot apply that method. In this paper, we proposed SNR estimation method for continuous speech signal. The waveform which is stationary region of voiced speech is very correlated by pitch period. So we can estimate the SNR by correlation of near waveform after dividing a frame for each pitch. For unvoiced speech signal, vocal track characteristic is reflected by noise, so we can estimate SNR by using spectral distance between spectrum of received signal and estimated vocal track. Lastly, energy of speech signal is mostly distributed on voiced region, so we can estimate SNR by the ratio of voiced region energy to unvoiced.

• Journal of Platform Technology
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• v.6 no.3
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• pp.23-30
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• 2018

A motion pattern generation is a process of calculating a certain stable motion trajectory for stably operating a certain motion. A motion control is to make a posture of a robot stable by eliminating occurring disturbances while a robot is in operation using a pre-generated motion pattern. In this paper, a general method of motion pattern generation for a biped walking robot using universal approximator, learning neural networks, is proposed. Existing techniques are numerical methods using recursive computation and approximating methods which generate an approximation of a motion pattern by simplifying a robot's upper body structure. In near future other approaches for the motion pattern generations will be applied and compared as to be done.

• Journal of KIISE:Databases
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• v.37 no.1
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• pp.44-49
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• 2010

In this paper, we first address the problems associated with indexing and searching for reduced-dimensional vectors, which are reduced by using a combination of angle approximation and dimension grouping. Then, we propose a novel method to solve the problems. We also show the superiority of the proposed method by performing extensive experiments with synthetic and real-life data sets.

• Computational Structural Engineering
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• v.17 no.2
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• pp.60-72
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• 2004

유한요소법의 테두리 내에서, 함수 자체 및 그 미분에서 발생하는 임의의 불연속면을 처리할 수 있고, 또 불연속면의 교차 및 분기를 다루는 기법을 제사하였다. 불연속면을 근사하기 위해 거리함수를 이용하였고, 불연속면의 천이는 레벨？ 함수를 이용하여 표현하였다. 이산화된 방정식을 유도하기 위해 표준 갈라킨법을 이용하였다. 수치해석 예로서, 균열성장, 회전축 베어링, 비부착 함입, 암반의 절리를 대상으로 하였다. 본 논문은 International Journal for Numerical Methods in Engineering 2001년 50호 pp. 993-1013에 발표된 논문이다. (중략)

• Proceedings of the Korea Multimedia Society Conference
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• 2002.05d
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• pp.559-564
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• 2002

본 논문에서는 범죄수사의 초동수사 기법으로 사용되고 있는 몽타주와 실물 사진과의 근사 영상 검색 알고리즘을 제안한다. 입력 몽타주를 얼굴인식 기법에 적용하여 이진영상화와 형태학적 필터로 영상의 잡음을 제거한 후 경계선을 추출하였다. 추출된 경계선 영상으로 레이블링 과정을 거친 후 얼굴의 중요 요소를 포함하는 특징얼굴을 구성한다. 특징얼굴은 웨이블릿 변환을 통해 다운 샘플링 된 LL대역의 계수로 변환되며, 고유값 연산을 통해 계수 매트릭스의 고유 값을 추출 한다. 입력 몽타주의 고유값은 같은 절차를 거친 실물 사진의 저장된 고유값과 계수의 분포를 비교한다. 실험 결과 몽타주와 유사한 실물 사진을 검색할 수 있었으며 영상의 크기 변화와 왜곡 및 압축에 견고한 비교 검색 결과를 얻었다.

• Journal of the Earthquake Engineering Society of Korea
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• v.5 no.3
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• pp.1-8
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• 2001

Seismic design forces for bridge components may be determined by modifying elastic member forces of design earthquakes using appropriate response modification factors according to the national design code of bridges Modeling technique of pile foundation system is one of the important parameters which greatly affects the results in the process of the elastic seismic analysis of a bridge system with pile foundation. In this paper, a approximate and simplified modeling technique of a pile foundation system for the practical purposes is presented. The modeling technique is based on the stiffnesses of pile foundation during earthquake. The horizontal stiffnesses are determined from the resistance-deflection curves derived from the results of dynamic field tests using cyclic loads and the vertical stiffness includes the effects of the end bearing capacities and side friction of piles as well as the pile compliances under the expected vertical load level. The applicability of the proposed technique has been validated through the some example bridge analyses.