• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.3A
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• pp.260-268
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• 2010

Channel inversion is one of the simplest techniques for multiuser downlink systems with single-antenna users. In this paper, we extend the regularized channel inversion technique developed for the single-antenna user case to multiuser multiple-input multiple-output (MIMO) channels with multiple-antenna users. We first employ the multiuser preprocessing to project the multiuser signals near the null space of the unintended users based on the MMSE criterion, and then the single-user preprocessing is applied to the decomposed MIMO interference channels. In order to reduce the complexity, we focus on non-iterative solutions for the multiuser transmit beamforming and use a linear receiver based on an MMSE criterion. Simulation results show that the proposed scheme outperforms existing joint iterative algorithms in most multiuser configurations.

• Journal of Astronomy and Space Sciences
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• v.13 no.2
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• pp.181-197
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• 1996

Thc CCD earth image experiment(CEIE) is one of the main payload of the KITSAT-1. Since it was launched on Age. 11, 1992, the CEIE has taken more than 500 images on the earth surface world-wide so far. An image from the space is very different from a feature on the real Earth surface due to various radiometric and geometric distortions. Preprocessing to remove those distortions has to take place before the image data are processed and analyzed further for various applications. This paper summarizes the result of the operation of the CEIE and describes the procedure to perform preprocessing including radiometric and geometric correction.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.183-185
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• 2010

There are many error sources in GPS signal propagation because the signals do not propagate in vacuum. The GPS observations should be preprocessed before they are used for positioning. The cycle slip and outlier detection algorithms are tested in this study in RINEX level using various linear combinations of the observables. The elbourne-Wubbena (M-W) linear combination has an advantage of long wavelength with low noise, and the geometry-free and ionosphere-free linear combinations are used as well to clean the measurements.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.13-16
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• 2017

제스처 인식은 HCI(Human-Computer Interaction) 및 HRI(Human-Robot Interaction) 분야에서 활발히 연구되고 있는 기술이며, 제스처 데이터의 특징을 추출해내고 그에 따른 분류를 통하여 사용자의 제스처를 정확히 판별하는 것이 중요한 과제로 자리 잡았다. 본 논문에서는 EMG(Electromyography) 센서로 측정한 사용자의 손 제스처 데이터를 분석하는 방안에 대하여 서술한다. 수집된 데이터의 노이즈를 제거하고 데이터의 특징을 극대화시키기 위하여 연속적인 데이터로 변환하는 전처리 과정을 거쳐 이를 머신 러닝 알고리즘을 사용하여 분류하였다. 이 때, 기존의 raw 데이터와 전처리 과정을 거친 데이터의 성능을 decision-tree 알고리즘을 통하여 비교하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.12A
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• pp.1238-1243
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• 2007

The computational complexity for the zero-forcing (ZF)-based multiuser (MU) multiple-input multiple-output(MIMO) preprocessing matrices can be immoderately large as the number of transmit antennas or users increases. In this paper, we show that the span of singular vector space of a matrix can be obtained from the singular vectors of the parted rows of that matrix with computational saving and propose a computationally efficient recursive-algorithm for achieving the ZF-based preprocessing matrices. Analysis about the complexities shows that a new recursive-algorithm can lighten the computational load.

• Korean Journal of Remote Sensing
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• v.36 no.4
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• pp.545-555
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• 2020

This paper focuses on automatic image registration between EO (Electro-Optical) and IR (InfraRed) satellite images with different spectral properties using block-based approach and simple preprocessing technique to enhance the performance of feature matching. If unpreprocessed EO and IR images from Kompsat-3A satellite were applied to local feature matching algorithms(Scale Invariant Feature Transform, Speed-Up Robust Feature, etc.), image registration algorithm generally failed because of few detected feature points or mismatched pairs despite of many detected feature points. In this paper, we proposed a new image registration method which improved the performance of feature matching with block-based registration process on 9-divided image and pre-processing technique based on adaptive histogram equalization. The proposed method showed better performance than without our proposed technique on visual inspection and I-RMSE. This study can be used for automatic image registration between various images acquired from different sensors.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.10a
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• pp.69-76
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• 1998

Due to the drastic improvement of computer hardware and operating system, it is easy to break through the main defects of limited computer memory and processing time, etc. To keep up with this situation, this paper is focused on developing the preprocessor program with the input method based on vector graphic editor and the preprocessing technique including automatic node generation algorithm for the $\rho$-version finite element program. To develop this preprocessor program, the special data structure and the OOP(Object Oriented Programming) have been used by the Visual Basic 4.0. The Special data structure is proposed to describe the geometric data of node numberings and coordinates suitable for the $\rho$-version finite element program, which are quite different from the comvential h-version finite element program.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.165-166
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• 2018

최근 딥러닝 기술이 발전함에 따라 이를 네트워크 침입탐지 분야에 적용하려는 연구가 활발히 이루어지고 있으며 이에 따라 대용량 네트워크 데이터에 대한 처리 방법이 주목받고 있다. 본 논문에서는 네트워크 데이터를 이미지화하는 전처리 방법을 제안한다. 네트워크 데이터를 세션단위로 처리하여 손실율을 줄이면서 딥러닝 알고리즘에 바로 적용할 수 있도록 정규화된 이미지로 변환하는 방법이다. 이를 통해 딥러닝 기술을 적용한 네트워크 정보보안 분야의 연구 활성화를 기대할 수 있다.

• 한국IT서비스학회:학술대회논문집
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• 2009.05a
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• pp.341-344
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• 2009

네트워크(Network) 라우터(Router)와 스위치(Switch) 장치에서 수많은 패킷(Packet)이 통과된다. 네트워크에 연결된 컴퓨터가 20대일 경우에 일일 평균 패킷 전송양은 약 400GB 정도에 이른다. 이러한 패킷 데이터를 분석하기 위해서는 수집된 데이터를 디스크 장치에 저장할 수 있는 대규모의 저장공간과 주기적인 백업이 필요하다. 수집된 데이터 원형에는 사용자가 원하는 정보뿐만 아니라 불필요한 정보가 산재해있다. 따라서 수집된 데이터를 원형 그대로 저장하는 것이 아니라 원하는 정보(Information)와 지식(Knowledge)이 유지되고 쉽게 식별될 수 있도록 데이터를 가공해서 요약된 정보를 유지하는 것이 효과적이다. 전 세계적으로 네트워크를 통과하는 패킷 데이터의 양이 헤아릴 수 없을 만큼 증가하고, 인터넷 보급률이 증가함에 따라서 인터넷 사용자 및 소비자의 정보 분석의 필요성이 부각되고 있다. 본 논문에서는 네트워크에서 수집된 패킷 데이터에 적합한 데이터 전처리 기법(preprocessing)을 제안한다.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.7
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• pp.625-631
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• 2010

This paper proposes lane recognition algorithm using lane prominence technique to extract lane candidate. The lane prominence technique is combined with embossing effect, lane thickness check, and lane extraction using mask. The proposed lane recognition algorithm consists of preprocessing, lane candidate extraction and lane recognition. First, preprocessing is executed, which includes gray image acquisition, inverse perspective transform and gaussian blur. Second, lane candidate is extracted by using lane prominence technique. Finally, lane is recognized by using hough transform and least square method. To evaluate the proposed lane recognition algorithm, this algorithm was applied to the detection of lanes in the rainy and night day. The experiment results showed that the proposed algorithm can recognize lane in various environment. It means that the algorithm can be applied to lane recognition to drive unmanned vehicles.