• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.480-483
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• 2004

This paper, we present the evaluation of outage probability on the SNR under the overlapped carrier allocation scheme in the reverse link with imperfect power control of a cellular CDMA system, which is base on using Gaussian approximation. In numerical results, the band limited pulse generated by square-root of raised consin pulse shaping filters (SRRC) of the transmitted signal is investigated and compared in conventional FD/CDMA and OC-CDMA of the outage probability. It will be also show that the outage probability can be improved by overlapping of carriers. We use error statistics to model the intra-cell interference and evaluate the impact of different mobiles velocity and number of resolvable paths on the system performance.

• 전자공학회논문지B
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• 제33B권3호
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• pp.176-185
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• 1996

Transformin the huge size of drawings into a suitable format for CAD system and recognizng the contents of drawings are the major concerans in the automated analysis of engineering drawings. This paper proposes some methods for text/graphics separation, symbol extraction, vectorization and symbol recognition with the object of applying them to electronic cirucit drawings. We use MBR (Minimum bounding rectangle) and size of isolated region on the drawings for separating text and graphic regions. Characteristics parameters such as the number of pixels, the length of circular constant and the degree of round shape are used for extracting loop symbols and geometric structures for non-loop symbols. To recognize symbols, nearest netighbor between FD (foruier descriptor) of extractd symbols and these of classification reference symbols is used. Experimental results show that the proposed method can generate compact vector representation of extracted symbols and perform the scale change and rotation of extracted symbol using symbol vectorization. Also we achieve an efficient searching of circuit drawings.

• 전기학회논문지
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• 제61권4호
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• pp.639-642
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• 2012

Optical coherence tomography(OCT) can provide real-time and non-invasive subsurface imaging with ultra-high resolution of micrometer scale. However, conventional OCT systems generally have a limited imaging depth range within a depth of only 1-2 mm. To overcome the limitation, we have proposed an active surface tracking algorithm used in common-path Fourier-domain OCT system in order to extend the imaging depth range. The surface tracking algorithm based on the threshold and Savitzky-Golay filter of A-scan data was applied to real-time tracking. The algorithm has controlled a moving stage according to the sample's surface variance in real time. An OCT image obtained by the algorithm clearly show an extended imaging depth range. Consequently, the proposed algorithm demonstrated the potential for improving the conventional OCT systems with limitary depth range.

• 한국전산구조공학회논문집
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• 제15권2호
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• pp.341-349
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• 2002

레이더법은 건축구조물에 대한 비파괴 검사의 대표적인 방법의 하나이다. 레이더로 측정된 결과들을 분석하기 위해서는 전자기파의 전파에 대한 수치적인 모델링을 통한 이론적인 접근이 필요하다. 콘크리트 시편에 전파되는 전자기파를 모델링하기 위해 유한차분 시간영역법을 적용하고자 한다. 유한차분 시간영역법은 전자파 해석과 모델링을 통한 시뮬레이션에 매우 유용한 방법이다. 본 연구에서는 유한차분 시간영역법을 이용하여 두께가 다른 5개의 시편을 3차원으로 모델링하였다. 모델링 결과와 실험 결과를 비교하여 실험에서 시편 뒷 표면을 찾으며 시편두께를 측정한다.

• 말소리와 음성과학
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• 제5권4호
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• pp.211-216
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• 2013

The IVA(Independent Vector Analysis) is a well-known FD-ICA method used to solve the frequency permutation problem. It generally works quite well for blind source separation problems, but still needs some improvements in the frequency bin permutation problem. This paper proposes a post-processing method which can improve the source separation performance with the IVA by fixing the remaining frequency permutation problem. The proposed method makes use of the correlation coefficient of power ratio between frequency bins for separated signals with the IVA-based 2-channel source separation. Experimental results verified that the proposed method could fix the remaining frequency permutation problem in the IVA and improve the speech quality of the separated signals.

• 한국통신학회논문지
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• 제22권4호
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• pp.771-781
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• 1997

In order to solve the problem of uncovered background region due to the region-due to the region-based motion estimation, this paper presents a new method which generates the uncovered region memory using motion estimation and shows the application of the algorithm for very low bit rate video coding. The proposed algorithm can be briefly described as follows it detects the changed region by using the information of FD(frame difference) and segmentation, and then as for only that region the backward motion estimation without transmission of shape information is done. Therefore, from only motion information the uncovered background region memory is generated and updated. The contents stored in the uncovered background region memory are referred whenever the uncovered region comes into existence. The regions with large prediction error are transformed and coded by using DCT. As results of simulation, the proposed algorithm shows the superior improvement in the subjective and objective image quality due to the remarkable reduction of transmission bits for prediction error.

• ETRI Journal
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• 제38권2호
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• pp.280-290
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• 2016

To implement high-order multiuser multiple input and multiple output (MU-MIMO) for massive MIMO systems, there must be a feedback scheme that can warrant its performance with a limited signaling overhead. The interference-to-noise ratio can be a basis for a novel form of Codebook (CB)-based MU-MIMO feedback scheme. The objective of this paper is to verify such a scheme's performance under a practical system configuration with a 3D channel model in various radio environments. We evaluate the performance of various CB-based feedback schemes with different types of overhead reduction approaches, providing an experimental ground with which to optimize a CB-based MU-MIMO feedback scheme while identifying the design constraints for a massive MIMO system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권12호
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• pp.3991-4007
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• 2022

In the public healthcare, a computational system that can automatically and efficiently detect and classify falls from a video sequence has significant potential. With the advancement of deep learning, which can extract temporal and spatial information, has become more widespread. However, traditional 3D CNNs that usually adopt shallow networks cannot obtain higher recognition accuracy than deeper networks. Additionally, some experiences of neural network show that the problem of gradient explosions occurs with increasing the network layers. As a result, an enhanced three-dimensional ResNet-based method for fall detection (3D-ERes-FD) is proposed to directly extract spatio-temporal features to address these issues. In our method, a 50-layer 3D residual network is used to deepen the network for improving fall recognition accuracy. Furthermore, enhanced residual units with four convolutional layers are developed to efficiently reduce the number of parameters and increase the depth of the network. According to the experimental results, the proposed method outperformed several state-of-the-art methods.

• 한국인공지능학회지
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• 제11권4호
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• pp.21-27
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• 2023

This paper discusses a deep learning-based road surface analysis system that collects data by installing vibration sensors on the 4-axis wheel bearings of a vehicle, analyzes the data, and appropriately classifies the characteristics of the current driving road surface for use in the vehicle's control system. The data used for road surface analysis is real-time large-capacity data, with 48K samples per second, and the A2B protocol, which is used for large-capacity real-time data communication in modern vehicles, was used to collect the data. CAN and CAN-FD commonly used in vehicle communication, are unable to perform real-time road surface analysis due to bandwidth limitations. By using A2B communication, data was collected at a maximum bandwidth for real-time analysis, requiring a minimum of 24K samples/sec for evaluation. Based on the data collected for real-time analysis, performance was assessed using deep learning models such as LSTM, GRU, and RNN. The results showed similar road surface classification performance across all models. It was also observed that the quality of data used during the training process had an impact on the performance of each model.

• 지구물리와물리탐사
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• 제14권2호
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• pp.164-175
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• 2011

낮은 주파수의 자연 전자기장을 이용하는 MT 탐사는 지하 심부의 전기전도도 구조를 규명할 수 있기 때문에, 지열에너지자원 탐사, 이산화탄소의 지중저장을 위한 부지 선정, 인공저류층 지열발전 시스템 유망 지역 탐사 등에 적용되고 있다. 또한 해양 MT 자료를 활용하면 해양전자탐사 자료 해석의 정확도를 높일 수 있다. MT 자료의 해석에 있어 정확한 모델링 기법은 필수적이다. 변유한요소법을 이용한 기존의 MT 모델링 알고리듬에서는 보조장인 자기장을 차분적 방법론에 기초하여 계산하였기 때문에 수직자기장의 정확한 계산에 한계가 있었다. 이 논문에서는 변유한요소법의 기저함수들의 선형결합으로 근사된 전기장을 직접 미분하는 방법으로 수직자기장을 계산하였다. 수치 실험을 통해, 지형이 있는 경우에 수직자기장에 대한 기존의 알고리듬의 결과에 오차가 있음을 확인하였다. 최종적으로, 지형이 있는 모형에 대한 기존의 인덕션 벡터와 티퍼의 결과는 오차가 있는 수직자기장을 이용하였으므로, 이 논문에서는 개선된 알고리듬을 이용하여 올바른 결과를 제시하고자 한다.