• Title/Summary/Keyword: 누적차분

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Deinterleaving the Pulse Trains in Multiple Signal Environment (다중 신호환경하에서 펄스 열 분리(deinterleaving))

  • 이성호;김정호;정회인
    • Journal of the Korea Institute of Military Science and Technology
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    • v.5 no.4
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    • pp.38-48
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    • 2002
  • Some signals, such as in radar system, are transmitted as periodic pulse trains. If more than one pulse train are transmitted over the same communication channel, a problem is to separate them for source identification and extract each pulse train at the receiver. This is known as pulse train deinterleaving. In this paper, we present an approach for deinterleaving the pulse trains and extracting their periods combining the estimation of the frequency of each pulse train by DFT, CDIF/SDIF histogram and Sequence Search technique. Also, we present the result of deinterleaving pulse trains and extracting PRI in the complex environment which multiple signals are interleaved.

Viterbi-based Decoding Algorithm for DBO-CSS

  • Yoon, Sang-Hun;Jung, Jun-Mo
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2011.10a
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    • pp.646-649
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    • 2011
  • Differential detection algorithm for DBO-CSS based on maximum signal energy detection (MSED) using viterbi algorithm is proposed. In order to mitigate SNR degradation caused by differential decoding, a modified viterbi algorithm with so called correlation metric (CM) in every state is proposed. It is shown that the performance gain of the proposed algorithm when compared with that of the conventional differential detection with the block decoding algorithm is about 2.5dB at BER = $10^{-5}$.

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Rational Estimation of Dam Low-flow Frequency Inflow (가뭄대응력 평가를 위한 합리적 댐 유입량 산정 연구)

  • Kim, Ji-Heun;Lee, Jae-Hwang;Kim, Yeong-O
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.178-178
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    • 2021
  • 최근 들어 기후변화로 인한 극심한 가뭄 피해가 한반도에 발생하고 있다. 가뭄 상황에 대비하여 댐을 안정적으로 운영하기 위해서는 갈수빈도 유입량에 대한 분석이 필수적이다. 갈수빈도해석의 경우, 홍수빈도해석과 유사하게 확률밀도함수의 극값에 대한 확률값을 산정하며, 확률 분포형의 역함수에 비초과확률을 대입하여 산정한다. 그러나 홍수와 달리 가뭄은 지속기간이 긴 특성 탓에 자기상관을 고려해야하며, 댐 및 저수지 등 대규모 시설물의 경우 일반적인 하천과 달리 저류효과로 인해 누적 유량에 대한 고려가 필요하다. 이에 K-water는 자체 제작한 누가차분법 및 Disaggregation 두 가지 방법을 채택하여 실무에서 사용해왔다. 그러나 누가차분법을 사용할 경우, 빈도유입량이 지나치게 크게 산정되는 문제가 있으며, Disaggregation 방법을 사용하는 경우, 특정 빈도 이상의 극한가뭄에서 유입량의 차이가 유의미하지 않아 산정된 빈도유입량과 최근 발생한 극심한 가뭄의 실측유입량간 큰 차이가 발생하고 있다. 따라서 본 연구에서는 자기상관을 고려한 선형회귀모형에 근거하여 빈도유입량을 배분하는 방법을 제안한다. 또한, 앞서 서술한 네 가지 빈도유입량 방법(월빈도분석, 누가차분법, K-water Disaggregation, 자기상관 선형회귀모형)에 대한 수식적 비교를 수행하며, 국내 댐 유역에 적용 및 평가를 통해 자료 특성에 따른 적절한 빈도유입량 산정방식에 대한 기준을 제안한다. 본 연구를 통해 가뭄특성을 고려한 합리적인 댐 유입량을 산정함으로써 보다 유연한 수자원시설물의 가뭄대응이 이루어질 것으로 기대된다.

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Cumulative Effects of Trade Liberalization : The Case of Korean Manufacturing (무역자유화의 동태적 누적효과: 한국 제조업)

  • Park, Soonchan
    • Economic Analysis
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    • v.17 no.4
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    • pp.30-51
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    • 2011
  • Since the previous studies on the effects of trade liberalization implicitly assume that trade liberalization affects economic performance only in any point in time, they inevitably are static. Static evaluations fail to account for cumulative dynamic effects of trade liberalization that affect continuously economic performance. This paper tries to fill this gap of the previous studies in this field, estimating cumulative effects of trade liberalization on economic performance by employing an dynamic version of empirical model. One of important empirical issue is controlling bias from endogeneity. To resolve this problem, this paper employes system GMM that uses lagged first-differences as instruments for level equations and lagged levels as instruments for first-differences equations. It improves upon cross-section estimators because it controls for the potential bias induced by the omission of industry-specific effects and the endogeneity of all regressors. This study investigates the effects of trade liberalization in Korean manufacturing for the period from 1988 to 2005 and finds that cumulative dynamic effects of trade liberalization are present and bigger than static effects.

Reliable Smoke Detection using Static and Dynamic Textures of Smoke Images (연기 영상의 정적 및 동적 텍스처를 이용한 강인한 연기 검출)

  • Kim, Jae-Min
    • The Journal of the Korea Contents Association
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    • v.12 no.2
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    • pp.10-18
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    • 2012
  • Automatic smoke detection systems using a surveillance camera requires a reliable smoke detection method. When an image sequence is captured from smoke spreading over in the air, not only has each smoke image frame a special texture, called static texture, but the difference between two smoke image frames also has a peculiar texture, called dynamic texture. Even though an object has a static texture similar to that of the smoke, its dynamic texture cannot be similar to that of the smoke if its movement differs from the diffraction action of the smoke. This paper presents a reliable smoke detection method using these two textures. The proposed method first detects change regions using accumulated frame difference, and then picks out smoke regions using Haralick features extracted from two textures.

Design of Kinematic Position-Domain DGNSS Filters (차분 위성 항법을 위한 위치영역 필터의 설계)

  • Lee, Hyung Keun;Jee, Gyu-In;Rizos, Chris
    • Journal of Advanced Navigation Technology
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    • v.8 no.1
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    • pp.26-37
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    • 2004
  • Consistent and realistic error covariance information is important for position estimation, error analysis, fault detection, and integer ambiguity resolution for differential GNSS. In designing a position domain carrier-smoothed-code filter where incremental carrier phases are used for time-propagation, formulation of consistent error covariance information is not easy due to being bounded and temporal correlation of propagation noises. To provide consistent and correct error covariance information, this paper proposes two recursive filter algorithms based on carrier-smoothed-code techniques: (a) the stepwise optimal position projection filter and (b) the stepwise unbiased position projection filter. A Monte-Carlo simulation result shows that the proposed filter algorithms actually generate consistent error covariance information and the neglection of carrier phase noise induces optimistic error covariance information. It is also shown that the stepwise unbiased position projection filter is attractive since its performance is good and its computational burden is moderate.

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Design of Heavy Rain Advisory Decision Model Based on Optimized RBFNNs Using KLAPS Reanalysis Data (KLAPS 재분석 자료를 이용한 진화최적화 RBFNNs 기반 호우특보 판별 모델 설계)

  • Kim, Hyun-Myung;Oh, Sung-Kwun;Lee, Yong-Hee
    • Journal of the Korean Institute of Intelligent Systems
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    • v.23 no.5
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    • pp.473-478
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    • 2013
  • In this paper, we develop the Heavy Rain Advisory Decision Model based on intelligent neuro-fuzzy algorithm RBFNNs by using KLAPS(Korea Local Analysis and Prediction System) Reanalysis data. the prediction ability of existing heavy rainfall forecasting systems is usually affected by the processing techniques of meteorological data. In this study, we introduce the heavy rain forecast method using the pre-processing techniques of meteorological data are in order to improve these drawbacks of conventional system. The pre-processing techniques of meteorological data are designed by using point conversion, cumulative precipitation generation, time series data processing and heavy rain warning extraction methods based on KLAPS data. Finally, the proposed system forecasts cumulative rainfall for six hours after future t(t=1,2,3) hours and offers information to determine heavy rain advisory. The essential parameters of the proposed model such as polynomial order, the number of rules, and fuzzification coefficient are optimized by means of Differential Evolution.

The Effect of Pile Distallation on the Reduction of Cumulative Plastic Settlement (말뚝 설치를 통한 콘크리트궤도의 누적소성침하 감소 효과)

  • Lee, Su-Hyung;Lee, Il-Wha;Lee, Sung-Jin;Kim, Dae-Sang
    • Journal of the Korean Geotechnical Society
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    • v.24 no.5
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    • pp.129-137
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    • 2008
  • An active application of concrete track is being expected far the future constructions of Korean railroad. In comparison with the existing ballasted tract, a concrete track is very susceptible for the settlement, since its rehabilitation requires much time and cost. When a concrete track is constructed on fine-grained subgrade soil, excessive cumulative plastic settlements due to repetitive train road may occur. In this case, the settlement of the concrete track may be effectively reduced by installing a small number of small-diameter piles beneath the track. This paper presents the effect of pile installation on the reduction of cumulative plastic settlement of concrete track. A method combining experiential equation and numerical method is proposed. Using an existing experiential equation and the estimated earth pressure distribution, the cumulative plastic strain was calculated. From the results, it is verified that the effects of the pile installation is significant to effectively reduce the cumulative plastic settlement of concrete track. The reduction effects of the cumulative plastic settlement according to the pile number and pile arrangement are presented.

GPS 관측을 이용한 칠레지진(2010.2.27)에 의한 주변지역 변위발생분석

  • Baek, Jeong-Ho;Jo, Jeong-Ho;Park, Pil-Ho
    • Bulletin of the Korean Space Science Society
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    • 2010.04a
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    • pp.37.2-37.2
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    • 2010
  • GPS 관측자료를 이용하여 최근 발생한 칠레지진에 의한 지각의 변위를 결정하고 결과를 분석하였다. 고정밀 측지용 이중주파수 GPS 수신기 및 안테나가 장착된 관측소의 자료를 처리하면 수mm 정밀도로 관측소의 위치를 결정할 수 있으며, 수년간의 관측자료가 누적되면 연간 mm급의 움직임도 관측할 수 있어 판운동이나 지진, 단층연구 등에 널리 활용되고 있다. 이번 2010년 2월 27일 칠레 중서부에서 발생한 지진은 인근 지역을 30 cm 이상 움직였을 것으로 예상되며 8.8의 대형 지진규모와 많은 인명 및 재산피해를 유발시켜 학계뿐만 아니라 일반 언론에도 많은 주목을 받고 있다. 이 연구에서는 지진이 발생한 지역 부근에 위치한 국제 GPS 기준망의 GPS 관측자료를 처리하여 지진 발생 전후의 변위를 산출하고 분석하였다. 자료처리를 위해 Bernese GPS S/W 5.0을 사용하였고 24시간단위 자료에 대해 이중차분방법과 단독정밀측위방법을 사용하였다. 또한 지진이 발생 도중의 변위를 관찰하기 위해 이동측위방법을 사용하여 30초마다의 움직임을 계산하였다.

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A Fast Bayesian Detection of Change Points Long-Memory Processes (장기억 과정에서 빠른 베이지안 변화점검출)

  • Kim, Joo-Won;Cho, Sin-Sup;Yeo, In-Kwon
    • The Korean Journal of Applied Statistics
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    • v.22 no.4
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    • pp.735-744
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    • 2009
  • In this paper, we introduce a fast approach for Bayesian detection of change points in long-memory processes. Since a heavy computation is needed to evaluate the likelihood function of long-memory processes, a method for simplifying the computational process is required to efficiently implement a Bayesian inference. Instead of estimating the parameter, we consider selecting a element from the set of possible parameters obtained by categorizing the parameter space. This approach simplifies the detection algorithm and reduces the computational time to detect change points. Since the parameter space is (0, 0.5), there is no big difference between the result of parameter estimation and selection under a proper fractionation of the parameter space. The analysis of Nile river data showed the validation of the proposed method.