• Title/Summary/Keyword: 가중치 계수

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On the Performance CDMA System Using Weighted Value (가중치를 이용한 CDMA 시스템 성능분석)

  • Lee, Kwan-Houng;Kim, Hack-Yoon;Song, Woo-Young
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.3
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    • pp.213-219
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    • 2006
  • Interference occurs by signals received from directions that were different from the signals of the users in a mobile communication system. Various studies have been undertaken, including diversity, equalizer, etc., in order to reduce interference. In this study, the weighted value of the array antenna was obtained to improve signal-to-noise ratio. The weighted value was obtained as an eigen value and an eigen vector by using the correlation coefficient of the signal. The weighted value obtained was then applied to the CDMA system to increase system performance and capacity. Both QPSK and OQPSK modulation systems were applied to analyze performance.

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Parameter estimation of unsteady flow model using mulit-objective optimization and minimax regret approach (다목적최적화와 최소최대 후회도 방법에 의한 부정류 계산모형의 매개변수 추정)

  • Li, Li;Chung, Eun-Sung;Jun, Kyung Soo
    • Proceedings of the Korea Water Resources Association Conference
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    • 2017.05a
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    • pp.310-310
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    • 2017
  • 홍수추적 모형의 적절성을 결정하는 중요한 요소 중 하나는 모형의 매개변수이다. 특히 자연하천에 관한 부정류 계산모형의 매개변수인 조도계수는 하상재료의 특성에 따라 좌우되는 표피마찰뿐만 아니라 하상의 굴곡 등 단면형의 변화에 따른 형상손실 및 하천의 사행에 따른 손실 효과 등을 포괄적으로 내포하고 있기 때문에 모든 하천구간에 대하여 일반적으로 적용할 수 있는 조도계수의 값을 하나로 결정하기는 어렵다. 또한 조도계수는 흐름조건, 즉 유량 또는 수위의 변화에 따른 가변성을 갖고 있기 때문에, 흐름이 시간 및 공간적으로 변화하는 부정류 계산모형에 있어서는 더욱 그러하다. 그러므로 본 연구에서는 조도계수의 가변성과 다수 지점의 관측치를 고려한 모형보정의 결과로부터 얻은 파레토 최적화와 최소최대 후회도 방법(Minimax regret approach, MRA)을 결합하여 부정류 계산모형의 안정적인 매개변수를 선정할 수 있는 방법을 제안하였다. 여러 지점의 관측치를 고려한 모형의 보정은 다목적 최적화 문제로서, 여러 지점에 대한 가중치를 결합하여 얻은 하나의 목적함수에 대하여 여러 번의 개별 최적화를 수행함으로써 다수의 파레토 최적해들을 구할 수 있는 통합접근법을 적용하였다. 이때 유량에 따른 조도계수의 가변성을 나타내는 두 개의 매개변수로 구성된 관계식을 이용하여 두 구간에 대한 매개변수들을 모형의 추정 대상 매개변수로서 최적화하였다. 이 후 각기 다른 홍수사상에 대해 보정과 검증을 수행하였으며 각각에 대한 평가지표의 후회도를 정량화하였고 최종 안정적인 매개변수를 추정하기 위해 MRA를 이용하여 종합적인 순위를 도출하였다. MRA는 완전히 불확실한 의사결정 상황에서 유용한 방법으로 알려져 있는데 가장 나쁜 순위가 가장 좋은 것을 선택할 수 있게 하는 보수적인 의사결정기법이다. 계산결과 추정된 모형의 가변조도계수와 그로부터 얻은 두 개 지점에서의 평가지표인 RMSE는 두 지점에 대한 가중치의 조합에 따라 선택되는 매개변수 값에 따라 달라짐을 알 수 있었다. 본 연구에서 제시한 방법은 수문 및 수리모형의 다수의 관측지점의 자료를 이용한 매개변수 산정문제에 있어서 안정적인 해를 도출할 수 있다.

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Weighted Prediction based on Classification of Motion for HEVC (움직임의 구분에 기반한 HEVC의 가중치 예측)

  • Lim, Sung-won;Moon, Joo-hee
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2014.11a
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    • pp.105-106
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    • 2014
  • 본 논문에서는, 움직임이 존재하는 영역과 존재하지 않는 영역을 구분하여 영역마다 다른 가중치 계수 세트 w와 o를 사용하는 알고리즘이 제안된다. 제안된 기술의 실험 결과는 BD-rate기준으로 최대 -5.4%의 효율을 가져오며 인코더 복잡도는 약 110%, 디코더 복잡도는 거의 변화가 없다.

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Weighted TR prefilter for Minimum ISI in indoor wireless Communication System (실내 무선 통신 환경에서 심볼 간 간섭 최소화를 위해 가중치를 적용한 시역전 필터)

  • Yoon, Mi-Sun;Lee, Chung-Yong
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.49 no.8
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    • pp.52-57
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    • 2012
  • We propose a weighted time-reversal prefilter for indoor wireless communication systems. In the indoor wireless communication environments, the bit error rate (BER) performance is significantly degraded by the delay spread. The conventional schemes have complex receivers to recover deterioration of the BER. The proposed time-reversal prefilter simplifies the structure of receivers, minimizes the inter-symbol interference (ISI) and maintains the peak power level of the received signal. The simulation results show that the weighted time-reversal prefilter improves the BER performance in comparison with the conventional time-reversal prefilter.

Weighted Prediction considering Global Brightness Variation and Local Brightness Variation in HEVC (전체적 밝기 변화와 지역적 밝기 변화를 고려한 HEVC에서의 가중치 예측)

  • Lim, Sung-won;Moon, Joo-hee
    • Journal of Broadcast Engineering
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    • v.20 no.4
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    • pp.489-496
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    • 2015
  • In this paper, a new weighted prediction scheme is proposed to improve the coding efficiency for video scenes containing brightness variations. Conventional weighted prediction is applied by the reference picture and use only one weighted parameter set. Thus, it is only useful for GBV(Glabal Brightness Variation). In order to solve this problem, the proposed algorithm use three kind of schemes depending on situation. Experimental results show that maximum coding efficiency gain of the proposed method is up to 10.2% in luminance. Average computional time complexity is increased about 163% in encoder and about 101% in decoder.

A Study on Quantitative Measurement of Metadata Quality for Journal Articles (학술지 기사에 대한 메타데이터 품질의 계량화 방법에 관한 연구)

  • Lee, Yong-Gu;Kim, Byung-Kyu
    • Journal of the Korean Society for information Management
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    • v.28 no.1
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    • pp.309-326
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    • 2011
  • Most metadata quality measurement employ simple techniques by counting error records. This study presents a new quantitative measurement of metadata quality using advanced weighting schemes in order to overcome the limitations of exiting measurement techniques. Entropy, user tasks, and usage statistics were used to calculate the weights. Integrated weights were presented by combining these weights and were applied to actual journal article metadata. Entropy weights were found to reflect the characteristics of the data itself. User tasks presented the required metadata elements to solve user's information need. Integrated weights showed balanced measures without being affected by the influence of error elements, This finding indicates the new method being suitable for quantitative measurement of metadata quality.

A Graphical Method for Evaluating the Effect of Outliers in One- and Two-Variate Data (일변량 및 이변량 자료에 대하여 특이값의 영향을 평가하기 위한 그래픽 방법)

  • Jang, Dae-Heung
    • The Korean Journal of Applied Statistics
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    • v.20 no.2
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    • pp.395-407
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    • 2007
  • Outliers distort many measures for data analysis. We can propose dandelion seed plot as a graphical tool for evaluating the effect of outliers in one-and two-variate data. We can draw mean-variance dandelion seed plots using linked curves which are made by changing weights from 1 to 0 for each datum. Similarly we can also draw covariance-correlation-coefficient dandelion seed plots. This graphical method can be a useful tool for elementary statistics education in college.

Development of a Clustering Model for Automatic Knowledge Classification (지식 분류의 자동화를 위한 클러스터링 모형 연구)

  • 정영미;이재윤
    • Journal of the Korean Society for information Management
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    • v.18 no.2
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    • pp.203-230
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    • 2001
  • The purpose of this study is to develop a document clustering model for automatic classification of knowledge. Two test collections of newspaper article texts and journal article abstracts are built for the clustering experiment. Various feature reduction criteria as well as term weighting methods are applied to the term sets of the test collections, and cosine and Jaccard coefficients are used as similarity measures. The performances of complete linkage and K-means clustering algorithms are compared using different feature selection methods and various term weights. It was found that complete linkage clustering outperforms K-means algorithm and feature reduction up to almost 10% of the total feature sets does not lower the performance of document clustering to any significant extent.

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Influence Comparison of Customer Satisfaction Factor using Quantile Regression Model (분위회귀모형을 이용한 고객만족도 요인의 영향력 비교)

  • Kim, Seong-Yoon;Kim, Yong-Tae;Lee, Sang-Jun
    • Journal of Digital Convergence
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    • v.13 no.6
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    • pp.125-132
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    • 2015
  • It is current situation that a number of issues are being raised how the weight is calculated from customer satisfaction survey. This study investigated how the weight of satisfaction for each quantile is different by comparing ordinary least square regression model to quantile regression model and carried out bootstrap verification to find the influence difference of regression coefficient for each quantile. As the analysis result of using R(Quantreg package) that is open software, it appeared that there was the influence size of satisfaction factor along study result and quantile and there was the significant difference statistically regarding regression coefficient for each quantile. So, to use quantile regression model that offers the influence of satisfaction factor for each customer group along satisfaction level would contribute to plan the quantitative convergence policy for customer satisfaction.

Threshold Selection Method for Capacity Optimization of the Digital Watermark Insertion (디지털 워터마크의 삽입용량 최적화를 위한 임계값 선택방법)

  • Lee, Kang-Seung;Park, Ki-Bum
    • Journal of the Institute of Convergence Signal Processing
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    • v.10 no.1
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    • pp.49-59
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    • 2009
  • In this paper a watermarking algorithm is proposed to optimize the capacity of the digital watermark insertion in an experimental threshold using the characteristics of human visual system(HVS), adaptive scale factors, and weight functions based on discrete wavelet transform. After the original image is decomposed by a 3-level discrete wavelet transform, the watermarks for capacity optimization are inserted into all subbands except the baseband, by applying the important coefficients from the experimental threshold in the wavelet region. The adaptive scale factors and weight functions based on HVS are considered for the capacity optimization of the digital watermark insertion in order to enhance the robustness and invisibility. The watermarks are consisted of gaussian random sequences and detected by correlation. The experimental results showed that this algorithm can preserve a fine image quality against various attacks such as the JPEG lossy compression, noise addition, cropping, blurring, sharpening, linear and non-linear filtering, etc.

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