• 대한전기학회:학술대회논문집
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• 대한전기학회 1991년도 하계학술대회 논문집
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• pp.870-873
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• 1991

In this paper, We present demodulation and synchronization method of phase shift keying signal using Double Frequency Vector Technique for Reference Vector. 2nd Harmonic Vector for Reference Vector is utilized in discriminating between noise and carrier signal, and in producting correlation value for data bit logical level. And we applied this demodulator to Automatic Meter Reading System being communicated with electric distribution power lines.

• 한국컴퓨터산업학회논문지
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• 제5권9호
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• pp.987-992
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• 2004

비디오 시퀀스의 현재 블록의 움직임 벡터와 이전 블록의 움직임 벡터는 시간적 상관성을 갖고있다. 본 논문에서는 현재 프레임 블록의 인접 블록으로부터 예측된 움직임 정보를 구하여, 이를탐색 원점으로 하여 수정된 다이아몬드 지역 레이더 패턴으로 블록 정합을 수행하는 블록 정합움직임 추정 방식을 제안한다. 실험 결과 제안된 방식은 전역탐색을 제외한 기존의 방식들에 비해 PSNR 값에 있어서 평균적으로 0.02~0.37[dB] 개선되고 움직임 벡터 예측의 속도에 있어서 약 14~24% 이상의 높은 성능 향상을 보였다.

• Journal of information and communication convergence engineering
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• 제15권3호
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• pp.137-142
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• 2017

A general linearly constrained narrowband adaptive array is examined in the eigenvector space. The optimum weight vector in the eigenvector space is shown to have the same performance as in the standard coordinate system, except that the input signal correlation matrix and look direction steering vector are replaced with the eigenvalue matrix and transformed steering vector. It is observed that the variation in gain factor results in the variation in the distance between the constraint plane and the origin in the translated weight vector space such that the increase in gain factor decreased the distance from the constraint plane to the origin, thus affecting the nulling performance. Simulation results showed that the general linearly constrained adaptive array performed better at an optimal gain factor compared with the conventional linearly constrained adaptive array in a coherent signal environment and the former showed similar performance as the latter in a noncoherent signal environment.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2004년도 전력전자학술대회 논문집(2)
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• pp.620-624
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• 2004

Th is paper presents a systematical approach to study carrier based PWM techniques (CPWM) in diode-clamped and cascade multilevel inverters by using the proposed multi-modulating pattern method. This method is based on the vector correlation between CPWM and space vector PWM (SVPWM) and applicable to both multilevel inverter topologies. The CPWM technique can be described in a general mathematical equation, and obtain the same outputs similarly as of corresponding SVPWM. Control of the fundamental voltage, vector redundancies and phase redundancies in multilevel inverter can be formulated separately in the CPWM equation. The deduced CPWM can obtain a full vector redundancy control, and fully utilize phase redundancy in a cascade inverter. In the paper, CPWM equations and corresponding algorithm for generating multi-modulating signals will be performed, in which SVPWM attributes will be presented by corresponding controllable factors.

• 말소리와 음성과학
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• 제7권4호
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• pp.41-47
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• 2015

This paper examines whether the Global Vector model is applicable to Korean data as a universal learning algorithm. The main purpose of this study is to compare the global vector model (GloVe) with the word2vec models such as a continuous bag-of-words (CBOW) model and a skip-gram (SG) model. For this purpose, we conducted an experiment by employing an evaluation corpus consisting of 70 target words and 819 pairs of Korean words for word similarities and analogies, respectively. Results of the word similarity task indicated that the Pearson correlation coefficients of 0.3133 as compared with the human judgement in GloVe, 0.2637 in CBOW and 0.2177 in SG. The word analogy task showed that the overall accuracy rate of 67% in semantic and syntactic relations was obtained in GloVe, 66% in CBOW and 57% in SG.

• 품질경영학회지
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• 제29권1호
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• pp.1-10
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• 2001

We consider the problem of detecting special variations in multivariate $T^2$-control chart when two or more multivariate outliers are present. Since a multivariate outlier may reflect slippage in mean, variance, or correlation, it can distort the sample mean vector and sample covariance matrix. Damaged sample mean vector and sample covariance matrix have difficulty in examining special variations clearly, An alternative to detection outliers or special variations is to use robust estimators of mean vector and covariance matrix that are less sensitive to extreme observations than are the standard estimators $\bar{x}$ and $\textbf{S}$. We applied popular minimum volume ellipsoid(MVE) and minimum covariance determinant(MCD) method to estimate mean vector and covariance matrix and compared its results with standard $T^2$-control chart using simulated multivariate data with outliers. We found that the modified $T^2$-control chart based on the above robust methods were more effective in detecting special variations clearly than the standard $T^2$-control chart.

• 전자공학회논문지S
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• 제35S권5호
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• pp.59-67
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• 1998

This paper propose a new vector-quantizer design method for coefficients of wavelet transformed images. In conventional wavelet transform, it is quite often to employ wavelet transformed coefficients, not containing images to be encoded, as training sequences for designing a vector-quantizer. This method has a serious drawback ; it is not known how to find a proper set of training images. This paper investigates characteristics of images that should be considered in the design of vector-quantizers for wavelet transformed images. Besides the statistical parameters such as correlation and standard deviation, edge components are shown to characterise wavelet transform images. Training sequences established in accordance with the above knowledge are used in the design of quantizers having guaranteed range of applicable images. Results of computer simulations are shown to demonstrate the effectiveness of the proposed method.

• International Journal of Contents
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• 제1권2호
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• pp.26-30
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• 2005

According to the fast growth of information on the Internet, it is becoming increasingly difficult to find and organize useful information. To reduce information overload, it needs to exploit automatic text classification for handling enormous documents. Support Vector Machine (SVM) is a model that is calculated as a weighted sum of kernel function outputs. This paper describes a document classifier for web documents in the fields of Information Technology and uses SVM to learn a model, which is constructed from the training sets and its representative terms. The basic idea is to exploit the representative terms meaning distribution in coherent thematic texts of each category by simple statistics methods. Vector-space model is applied to represent documents in the categories by using feature selection scheme based on TFiDF. We apply a category factor which represents effects in category of any term to the feature selection. Experiments show the results of categorization and the correlation of vector length.

• 한국통신학회논문지
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• 제33권10A호
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• pp.1006-1012
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• 2008

Duvall 구조에 기초하여 코히런트(coherent), 인코히런트(incoherent) 간섭을 제거하는 효율적인 적응 빔 형성방법을 제시한다. 하나의 상관벡터를 이용하는 기존방식과 달리, 제안된 방법에서는 여러 개의 상관벡터를 이용하여 가중벡터의 차원을 크게 한다. 가중벡터 차원의 증가로 빔 형성기의 SINR(signal-to-interference plus noise ratio) 성능을 개선할 수 있으며, 더 많은 간섭을 제거 할 수 있다. 시뮬레이션 결과에 따르면, 제안방식은 기존방식에 비해 빠른 수렴특성, 우수한 정상상태(steady-state)에서의 SINR 성능을 보여준다.

• 한국통신학회논문지
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• 제24권12B호
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• pp.2401-2406
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• 1999

압축된 비디오 데이터에서 내용기반 컷 검출을 위해 다양한 특징 벡터 추출 방법이 연구되고 있다. 특징 벡터로써 화소값의 히스토그램을 이용한 방법의 경우 화소의 공간적 특성을 고려하지 않아 정확히 컷 검출을 기대하기 어렵다. 그래서 CCV(Color Coherent Vector)나 Color Correlogram등의 계산량이 복잡한 알고리즘이 많이 사용된다. 그러나 이러한 기법들은 정확한 컷 검출을 가능하게 하나 계산량이 너무 복잡하기 때문에 검출 시간이 많이 소요되는 단점이 있다. 본 논문에서는 MPEG 비디오 시퀀스에서 휘도성분의 DC값들의 공간적 상관도를 이용한 컷 검출 기법을 제안한다. 이 기법은 비교적 간단하기 때문에 처리 시간이 빠르며 또한 개선된 특징차 비교방법을 이용하여 검출율을 더 높일 수 있다.