• Korean Journal of Cognitive Science
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• v.23 no.3
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• pp.295-322
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• 2012

In this paper, we cluster similar word senses applying vector space model and HAL (Hyperspace Analog to Language). HAL measures corelation among words through a certain size of context (Lund and Burgess 1996). The similarity measurement between a word pair is cosine similarity based on the vector space model, which reduces distortion of space between high frequency words and low frequency words (Salton et al. 1975, Widdows 2004). We use PCA (Principal Component Analysis) and SVD (Singular Value Decomposition) to reduce a large amount of dimensions caused by similarity matrix. For sense similarity clustering, we adopt supervised and non-supervised learning methods. For non-supervised method, we use clustering. For supervised method, we use SVM (Support Vector Machine), Naive Bayes Classifier, and Maximum Entropy Method.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.4
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• pp.498-503
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• 2019

Electric propulsion ships are gaining widespread interest in the marine industry owing to extreme air pollution concerns. Consequently, several studies are actively being conducted for improving the power quality. Various methods have been developed that incorporate passive filters, notch filters, and active filters for reducing the harmonic content in the input current of a conventional diode front end rectifier. Among such filters, the active front end (AFE) rectifier is considered as an excellent technology. In this paper, current control for an AFE rectifier employing space vector PWM (Pulse Width Modulation) is proposed. Conventional current control methods for the AFE rectifier, hysteresis, SPWM (Sinusoidal Pulse Width Modulation), and SVPWM (Space Vector Pulse Width Modulation) were simulated by employing the PSIM software tool for analysis and comparisons. The results corroborate that SVPWM has the simplest structure and provides the best performance.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.2 s.308
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• pp.33-39
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• 2006

This paper presents the modified LVQ method for performance improvement of pattern classification. The proposed method uses the skewness of probability distribution between the input vectors and the reference vectors. During training, the reference vectors are closest to the input vectors using the probabilistic distribution of the input vectors, and they are positioned to approximate the decision surfaces of the theoretical Bayes classifier. In order to verify the effectiveness of the proposed method, we performed experiments on the Gaussian distribution data set, and the Fisher's IRIS data set. The experimental results show that the proposed method considerably improves on the performance of the LVQ1, LVQ2, and GLVQ.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.3C
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• pp.315-326
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• 2003

Abstract In this paper, an improved index assignment procedure is proposed to reduce the channel error effect in a communication system employing classified vector quantization(CVQ). The proposed algorithm consists of two parts: inner index assignment (IIA) and cross index assignment (CIA). The II A reduces the distortion resulting from the error in order bits, presenting the identity of each code vector in a subcodebook. The CIA modifies the indexes assigned by the IIA in such a way that the effect of the channel error occurring in class bits, indicating the class information of the code vector, can be minimized. Simulation results show that the proposed algorithms enable a reliable communication over noisy channels even without employing the channel encoding. Index Terms Classified vector quantization, index assignment.

• Journal of Broadcast Engineering
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• v.7 no.4
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• pp.310-316
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• 2002

In this paper, we propose an adaptive search range decision algorithm for fast motion estimation of video coding. Block matching algorithm for motion vector estimation that improves coding efficiency by reduction of temporal redundancy has trade-off problem between the motion vector accuracy and the complexity. The proposed algorithm playing as a pre-processing of fast motion estimation adaptively determines the motion search range by the local statistics of neighboring motion vectors. resulting in dramatic reduction of the computational cost without the loss of coding efficiency. Experimental results show the capability of the proposed algorithm.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.33-36
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• 1999

본 논문에서는 기존의 text-to-speech(TTS) 합성방식이 미리 정해진 화자에 의한 단조로운 합성음을 가지는 문제를 극복하기 위하여, 임의의 화자의 음색을 표현할 수 있는 화자 변환(Voice Conversion) 기능을 구현하였다. 구현된 방식은 화자의 음향공간을 Gaussian Mixture Model(GMM)로 모델링하여 연속 확률 분포에 따른 화자 변환을 가능케 했다. 원시화자(source)와 목적화자(target)간의 특징 벡터의 joint density function을 이용하여 목적화자의 음향공간 특징벡터와 변환된 벡터간의 제곱오류를 최소화하는 변환 함수를 구하였으며, 구해진 변환 함수로 벡터 mapping에 의한 스펙트럼 포락선을 변환했다. 운율 변환은 음성 신호를 정현파 모델에 의해서 모델링하고, 분석된 운율 정보(피치, 지속 시간)는 평균값을 고려해서 변환했다. 성능 평가를 위해서 VQ mapping 방법을 함께 구현하여 각각의 정규화된 켑스트럼 거리를 구해서 성능을 비교 평가하였다. 합성시에는 ABS-OLA 기반의 정현파 모델링 방식을 채택함으로써 자연스러운 합성음을 생성할 수 있었다.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.5
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• pp.31-36
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• 2011

In this paper, Mel-Frequency Cepstral Coefficient (MFCC), Decorrelated Filter Bank (DFB), Octave-based Spectral Contrast (OSC), Zero-Crossing Rate (ZCR), and Spectral Contract/Roll-Off are combined as a set of multiple feature-vectors for the music genre classification system based on the Support Vector Machine (SVM) classifier. In the conventional system, feature vectors for the entire genre classes are normalized for the SVM model training and classification. However, in this paper, selected feature vectors that are compared based on the One-Against-One (OAO) SVM classifier are only used for normalization. Using OSC as a single feature-vector and the multiple feature-vectors, we obtain the genre classification rates of 60.8% and 77.4%, respectively, with the conventional normalization method. Using the proposed normalization method, we obtain the increased classification rates by 8.2% and 3.3% for OSC and the multiple feature-vectors, respectively.

• Journal of Intelligence and Information Systems
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• v.3 no.2
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• pp.23-32
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• 1997

본 논문에서는 정성적 공간 표현 방식과 물체의 운동에 대한 추론 방식에 제시되었다. 기존의 정성적 벡터 표현 방식은 각도 개념을 추가하여 확장되었으며, 이에 따라 방향의 계산을 위해 필요한 정성적 벡터 연산도 확장되었다. 또한 회전운동에 의한 각도의 변화를 분석하는 추론 방식도 기술되었다. 운동에 대한 정성적 추론의 기본 아이디어는 공간에서의 위치와 운동을 상대적인 개념으로 표현하는 것이다. 이와같이 제안된 이론은 장치의 분석에 사용되어 주어진 연동 장치의 거동을 정확히 예측 할 수 있었다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1998.06a
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• pp.193-196
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• 1998

본 논문에서는 동영상 부호화에 있어서의 영상 간 중복성을 제거하기 위한 수단으로 사용되는 움직임 추정 방식에 관련된 내용으로 특히 밝기가 변하는 영상에 대해 부호화 성능을 높여 주는 움직임 추정방식에 대해 부호화 제안하였다. 제안한 움직임 추정은 기존의 평균 절대 오차나 평균 제곱 오차를 기반으로 하는 기존의 움직임 추정에 의한 움직임 벡터와 매크로블록 간 오차의 최소 분산을 가지는 움직임 벡터 중 부호화 시 적은 비트를 필요로 하는 움직임 벡터를 이용함으로써 일반 영상에는 기존의 방법과 유사한 부호화 성능을 나타내고, 화면의 밝기가 급격하게 변하는 영상에서는 기존의 방법보다 우수한 부호화 성능을 나타내도록 하는 방법이다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.12
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• pp.2618-2624
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• 2009

Harmonics (or distortion in wave form) has always existed in electrical power systems. It is harmless as long as its level is not substantial. However, with the recent rapid advancement of power electronics technology, so-called nonlinear loads, such as variable frequency drives for motor power/speed control, are increasingly finding their way to shipboard or offshore applications. In this paper a new approach to direct torque control (DTC) of induction motor drive is presented. In comparison with the conventional DTC methods the inverter switching frequency is constant and is dramatically increased, requiring neither any increase of the sampling frequency, nor any high frequency dither signal. The well-developed space vector modulation technique is applied to inverter control in the proposed DTC-based induction motor drive system, thereby dramatically reducing the current harmonics. As compared to the existing DTC approach with constant inverter switching frequency, the presented new approach does not invoke any concept of deadbeat control, thereby dramatically reducing the computations.