• Journal of the Korean Data and Information Science Society
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• v.19 no.2
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• pp.487-496
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• 2008

Recently survival analysis becomes popular in a variety of fields so that a number of statistical packages are developed for analyzing the survival model. In this paper, several types of survival models are introduced and considered briefly. In addition, widely used three packages(SAS, SPSS, and STATA) for survival data are reviewed and their characteristics are investigated.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.57-59
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• 1999

본 논문에서는 최대 엔트로피 원리에 기반한 문서 분류기의 학습을 제안한다. 최대 엔트로피 기법은 자연언어 처리에서 언어 모델링(Language Modeling), 품사 태깅 (Part-of-Speech Tagging) 등에 널리 사용되는 방법중의 하나이다. 최대 엔트로피 모델의 효율성을 위해서는 자질 선정이 중요한데, 본 논문에서는 자질 집합의 선택을 위한 기준으로 chi-square test, log-likelihood ratio, information gain, mutual information 등의 방법을 이용하여 실험하고, 전체 후보 자질에 대한 실험 결과와 비교해 보았다. 데이터 집합으로는 Reuters-21578을 사용하였으며, 각 클래스에 대한 이진 분류 실험을 수행하였다.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.221-222
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• 2008

We propose a LLR (log-likelihood ratio) selection combining technique that reduces much of complexity. This technique chooses the most reliable branch based on the magnitude of the LLR of each branch. We show that the proposed selection combining achieves significant power gains over conventional selection combining and nearly matches the performance provided by MRC.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.175-178
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• 2022

본 논문은 고차 계층 변조, 즉 계층 64QAM의 연판정 비트 검출을 위한 단순화된 연산 방법을 다룬다. 이는 기존 계층 변조의 연판정 비트, 즉 LLR(Log-Likelihood Ratio)값의 근사를 통해 불필요한 연산을 줄여 이에 필요한 지연시간을 줄일 수 있다. 또한 제안된 기법은 기존의 연판정 비트 검출 기법과 매우 유사한 비트 오류율(BER: Bit Error Rate) 성능을 유지하기 때문에 연판정 비트를 활용하는 방송 및 통신 시스템에 폭넓게 적용될 수 있을 것으로 기대한다.

• ETRI Journal
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• v.41 no.3
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• pp.308-315
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• 2019

Due to its high spectrum efficiency, 64-amplitude phase-shift keying (64-APSK) is one of the primary technologies used in deep space communications and digital video broadcasting through satellite-second generation. However, 64-APSK suffers from considerable computational complexity because of the de-mapping method that it employs. In this study, a low-complexity de-mapping method for (4 + 12 + 20 + 28) 64-APSK is proposed in which we take full advantage of the symmetric characteristics of each symbol mapping. Moreover, we map the detected symbol to the first quadrant and then divide the region in this first quadrant into several partitions to simplify the formula. Theoretical analysis shows that the proposed method requires no operation of exponents and logarithms and involves only multiplication, addition, subtraction, and judgment. Simulation results validate that the time consumption is dramatically decreased with limited degradation of bit error rate performance.

• Communications for Statistical Applications and Methods
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• v.9 no.3
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• pp.715-723
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• 2002

This paper is to show a clustering application of a density estimation method that utilizes the Gaussian mixture model. We define "closeness measure" as a clustering criterion to see how close given two Gaussian components are. Closeness measure is defined as the ratio of log likelihood between two Gaussian components. According to simulations using artificial data, the clustering algorithm turned out to be very powerful in that it can correctly determine clusters in complex situations, and very flexible in that it can produce different sizes of clusters based on different threshold valuesold values

• Proceedings of the KSPS conference
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• 2005.04a
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• pp.95-98
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• 2005

Many utterance verification (UV) algorithms have been studied to reject out-of-vocabulary (OOV) in speech recognition systems. Most of conventional confidence measures for UV algorithms are mainly based on log likelihood ratio test, but these measures take much time to evaluate the alternative hypothesis or anti-model likelihood. We propose a novel confidence measure which makes use of a momentary best scored state sequence during Viterbi search. Our approach is more efficient than conventional LRT-based algorithms because it does not need to build anti-model or to calculate the alternative hypothesis. The proposed confidence measure shows better performance in additive noise-corrupted speech as well as clean speech.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.2A
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• pp.107-112
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• 2009

Spectral efficiency of current two-phase cooperative communications protocols is low since in the second time the relay forwards the same signal received from the source to the destination, the source keeps silent in this time. In this paper, we propose a novel cooperative communications protocol where the signal needed to transmit to the destination is sent in both phases, the source and the relay also transmit different signal to the destination thus no loss of spectral efficiency. This protocol performs signal selection based on log-likelihood ratio (LLR) at relay and maximum likelihood (ML) detection at destination. While existing protocols pay for a worse performance than direct transmission in the low SNR regime which is of special interest in ad hoc networks, ours is better over the whole range of SNR. In addition, the proposal takes advantages of bandwidth efficiency, long delay and interference among many terminals in ad hoc network. Simulation results show that the proposed protocol can significantly save total energy for wireless ad hoc networks.

• Proceedings of the IEEK Conference
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• 2003.07a
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• pp.537-540
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• 2003

본 논문에서는 터보 디코더에 사용되는 MAP 알고리즘의 저전력 구조를 제안한다. 터보 디코더 알고리즘 중 하나인 MAP 알고리즘은 많은 메모리 사이즈와 복잡한 연산량을 가진다. 본 논문에서는 메모리 사이즈를 줄이기 위하여 두 번의 상태 천이(branch metric) 과정을 하나로 통합 계산하는 방식을 제안하였다. 제안된 방식으로 구한 상태 천이 값을 이용해서 FSM(Forward State Metric)값을 구하면 BM(branch metric)값이 다음 상태의 FSM에 포함되어지므로 APP(A Posteriori Probability)를 계산할 때 BM부분이 빠져 LLR(Log Likelihood Ratio)의 연산량을 줄일 수 있다. 실험결과 기존의 MAP 알고리즘과 동일 성능을 가지면서 MAP 알고리즘을 개선한 Pietrobon 알고리즘을 log-MAP 알고리즘에 적용하여 LLR 연산량을 비교했을 때 덧셈 연산을 반으로 줄일 수 있음을 확인하였다.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.135-144
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• 2003

This work is concerned with comparison of the recently developed disparity measures for the partial association model in three dimensional categorical data. Data are generated by using simulation on each term in the log-linear model equation based on the partial association model, which is a proposed method in this paper. This alternative Monte Carlo methods are explored to study the behavior of disparity measures such as the power divergence statistic I(λ), the Pearson chi-square statistic X$^2$, the likelihood ratio statistic G$^2$, the blended weight chi-square statistic BWCS(λ), the blended weight Hellinger distance statistic BWHD(λ), and the negative exponential disparity statistic NED(λ) for moderate sample sizes. We find that the power divergence statistic I(2/3) and the blended weight Hellinger distance family BWHD(1/9) are the best tests with respect to size and power.